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152 pts total For Questions 1-2 use the 7 step process to answer. Refer to slides if you are unsure of the 7 step process. PLEASE DON’T OMIT ANY PART OF THE PROCESS!!! (40 pts) THIS IS DONE IN SPSS USING BREAST CANCER AND OBESITY DATASET Dataset Background – PLEASE READ: Obesity is very common in American society and is a risk factor for breast cancer for postmenopausal women. One mechanism explaining why obesity is a risk factor is that it may raise estrogen levels in women. In particular, one type of estrogen, serum estradiol, is a strong risk factor for breast cancer. To better assess this relationship, researchers studied a group of 200 postmenopausal women. The SPSS file is entitled, Breast Cancer and Obesity . Adiposity was measured in two different ways: (a) by body mass index (BMI) = weight (kg) / height(m 2 ) and also (b) by waist-hip ratio (WHR) = waist circumference/hip circumference. BMI is a measure of overall adiposity, whereas WHR is a measure of abdominal adiposity. In addition, a complete hormonal profile was obtained, including serum estradiol. Finally, other breast-cancer risk factors were also assessed among these women, including ethnicity, parity, age at first birth, and age at menarche. Codebook Variable Column Code Label Values (if categorical) Id 1 Identification number ES_1 2 Serum Estradiol ETHNIC 3 Ethnicity 1 = African-American, 0 = Caucasian NUMCHILD 4 Parity, number of children AGEFBO 5 Age at 1 st birth (missing a response if never had a child) ANYKIDS 6 Gave birth to any children? 1 = Yes, 0 = No AGEMENAR 7 Age at menarche BMI 8 Body Mass Index WHR 9 Waist-hip ratio **Missing responses are left blank ALSO THE FOLLOWING CONTINUOUS VARIABLES HAVE BEEN CATEGORIZED!! BMI has been categorized, bmi_cat, : normal BMI (<25) and abnormal BMI (25 or greater). Menarche has been categorized, menarche_cat, two categories - 9-12 and 13-16 WHR has also been categorized, whr_category, 3 categories - 0-.69, .7-.79, and .8 and greater 1. Is there a statistically significant difference in mean estradiol between African Americans and Caucasions? a. Provide a visual aid depicting the mean differences between the two groups. 2. Is there a statistically significant difference in mean estradiol between ethnicity status depending on BMI_CAT (using the categorized variable, so normal or abnormal groups)? 3. Please use the rock climbing performance dataset. Here is the description: This is research done by a senior at PSU-Berks. He was interested in determining the effects of imagery on rock climbing performance. He chose 20 experienced rock climbers. With randomization on the order, he had them climb with no imagery on a rock wall and then had them climb with imagery (on a different but same difficulty wall). Ignoring issues of confounding, can we conclude that imagery decreases rock wall climb time (in seconds)? (15pts) a. What statistical test should be use.
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Kines 260 Take Home FinalNameDue Friday December 12th at 11 A.docx
Kines 260 Take Home Final
Name:
Due Friday December 12th at 11 A.M. in my mailbox
152 pts total
For Questions 1-2 use the 7 step process to answer. Refer to slides if you are unsure of the 7 step process. PLEASE DON’T OMIT ANY PART OF THE PROCESS!!! (40 pts) THIS IS DONE IN SPSS USING BREAST CANCER AND OBESITY DATASET
Dataset Background – PLEASE READ:
Obesity is very common in American society and is a risk factor for breast cancer for postmenopausal women. One mechanism explaining why obesity is a risk factor is that it may raise estrogen levels in women. In particular, one type of estrogen, serum estradiol, is a strong risk factor for breast cancer. To better assess this relationship, researchers studied a group of 200 postmenopausal women. The SPSS file is entitled, Breast Cancer and Obesity.
Adiposity was measured in two different ways: (a) by body mass index (BMI) = weight (kg) / height (m2) and also (b) by waist-hip ratio (WHR) = waist circumference/hip circumference. BMI is a measure of overall adiposity, whereas WHR is a measure of abdominal adiposity. In addition, a complete hormonal profile was obtained, including serum estradiol. Finally, other breast-cancer risk factors were also assessed among these women, including ethnicity, parity, age at first birth, and age at menarche.
Codebook
Variable
Column
Code
Label
Values (if categorical)
Id
1
Identification number
ES_1
2
Serum Estradiol
ETHNIC
3
Ethnicity
1 = African-American, 0 = Caucasian
NUMCHILD
4
Parity, number of children
AGEFBO
5
Age at 1st birth
(missing a response if never had a child)
ANYKIDS
6
Gave birth to any children?
1 = Yes, 0 = No
AGEMENAR
7
Age at menarche
BMI
8
Body Mass Index
WHR
9
Waist-hip ratio
**Missing responses are left blank
ALSO THE FOLLOWING CONTINUOUS VARIABLES HAVE BEEN CATEGORIZED!!
· BMI has been categorized, bmi_cat, : normal BMI (<25) and abnormal BMI (25 or greater).
· Menarche has been categorized, menarche_cat, two categories - 9-12 and 13-16
· WHR has also been categorized, whr_category, 3 categories - 0-.69, .7-.79, and .8 and greater
1. Is there a statistically significant difference in mean estradiol between African Americans and Caucasions?
a. Provide a visual aid depicting the mean differences between the two groups.
2. Is there a statistically significant difference in mean estradiol between ethnicity status depending on BMI_CAT (using the categorized variable, so normal or abnormal groups)?
3. Please use the rock climbing performance dataset. Here is the description: This is research done by a senior at PSU-Berks. He was interested in determining the effects of imagery on rock climbing performance. He chose 20 experienced rock climbers. With randomization on the order, he had them climb with no imagery on a rock wall and then had them climb with imagery (on a different but same difficulty ...
Multiple Linear Regression Homework Help
I am Samson H. I am a Multiple Linear Regression Homework Expert at statisticshomeworkhelper.com. I hold a Master's in Statistics, from Michigan, USA. I have been helping students with their homework for the past 12 years. I solved homework related to Multiple Linear Regression.
Visit statisticshomeworkhelper.com or email info@statisticshomeworkhelper.com.You can also call on +1 678 648 4277 for any assistance with Multiple Linear Regression Homework Help.
14 + 8 Answers and calculations as basic statistics student would ex.docx
14 + 8 Answers and calculations as basic statistics student would explain put into both an MS Excel spreadsheet and copied into MS Word doc format. Due by 7pm 2/2/14.
Week 2 Assignment
A. What is the probability of rolling a four in the gambling dice game of craps (given two six sided dice)?
B. What is the probability that a player can roll a four 3 times in a row (assume that rolling the dice each time does not affect the outcome of the next roll)?
Population A and Population B both have a mean height of 70.0 inches with an SD of 6.0. A random sample of 30 people is picked from population A, and random sample of 50 people is selected from Population B. Which sample mean will probably yield a more accurate estimate of its population mean? Why?
3. Suppose we obtained data on vein size after application of a nitroglycerin ointment in a sample of 50 patients. The mean vein size is found to be 7.8mm with an SD of 2.1. Using a
t
distribution table, what are the confidence limits for a 95% confidence interval? For a 99% confidence interval?
4. In a pilot study evaluating the use of a new drug to lower resting heart rates (HR) of patients, the following data was recorded:
Subject #
Resting HR
001
72
002
88
003
71
004
87
005
64
006
77
007
79
008
59
009
66
010
68
011
78
012
89
013
91
014
81
015
77
016
75
017
69
Given that the average resting HR of the general population for this study is 72, use StatCrunch to perform the appropriate
t
test. What is the value of
t
? Using an alpha of 0.05, is the
t
statistic significant? Why? What are the confidence limits for a 95% confidence interval here and what do they mean for this patient group? Copy and Paste your work from StatCrunch into your Word document submission.
5. Write one or two sentences that could be used to report the results obtained for the t-test in Exercise 4.
6. For which of the following situations is the
independent
groups t-test appropriate (if inappropriate, why?):
a. The independent variable is infant birth weight at one week (normal vs high); the dependent variable is resting heart rate.
b. The independent variable is radiation treatment on throat cancer patients (after a low dose and then a high dose treatment); the dependent variable is white blood cell count.
c. The IV is infant birth weight (low vs normal birth weight); the DV is number of days absent from school in first grade.
d. The IV is gender (male vs female); the DV is compliance vs noncompliance with a medication regimen.
e. The independent variable is married status (single vs divorced vs married); the dependent variable is happiness measured on a scale from 1 to 50
7. For which of the following situations is the
dependent
groups t-test appropriate (if not appropriate, why?)
a. The IV is presence or absence of conversation directed to comato.
Multiple Linear Regression Homework Help
I am Samson H. I am a Multiple Linear Regression Homework Expert at excelhomeworkhelp.com. I hold a Master's in Statistics, from Michigan, USA. I have been helping students with their homework for the past 7 years. I solved homework related to Multiple Linear Regression.
Visit excelhomeworkhelp.com or email info@excelhomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Multiple Linear Regression Homework.
Week 2 Assignment1. A. What is the probability of rolling a four.docx
This document contains instructions and questions for a statistics assignment involving probability, confidence intervals, hypothesis testing using t-tests and ANOVA, chi-square tests, and matching statistical tests to research situations. It includes 14 multiple choice and short answer questions requiring calculations and interpretations of statistical analyses on sample data using the StatCrunch software.
Nonparametric Test Chi-Square Test for Independence Th.docx
Nonparametric Test
Chi-Square Test for Independence
The test is used to determine whether two categorical variables are independent.
Notation for the Chi-Square Test for Independence (Please note that the notation varies
depending on the text)
O represents the observed frequency of an outcome
E represents the expected frequency of an outcome
r represents the number of rows in the contingency table
c represents the number of columns in the contingency table
n represents the total number of trials
Test Statistic
2
2
1 1
O E
E
df r c
The Chi-Square test is a hypothesis test. There are seven steps for a hypothesis test.
1. State the null hypothesis
2. State the alternative hypothesis
3. State the level of significance
4. State the test statistic
5. Calculate
6. Statistical Conclusion
7. Experimental Conclusion
Example
A university is interested to know if the choice of major has a relationship to gender. A
random sample of 200 incoming freshmen students was taken (100 male and 100
female). There major and gender were recorded. The results are shown in the
contingency table below.
Major Female Male
Math 5 15
Nursing 44 10
English 10 10
Pre-Med 17 20
History 4 5
Education 15 20
Undecided 5 20
To determine if there is a relationship between the gender of a freshmen student and
thei declared major perform the hypothesis test (Use level of significance 0.05 ) .
Step 1: Null Hypothesis
0 : Gender and Major of Freshmen students are independentH
Step 2: Alternative Hypothesis
: Gender and Major of Freshmen students are not independentAH
Step 3: Level of Significance
0.05
Step 4: Test Statistic
2
2
1 1
O E
E
df r c
Step 5: Calculations
There are several calculations for this test. We have to find the expected frequency for
each cell in the contingency table. The expected frequency is the probability under the
null hypothesis times the total frequency for the given row. Here the probability under
the null hypothesis is .5, as the probability of being male and female is equal.
rE pn
Major Female Male
Math 1 .5 20 10E 2 .5 20 10E
Nursing 3 .5 54 27E 4 .5 54 27E
English 5 .5 20 10E 6 .5 20 10E
Pre-Med 7 .5 37 18.5E 8 .5 37 18.5E
History 9 .5 9 4.5E 10 .5 9 4.5E
Education 11 .5 35 17.5E 12 .5 35 17.5E
Undecided 13 .5 25 12.5E 14 .5 25 12.5E
Know calculate the test statistic.
2
2
2 2 2 2
2
2 2 2 2
2 2 2 2
2 2
2
5 10 15 10 44 27 10 27
10 10 27 27
10 10 10 10 17 18.5 20 18.5
10 10 18.5 18.5
4 4.5 5 4.5 15 17.5 20 17.5
4.5 4.5 17.5 17.5
5 12.5 20 12.5
12.5 12.5
2.5 2.5 10.7 10.7 0 0 .1216
obs
ob.
WEEK 7 – EXERCISES Enter your answers in the spaces pr.docx
WEEK 7 – EXERCISES
Enter your answers in the spaces provided. Save the file using your last name as the beginning of the file name (e.g., ruf_week6_exercises) and submit via “Assignments.” When appropriate,
show your work
. You can do the work by hand, scan/take a digital picture, and attach that file with your work.
A sports researcher gave a standard written test of eating habits to 12 randomly selected professionals, four each from baseball, football, and basketball. The results were as follows:
Eating Habits Scores
Baseball Players
Football Players
Basketball Players
34
27
35
18
28
44
21
67
47
65
42
61
Is there a difference in eating habits among professionals in the three sports? (Use the .05 significance level.)
a.
Use the five steps of hypothesis testing.
b.
Sketch the distribution involved.
c.
Determine effect size.
2.
To study the effectiveness of treatments for insomnia, a sleep researcher conducted a study with 12 participants.
Four participants were instructed to count sheep (Sheep Condition), four were told to concentrate on their breathing (Breathing Condition), and four were not given any special instructions. Over the next few days, measures were taken of how many minutes it took each participant to fall asleep. The average times for the participants in the Sheep Condition were 14, 28, 27, and 31; for those in the Breathing Condition, 25, 22, 17, and 14; and for those in the control condition, 45, 33, 30, and 41.
Do these results suggest that the different techniques have different effects?
(Use the .05 significance level.)
a.
Use the five steps of hypothesis testing.
b.
Sketch the distribution involved.
c.
Figure the effect size of the study.
d.
Explain your findings (including the logic of comparing within-group to between-group population variance estimates, how each of these is figured, and the
F
distribution).
High school juniors planning to attend college were randomly assigned to view one of four videos about a particular college, each differing according to what aspect of college life was emphasized: athletics, social life, scholarship, or artistic/cultural opportunities. After viewing the videos, the students took a test measuring their desire to attend this college. The results were as follows:
Desire to Attend this College
Athletics
Social Life
Scholarship
Art/Cultural
68
89
74
76
56
78
82
71
69
81
79
69
70
77
80
65
Do these results suggest that the type of activity emphasized in a college film affects desire to attend that college? (Use the .01 significance level.)
a.
Use the five steps of hypothesis testing.
b.
Sketch the distribution involved.
c.
Figure the effect size of the study.
d.
Explain the logic of what you have done to a person who is unfamiliar with the analysis of variance.
A team of psychologists designed a study in which 12 psychiatric patients diagnosed as having generalized anxiety disorder were randomly assigned to one of three new types of th.
Data quality assurance
This document discusses the importance of quality assurance in gait analysis. It emphasizes that measurements must be accurate if meaningful interpretations are to be made. Staff training, vigilance for errors, repeatability studies, and ensuring data consistency are key aspects of quality assurance. Formal training in both the science and art of gait analysis is needed. Differences between labs may suggest systematic differences in measurement practices, highlighting the need for standardization. Quality assurance also requires an open culture and consideration of multiple data sources to validate findings and catch errors.
Recommended
Kines 260 Take Home FinalNameDue Friday December 12th at 11 A.docx
Kines 260 Take Home Final
Name:
Due Friday December 12th at 11 A.M. in my mailbox
152 pts total
For Questions 1-2 use the 7 step process to answer. Refer to slides if you are unsure of the 7 step process. PLEASE DON’T OMIT ANY PART OF THE PROCESS!!! (40 pts) THIS IS DONE IN SPSS USING BREAST CANCER AND OBESITY DATASET
Dataset Background – PLEASE READ:
Obesity is very common in American society and is a risk factor for breast cancer for postmenopausal women. One mechanism explaining why obesity is a risk factor is that it may raise estrogen levels in women. In particular, one type of estrogen, serum estradiol, is a strong risk factor for breast cancer. To better assess this relationship, researchers studied a group of 200 postmenopausal women. The SPSS file is entitled, Breast Cancer and Obesity.
Adiposity was measured in two different ways: (a) by body mass index (BMI) = weight (kg) / height (m2) and also (b) by waist-hip ratio (WHR) = waist circumference/hip circumference. BMI is a measure of overall adiposity, whereas WHR is a measure of abdominal adiposity. In addition, a complete hormonal profile was obtained, including serum estradiol. Finally, other breast-cancer risk factors were also assessed among these women, including ethnicity, parity, age at first birth, and age at menarche.
Codebook
Variable
Column
Code
Label
Values (if categorical)
Id
1
Identification number
ES_1
2
Serum Estradiol
ETHNIC
3
Ethnicity
1 = African-American, 0 = Caucasian
NUMCHILD
4
Parity, number of children
AGEFBO
5
Age at 1st birth
(missing a response if never had a child)
ANYKIDS
6
Gave birth to any children?
1 = Yes, 0 = No
AGEMENAR
7
Age at menarche
BMI
8
Body Mass Index
WHR
9
Waist-hip ratio
**Missing responses are left blank
ALSO THE FOLLOWING CONTINUOUS VARIABLES HAVE BEEN CATEGORIZED!!
· BMI has been categorized, bmi_cat, : normal BMI (<25) and abnormal BMI (25 or greater).
· Menarche has been categorized, menarche_cat, two categories - 9-12 and 13-16
· WHR has also been categorized, whr_category, 3 categories - 0-.69, .7-.79, and .8 and greater
1. Is there a statistically significant difference in mean estradiol between African Americans and Caucasions?
a. Provide a visual aid depicting the mean differences between the two groups.
2. Is there a statistically significant difference in mean estradiol between ethnicity status depending on BMI_CAT (using the categorized variable, so normal or abnormal groups)?
3. Please use the rock climbing performance dataset. Here is the description: This is research done by a senior at PSU-Berks. He was interested in determining the effects of imagery on rock climbing performance. He chose 20 experienced rock climbers. With randomization on the order, he had them climb with no imagery on a rock wall and then had them climb with imagery (on a different but same difficulty ...
Multiple Linear Regression Homework Help
I am Samson H. I am a Multiple Linear Regression Homework Expert at statisticshomeworkhelper.com. I hold a Master's in Statistics, from Michigan, USA. I have been helping students with their homework for the past 12 years. I solved homework related to Multiple Linear Regression.
Visit statisticshomeworkhelper.com or email info@statisticshomeworkhelper.com.You can also call on +1 678 648 4277 for any assistance with Multiple Linear Regression Homework Help.
14 + 8 Answers and calculations as basic statistics student would ex.docx
14 + 8 Answers and calculations as basic statistics student would explain put into both an MS Excel spreadsheet and copied into MS Word doc format. Due by 7pm 2/2/14.
Week 2 Assignment
A. What is the probability of rolling a four in the gambling dice game of craps (given two six sided dice)?
B. What is the probability that a player can roll a four 3 times in a row (assume that rolling the dice each time does not affect the outcome of the next roll)?
Population A and Population B both have a mean height of 70.0 inches with an SD of 6.0. A random sample of 30 people is picked from population A, and random sample of 50 people is selected from Population B. Which sample mean will probably yield a more accurate estimate of its population mean? Why?
3. Suppose we obtained data on vein size after application of a nitroglycerin ointment in a sample of 50 patients. The mean vein size is found to be 7.8mm with an SD of 2.1. Using a
t
distribution table, what are the confidence limits for a 95% confidence interval? For a 99% confidence interval?
4. In a pilot study evaluating the use of a new drug to lower resting heart rates (HR) of patients, the following data was recorded:
Subject #
Resting HR
001
72
002
88
003
71
004
87
005
64
006
77
007
79
008
59
009
66
010
68
011
78
012
89
013
91
014
81
015
77
016
75
017
69
Given that the average resting HR of the general population for this study is 72, use StatCrunch to perform the appropriate
t
test. What is the value of
t
? Using an alpha of 0.05, is the
t
statistic significant? Why? What are the confidence limits for a 95% confidence interval here and what do they mean for this patient group? Copy and Paste your work from StatCrunch into your Word document submission.
5. Write one or two sentences that could be used to report the results obtained for the t-test in Exercise 4.
6. For which of the following situations is the
independent
groups t-test appropriate (if inappropriate, why?):
a. The independent variable is infant birth weight at one week (normal vs high); the dependent variable is resting heart rate.
b. The independent variable is radiation treatment on throat cancer patients (after a low dose and then a high dose treatment); the dependent variable is white blood cell count.
c. The IV is infant birth weight (low vs normal birth weight); the DV is number of days absent from school in first grade.
d. The IV is gender (male vs female); the DV is compliance vs noncompliance with a medication regimen.
e. The independent variable is married status (single vs divorced vs married); the dependent variable is happiness measured on a scale from 1 to 50
7. For which of the following situations is the
dependent
groups t-test appropriate (if not appropriate, why?)
a. The IV is presence or absence of conversation directed to comato.
Multiple Linear Regression Homework Help
I am Samson H. I am a Multiple Linear Regression Homework Expert at excelhomeworkhelp.com. I hold a Master's in Statistics, from Michigan, USA. I have been helping students with their homework for the past 7 years. I solved homework related to Multiple Linear Regression.
Visit excelhomeworkhelp.com or email info@excelhomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Multiple Linear Regression Homework.
Week 2 Assignment1. A. What is the probability of rolling a four.docx
This document contains instructions and questions for a statistics assignment involving probability, confidence intervals, hypothesis testing using t-tests and ANOVA, chi-square tests, and matching statistical tests to research situations. It includes 14 multiple choice and short answer questions requiring calculations and interpretations of statistical analyses on sample data using the StatCrunch software.
Nonparametric Test Chi-Square Test for Independence Th.docx
Nonparametric Test
Chi-Square Test for Independence
The test is used to determine whether two categorical variables are independent.
Notation for the Chi-Square Test for Independence (Please note that the notation varies
depending on the text)
O represents the observed frequency of an outcome
E represents the expected frequency of an outcome
r represents the number of rows in the contingency table
c represents the number of columns in the contingency table
n represents the total number of trials
Test Statistic
2
2
1 1
O E
E
df r c
The Chi-Square test is a hypothesis test. There are seven steps for a hypothesis test.
1. State the null hypothesis
2. State the alternative hypothesis
3. State the level of significance
4. State the test statistic
5. Calculate
6. Statistical Conclusion
7. Experimental Conclusion
Example
A university is interested to know if the choice of major has a relationship to gender. A
random sample of 200 incoming freshmen students was taken (100 male and 100
female). There major and gender were recorded. The results are shown in the
contingency table below.
Major Female Male
Math 5 15
Nursing 44 10
English 10 10
Pre-Med 17 20
History 4 5
Education 15 20
Undecided 5 20
To determine if there is a relationship between the gender of a freshmen student and
thei declared major perform the hypothesis test (Use level of significance 0.05 ) .
Step 1: Null Hypothesis
0 : Gender and Major of Freshmen students are independentH
Step 2: Alternative Hypothesis
: Gender and Major of Freshmen students are not independentAH
Step 3: Level of Significance
0.05
Step 4: Test Statistic
2
2
1 1
O E
E
df r c
Step 5: Calculations
There are several calculations for this test. We have to find the expected frequency for
each cell in the contingency table. The expected frequency is the probability under the
null hypothesis times the total frequency for the given row. Here the probability under
the null hypothesis is .5, as the probability of being male and female is equal.
rE pn
Major Female Male
Math 1 .5 20 10E 2 .5 20 10E
Nursing 3 .5 54 27E 4 .5 54 27E
English 5 .5 20 10E 6 .5 20 10E
Pre-Med 7 .5 37 18.5E 8 .5 37 18.5E
History 9 .5 9 4.5E 10 .5 9 4.5E
Education 11 .5 35 17.5E 12 .5 35 17.5E
Undecided 13 .5 25 12.5E 14 .5 25 12.5E
Know calculate the test statistic.
2
2
2 2 2 2
2
2 2 2 2
2 2 2 2
2 2
2
5 10 15 10 44 27 10 27
10 10 27 27
10 10 10 10 17 18.5 20 18.5
10 10 18.5 18.5
4 4.5 5 4.5 15 17.5 20 17.5
4.5 4.5 17.5 17.5
5 12.5 20 12.5
12.5 12.5
2.5 2.5 10.7 10.7 0 0 .1216
obs
ob.
WEEK 7 – EXERCISES Enter your answers in the spaces pr.docx
WEEK 7 – EXERCISES
Enter your answers in the spaces provided. Save the file using your last name as the beginning of the file name (e.g., ruf_week6_exercises) and submit via “Assignments.” When appropriate,
show your work
. You can do the work by hand, scan/take a digital picture, and attach that file with your work.
A sports researcher gave a standard written test of eating habits to 12 randomly selected professionals, four each from baseball, football, and basketball. The results were as follows:
Eating Habits Scores
Baseball Players
Football Players
Basketball Players
34
27
35
18
28
44
21
67
47
65
42
61
Is there a difference in eating habits among professionals in the three sports? (Use the .05 significance level.)
a.
Use the five steps of hypothesis testing.
b.
Sketch the distribution involved.
c.
Determine effect size.
2.
To study the effectiveness of treatments for insomnia, a sleep researcher conducted a study with 12 participants.
Four participants were instructed to count sheep (Sheep Condition), four were told to concentrate on their breathing (Breathing Condition), and four were not given any special instructions. Over the next few days, measures were taken of how many minutes it took each participant to fall asleep. The average times for the participants in the Sheep Condition were 14, 28, 27, and 31; for those in the Breathing Condition, 25, 22, 17, and 14; and for those in the control condition, 45, 33, 30, and 41.
Do these results suggest that the different techniques have different effects?
(Use the .05 significance level.)
a.
Use the five steps of hypothesis testing.
b.
Sketch the distribution involved.
c.
Figure the effect size of the study.
d.
Explain your findings (including the logic of comparing within-group to between-group population variance estimates, how each of these is figured, and the
F
distribution).
High school juniors planning to attend college were randomly assigned to view one of four videos about a particular college, each differing according to what aspect of college life was emphasized: athletics, social life, scholarship, or artistic/cultural opportunities. After viewing the videos, the students took a test measuring their desire to attend this college. The results were as follows:
Desire to Attend this College
Athletics
Social Life
Scholarship
Art/Cultural
68
89
74
76
56
78
82
71
69
81
79
69
70
77
80
65
Do these results suggest that the type of activity emphasized in a college film affects desire to attend that college? (Use the .01 significance level.)
a.
Use the five steps of hypothesis testing.
b.
Sketch the distribution involved.
c.
Figure the effect size of the study.
d.
Explain the logic of what you have done to a person who is unfamiliar with the analysis of variance.
A team of psychologists designed a study in which 12 psychiatric patients diagnosed as having generalized anxiety disorder were randomly assigned to one of three new types of th.
Data quality assurance
This document discusses the importance of quality assurance in gait analysis. It emphasizes that measurements must be accurate if meaningful interpretations are to be made. Staff training, vigilance for errors, repeatability studies, and ensuring data consistency are key aspects of quality assurance. Formal training in both the science and art of gait analysis is needed. Differences between labs may suggest systematic differences in measurement practices, highlighting the need for standardization. Quality assurance also requires an open culture and consideration of multiple data sources to validate findings and catch errors.
RESHMA.pptx
The document presents a study on the effectiveness of home-based exercise intervention on osteoarthritis among old age people. The objectives are to assess and compare joint pain levels before and after the intervention in experimental and control groups, and to examine the association between pain levels and demographic variables. The study will involve 60 subjects, 30 in the experimental group receiving home exercises and 30 controls. Outcomes will be measured using a pain scale. Results will be analyzed using t-tests, frequencies, percentages, and chi-square to evaluate the effectiveness of the home exercises in reducing joint pain for older adults with osteoarthritis.
Changes During Passive Recovery In Lower Limbs Tiredness After Strenuous Workout
Abstract: Lower limbs tiredness is a widely accepted indicator for recovery state prediction. The study was
designed and purposed to know the rate and trend of lower limbs tiredness recovery after strenuous workout in
passive state. Ten athletes from LNIPE, Gwalior having almost similar anthropometric measurements,
physiological capacity, chronological age(18-19 year), training age(5-6 year), event(sprinters) etc. residing in
same campus having similar daily routine were selected as participant in this experiment. The experiment was
conducted in a highly controlled environment using sophisticate equipments. Target Heart Rate Zone of the
workout lasting for 20 minutes was 80%-90% of their Maximum Heart Rate. Three readings including pre, post
and 30 minutes post workout was considered for both the two tests (Isometric Leg Strength Test and Sergeant
Jump Test) selected for the purpose. rANOVA was employed separately to derive out meaningful information
from the raw data. In both the tests well controlled workout for 20 minutes resulted in significant increase state
of post workout readings. With passage of time after 30 minutes post passive recovery there was no
improvement in state of tiredness. Thus scope of future research is there in planning out means and methods to
promote lower limbs tiredness recovery during this post recovery period.
Keyword: Isometric Leg Strength Test, Sergeant Jump Test, Recovery, rANOVA
How Does Exercise Affect Muscle And Fatty Tissue (Compat)
This experiment aims to examine the effects of exercise on fat tissue (adipose tissue) and muscle tissue (lean tissue) distribution in the body. It will randomly assign 30 subjects to a control group or exercise intervention group. Both groups' tissue volumes will be measured before and after a three-week period using MRI. Statistical analysis will compare the tissue volumes within and between groups to determine if exercise significantly changes fat and muscle tissue amounts.
Chapter 5 anova analysis
1) The document discusses how to perform a one-way ANOVA analysis in SPSS to determine if the means of three populations are statistically different.
2) It provides an example comparing the weights of maize plants that received different fertilizer treatments (biological, chemical, none).
3) The one-way ANOVA analysis found that the mean weights were statistically different between the three fertilizer groups, with the chemical fertilizer producing the highest average weight.
Stat170 - Introductory Statistics Semester 2, 2015 Assignmen.docx
Stat170 - Introductory Statistics
Semester 2, 2015 Assignment 2
Instructions:
1. Type your answers directly into this document.
2. The answers to all questions are to be word processed. You can either type formulae into your solution or you can use the equation editor in Word or you may include hand-written equations and diagrams by photographing them so that you have the image saved as a picture file and then pasting (inserting) the image/s into your solution.
3. Your assignment should be uploaded as a Word (.doc or .docx) or PDF file (created from a Word processed document) ONLY. Other formats, including a PDF created from an image, will not be accepted by the system.
Information:
Q1
Q2
Q3
Q4
Total
10
13
10
17
50
1) Question 1 (10 marks)
Include an appropriate diagram for each part of this question. You can sketch these diagrams and paste in a photo of your sketch, along with your solutions.
a. BranCrunch is a new breakfast cereal. Boxes of BranCrunch are labelled ‘ 675 grams’ but there is some variation. The actual mean weight is 675 grams with a standard deviation of 21 grams.
i. Dan’s Discount Store sells BranCrunch in mega-packs of 8 boxes. Assuming the weights of boxes of BranCrunch are normally distributed, find the probability that the average weight of a mega-pack of BranCrunch is higher than 665 grams.
ii. Louie’s Convenience Store receives a shipment of 30 boxes of BranCrunch. Louie’s will complain to the manufacturers if the total weight of this shipment is lower than 20 kg. Find the probability that Louie’s Convenience Store will complain about the shipment and explain why the information about the weights of BranCrunch following a normal distribution is not necessary to answer this part of the question.
b. In 2014 the Department of Social Services reported that 32% of current marriages in Australia were expected to end in divorce.
Find the probability that more than 8 marriages out of a random sample of 20 marriages which were current in 2014 would end in divorce.
Question 2 (13 marks)
Lean body mass is the amount of weight carried on the body that is not fat. Metabolic rate is the rate at which the body consumes energy. The following Minitab output was constructed using data recorded in a fitness study which was designed to compare the lean body masses and also the metabolic rates of adolescent males and adolescent females. Use this output to answer the questions which follow.
Two-sample T for LeanBodyMass
Sex N Mean StDev SE Mean
Male 75 52.63 6.66 0.77
Female 75 43.42 6.05 0.70
Difference = μ (Male) - μ (Female)
Estimate for difference: 9.21
95% CI for difference: (****, ****)
T-Test of difference = 0 (vs ≠): T-Value = **** P-Value = **** DF = ****
Both use Pooled StDev = 6.3633
Two-sample T for MetRate
SE
Sex N Mean StDev Mean
Male 75 1626 227 26
Female 75 1258 172.
1. The following are body mass index (BMI) scores measured in 12.docx
1. The following are body mass index (BMI) scores measured in 12 patients who are free of diabetes and participating in a study of risk factors for obesity. Body mass index is measured as the ratio of weight in kilograms to height in meters squared. Generate a 95% confidence interval estimate of the true BMI.
25
27
31
33
26
28
38
41
24
32
35
40
2. Consider the data in Problem 1. How many subjects would be needed to ensure that a 95% confidence interval estimate of BMI had a margin of error not exceeding 2 units?
3. The mean BMI in patients free of diabetes was reported as 28.2. The investigator conducting the study described in Problem 1 hypothesizes that the BMI in patients free of diabetes is higher. Based on the data in Problem 1 is there evidence that the BMI is significantly higher that 28.2? Use a 5% level of significance.
4. Peak expiratory flow (PEF) is a measure of a patient’s ability to expel air from the lungs. Patients with asthma or other respiratory conditions often have restricted PEF. The mean PEF for children free of asthma is 306. An investigator wants to test whether children with chronic bronchitis have restricted PEF. A sample of 40 children with chronic bronchitis are studied and their mean PEF is 279 with a standard deviation of 71. Is there statistical evidence of a lower mean PEF in children with chronic bronchitis? Run the appropriate test at =0.05.
5. Consider again the study in Problem 4, a different investigator conducts a second study to investigate whether there is a difference in mean PEF in children with chronic bronchitis as compared to those without. Data on PEF are collected and summarized below. Based on the data, is there statistical evidence of a lower mean PEF in children with chronic bronchitis as compared to those without? Run the appropriate test at =0.05.
Group
Number of Children
Mean PEF
Std Dev PEF
Chronic Bronchitis
25
281
68
No Chronic Bronchitis
25
319
74
6. Using the data presented in Problem 5,
a) Construct a 95% confidence interval for the mean PEF in children without chronic bronchitis.
b) How many children would be required to ensure that the margin of error in (a) does not exceed 10 units?
7. A clinical trial is run to investigate the effectiveness of an experimental drug in reducing preterm delivery to a drug considered standard care and to placebo. Pregnant women are enrolled and randomly assigned to receive either the experimental drug, the standard drug or placebo. Women are followed through delivery and classified as delivering preterm (< 37 weeks) or not. The data are shown below.
Preterm Delivery
Experimental Drug
Standard Drug
Placebo
Yes
17
23
35
No
83
77
65
Is there a statistically significant difference in the proportions of women delivering preterm among the three treatment groups? Run the test at a 5% level of significance.
8. Using the data in Problem 7, generate a 95% confidence interval for the difference in proportions of women ...
1T1 Conduct one-way ANOVA analysis on the height using the .docx
1
T1: Conduct one-way ANOVA analysis on the height using the "Weight and Height.xlsx" sample data under the Data Sets (See Attachment) folder (Note that you will need to change the format of the data set to conduct the analysis). Based on your results, what conclusion would you draw regarding the average height of students in the three states?
Solution
:
Null Hypothesis: All the states have the same mean height of the students.
Alternate Hypothesis: Not all the states have the same mean height of the students.
The One-Way Analysis of Variance was performed in SPSS. The SPSS output is given as follows:
Descriptives
Height
N
Mean
Std. Deviation
Std. Error
95% Confidence Interval for Mean
Minimum
Maximum
Lower Bound
Upper Bound
KS
28
67.5714
3.30184
.62399
66.2911
68.8517
62.00
75.00
MO
41
69.9756
3.24220
.50635
68.9522
70.9990
61.00
75.00
NE
23
67.8696
4.18593
.87283
66.0594
69.6797
61.75
74.00
Total
92
68.7174
3.65929
.38151
67.9596
69.4752
61.00
75.00
Test of Homogeneity of Variances
Height
Levene Statistic
df1
df2
Sig.
1.697
2
89
.189
Levene Statistic (2, 89) = 1.697, p-value = 0.189Comment by Bo Yan: I don’t have SPSS installed on my computer. But the your results are slightly different from the numbers I got from using Excel and another statistical package.
The p-value is significant at α=0.05. From this test we conclude that we do not have the homogeneity of variance. Comment by Bo Yan: Does the evidence support your conclusion here when p > 0.05?
ANOVA
Height
Sum of Squares
df
Mean Square
F
Sig.
Between Groups
118.211
2
59.105
4.781
.011
Within Groups
1100.316
89
12.363
Total
1218.527
91
F (2, 89) = 4.781, p-value = 0.011
The p-value is significant at α=0.05. We reject the null hypothesis. From our analysis there is sufficient evidence to conclude that not all the states have the same mean height of the students, at a significance level of 0.05. This can be further emphasized from the results of the post-hoc tests. The following table shows the results of the Turkey’s HSD post hoc tests:Comment by Bo Yan: Good.
Multiple Comparisons
Dependent Variable: Height
Tukey HSD
(I) State
(J) State
Mean Difference (I-J)
Std. Error
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
KS
MO
-2.40418*
.86202
.018
-4.4588
-.3495
NE
-.29814
.98948
.951
-2.6566
2.0603
MO
KS
2.40418*
.86202
.018
.3495
4.4588
NE
2.10604
.91601
.061
-.0773
4.2894
NE
KS
.29814
.98948
.951
-2.0603
2.6566
MO
-2.10604
.91601
.061
-4.2894
.0773
*. The mean difference is significant at the 0.05 level.
KS & MO:
The 95% confidence interval for the difference of means is given as (-4.4588, -.3495).
As the confidence interval does not contain 0, we can conclude that there is statistically significant difference between the mean height of students belonging to the states KS and MO.Comment by Bo Yan: Now you should understand the difference between statistically significant and practically significant difference. So I expect you to be mor.
Objective Assessment of Postural Control.pptx
presentation on in depth assessment of posture and balance
The Effects Of Creatine On Repeated Sprint Performance, Maximum Strength And ...
1. The document reports on a study that examined the effects of creatine versus a placebo on repeated sprint performance, maximum strength, and power in 15 participants.
2. The results showed no significant differences between the creatine and placebo groups in pre-sprint or post-sprint times, rates of perceived exertion, concentric and eccentric peak torque, or jump heights.
3. While both groups improved slightly from pre to post testing, the creatine group demonstrated slightly greater improvements than the placebo group in some measures like decreased sprint times, increased concentric peak torque, and increased jump heights. However, all differences were small with no statistical significance.
Exercise 1 12 no solution
This document contains a series of exercises related to biostatistics and research methods. It includes exercises on categorizing variables, designing a questionnaire, different sampling methods like simple random sampling, systematic random sampling, stratified sampling and cluster sampling. It also includes exercises on ordering and presenting data in frequency distribution tables, calculating measures of central tendency and dispersion, the normal distribution and confidence intervals. The final exercises are on the chi-square test and t-test, including examples of applying these statistical tests to compare groups.
Training load and injuries in football- lessons from research and practise
This document summarizes research on training load management in football. It discusses how monitoring training load and analyzing the data can inform decision making to find the optimal load for each player. While acute:chronic workload ratios are often used, the evidence for their ability to prevent injuries is limited due to poor study quality and lack of randomized controlled trials. Training load must be considered together with other individual factors, and load management aims to balance training and recovery rather than precisely predict or prevent health problems.
Biodex
The document provides release notes for version 1.32 of the Biodex Balance SD software. Key updates include: [END SUMMARY]
OUTCOME MEASURES IN SPORTS.pptx
The ppt consists of some basic and most useful outcome measures which are utilised to measure the different variables associated with the performance of an athlete or a player. It helps to evaluate, form diagnosis and to develop a management cum rehabilitation program for an athlete in sports.
WEEK 6 – EXERCISES Enter your answers in the spaces pr.docx
WEEK 6 – EXERCISES
Enter your answers in the spaces provided. Save the file using your last name as the beginning of the file name (e.g., ruf_week6_exercises) and submit via “Assignments.” When appropriate,
show your work
. You can do the work by hand, scan/take a digital picture, and attach that file with your work.
1
.
A psychotherapist studied whether his clients self-disclosed more while sitting in an easy chair or lying down on a couch. All clients had previously agreed to allow the sessions to be videotaped for research purposes. The therapist randomly assigned 10 clients to each condition. The third session for each client was videotaped and an independent observer counted the clients’ disclosures. The therapist reported that “clients made more disclosures when sitting in easy chairs (
M
= 18.20) than when lying down on a couch (
M
= 14.31),
t
(18) = 2.84,
p
< .05, two-tailed.” Explain these results to a person who understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
2.
A researcher compared the adjustment of adolescents who had been raised in homes that were either very structured or unstructured. Thirty adolescents from each type of family completed an adjustment inventory. The results are reported in the table below. Explain these results to a person who understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
Means on Four Adjustment Scales for
Adolescents from Structured versus Unstructured Homes
Scale
Structured Homes
Unstructured Homes
t
Social Maturity
106.82
113.94
–1.07
School Adjustment
116.31
107.22
2.03*
Identity Development
89.48
94.32
1.93*
Intimacy Development
102.25
104.33
.32
______________________
*
p
< .05
3.
Do men with higher levels of a particular hormone show higher levels of assertiveness? Levels of this hormone were tested in 100 men. The top 10 and the bottom 10 were selected for the study. All participants took part in a laboratory simulation in which they were asked to role-play a person picking his car up from a mechanic’s shop. The simulation was videotaped and later judged by independent raters on each of four types of assertive statements made by the participant. The results are shown in the table below. Explain these results to a person who fully understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
Mean Number of Assertive Statements
Type of Assertive Statement
Group
1
2
3
4
Men with High Levels
2.14
1.16
3.83
0.14
Men with Low Levels
1.21
1.32
2.33
0.38
t
3.81**
0.89
2.03*
0.58
______________________
*
p
< .05;
**
p
< 0.1
4.
A manager of a small store wanted to discourage shoplifters by putting signs around the store saying “Shoplifting is a crime!” However, he wanted to make sure this would not result in customers buying less. To test this, he displayed the signs every other W.
Running head Research report11Research report13Business Resea.docx
Running head: Research report 11
Research report 13Business Research Project Part 5:Research Report
Alexis Madera, Christopher Lauko, Cristina Linares,
Marina Garcia, & Sarah Maokosy
QNT/561
August 4, 2014
Jonathan Edelman
Research Report
Due to the new fitness and health awareness fad, gym memberships are growing rapidly. In order to better understand the demographics and cater to the needs of gym members, research is required. Fitness Gymnasium is a large fitness gym in Lincoln, Nebraska. Members of Learning Team A are a part of the management team. The management team has been tasked to provide health and wellness checkups for 40 random female gym members.
The purpose of this research is to obtain an overall understanding of the female demographics of the gym. The results of this research will provide Fitness Gymnasium with enough information to create fitness programs based on the needs of its female members. Blood pressure is an important variable to consider before allowing customers to obtain gym memberships. Varying results have been observed amongst the Blood Pressure and Body Mass Index (BMI) of female gym members.
Hypothesis
H0: There is no correlation between an applicant's BP and their BMI.
Ha: There is a correlation between an applicant's BP and their BMI.
Study
The purpose of this study is to find a correlation between Body Mass Index (BMI) and Blood Pressure (BP). Studies have shown those who have an above average BMI are more likely to have long term health problems such as high BP or hypertension. BMI is the calculation of a person's weight and height, and provides a reliable indicator of body fat in a person (Centers for Disease Control, 2013).BP is the measurement of the force of blood running through veins and arteries, which is measured in two numbers as a ratio: Systolic and Diastolic (S/D) (American Heart Association, 2014). According to a past research study, those who increased their BMI also increased their BP, which put them at risk of hypertension (Droyvold, Midthjell, Nilsen, & Holmen, 2005). From this, Fitness Gymnasium will create a program with the needs and the well-being of its female members in mind.
Population and Size
The current population and size is the amount of gym members. Fitness Gymnasium’s population is the amount of all male and female gym members, which is 100 members. With that being said, the population for Fitness Gymnasium is all male and female gym members, and the size is 100 members.
Target Population and Sample Size
The current target population for the gym is female gym members. At Fitness Gymnasium, the current percentage of female members is 50% of 100 total gym members, which makes the target population 50 females. For Fitness Gymnasium, the sample size is 40 using a 95% confidence level, 5% margin of error with a target population of 40 females (Appendix A).
Assessment/Survey
Fitness Gymnasium created the following survey to observe the correlation between a member’s BMI a.
3. parametric assumptions
This document discusses the parametric assumptions that must be met before conducting inferential statistics on data. It outlines the four main assumptions: 1) random sampling, 2) high level interval or ratio data, 3) normal distribution as assessed by skewness and kurtosis z-scores, and 4) equal or homogenous variance between groups. Meeting these assumptions ensures the appropriate statistical tests are used to avoid type I and II errors when making inferences about a population based on a sample. Non-parametric tests should be used if the assumptions are not met.
ELEMENTS OF STATISTICS / TUTORIALOUTLET DOT COM
Unit 3 Problem Set NAME: Elements of Statistics--FHSU Virtual College--Spring 2017
REMEMBER, these are assessed preparatory problems related to the content of Unit 3. The Unit 3 Exam will consist of similar types of
PRELAB 7 exercise phys.docx
The document discusses two high-intensity fitness tests: the Multistage Fitness (Beep) Test and the Yo-Yo Intermittent Recovery Test. It provides background on the tests and how they are conducted. While the Multistage Fitness Test is reliable, recent research shows it is not a valid predictor of VO2 max as was previously believed. The Yo-Yo Intermittent Recovery Test, specifically Level 1, has been proven to be both a valid and reliable measure of high-intensity aerobic capacity and a moderately reliable predictor of VO2 max. Both tests have limitations, such as difficulties regulating large groups for the Multistage Fitness Test.
Running head Final Project Data Analysis1Final Project Data A.docx
Running head: Final Project Data Analysis 1
Final Project Data Analysis 2
Final Project Data Analysis:
Luz Rodriguez
Southern New Hampshire University
Process and calculations
In completing the research on the influence that gender (male/female) has over the length of the hospital stay. We can use several types of statistical tests in analysis a more accurate analysis of the research question. This involves a dot plot and a histogram. In responding to this question, we can place gender in one category but studying it under two separate samples, male and female and the effects of length of stay after a myocardial infarction. We can compute this by resolving quantitative data and the relationship between the two factors s dot plot and a histogram would be effective in achieving this analysis.
Research question
To what extent does gender influence length of hospital stay for MI patients?
Response and predictor variables
Response: Length of hospital stay (LOS)
-Predictor: Gender (female and male)
Type of variable for predictor variable
Predictor: gender (female or male)
Type of diagram for analysis
Dot plot
Histogram
Data analysis
As shown the data tries to compare the differences between gender (male and Female) and the length of stay in hospitals with respect to each other. It’s clear that the length of hospital stay which is represented by 0 is shorter as compared to that of the female which is represented by 1. If there is a larger differences between the two genders, then there is a meaning which would reduce the standard deviation (Gerstman, 2015).
gender
n
mean
variance
Std. dev
Std. err.
median
range
min
max
Q1
Q3
0
65
0
0
0
0
0
0
0
0
0
0
1
35
1
0
0
0
1
0
1
1
1
1
Hypothesis test results:
Difference
Sample Diff.
Std. Err.
DF
T-Stat
P-value
μ1 - μ2
6.49
0.59375453
198
10.930443
<0.0001
References
Gerstman, B. B. (2015). Basic Biostatistics Statistics for Public Health (2nd ed.). Burlington, MA: Jones & Bartlett Learning.
gender 1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 2.0 17.0 34.0 3.0 6.0 1.0 3.0 gender 1 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 2.0 17.0 34.0 3.0 6.0 1.0 3.0
Course ProjectCriteriaPointsDescribes the patient that is the subject of the project including diagnoses, medications, and history OR describes the community, its strengths and problems and the mental health issue that will be the subject of the paper.4Includes any substance abuse or violence issues for the patient or community 2Discusses attempted interventions, what has been successful and what has not.4Describes own personal thoughts about the patient's or community's mental health issues. 4Describes any cognitive concerns and possible interventions.2Writes a nursing care plan including three priority nursing diagnoses with r/t and AEB factors.4Includes outcomes in Nursing Outcomes Classification language and interventions in Nursing Intervention Classificati ...
Running head Final Project Data Analysis1Final Project Data A.docx
Running head: Final Project Data Analysis 1
Final Project Data Analysis 2
Final Project Data Analysis:
Luz Rodriguez
Southern New Hampshire University
Process and calculations
In completing the research on the influence that gender (male/female) has over the length of the hospital stay. We can use several types of statistical tests in analysis a more accurate analysis of the research question. This involves a dot plot and a histogram. In responding to this question, we can place gender in one category but studying it under two separate samples, male and female and the effects of length of stay after a myocardial infarction. We can compute this by resolving quantitative data and the relationship between the two factors s dot plot and a histogram would be effective in achieving this analysis.
Research question
To what extent does gender influence length of hospital stay for MI patients?
Response and predictor variables
Response: Length of hospital stay (LOS)
-Predictor: Gender (female and male)
Type of variable for predictor variable
Predictor: gender (female or male)
Type of diagram for analysis
Dot plot
Histogram
Data analysis
As shown the data tries to compare the differences between gender (male and Female) and the length of stay in hospitals with respect to each other. It’s clear that the length of hospital stay which is represented by 0 is shorter as compared to that of the female which is represented by 1. If there is a larger differences between the two genders, then there is a meaning which would reduce the standard deviation (Gerstman, 2015).
gender
n
mean
variance
Std. dev
Std. err.
median
range
min
max
Q1
Q3
0
65
0
0
0
0
0
0
0
0
0
0
1
35
1
0
0
0
1
0
1
1
1
1
Hypothesis test results:
Difference
Sample Diff.
Std. Err.
DF
T-Stat
P-value
μ1 - μ2
6.49
0.59375453
198
10.930443
<0.0001
References
Gerstman, B. B. (2015). Basic Biostatistics Statistics for Public Health (2nd ed.). Burlington, MA: Jones & Bartlett Learning.
gender 1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 2.0 17.0 34.0 3.0 6.0 1.0 3.0 gender 1 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 2.0 17.0 34.0 3.0 6.0 1.0 3.0
Course ProjectCriteriaPointsDescribes the patient that is the subject of the project including diagnoses, medications, and history OR describes the community, its strengths and problems and the mental health issue that will be the subject of the paper.4Includes any substance abuse or violence issues for the patient or community 2Discusses attempted interventions, what has been successful and what has not.4Describes own personal thoughts about the patient's or community's mental health issues. 4Describes any cognitive concerns and possible interventions.2Writes a nursing care plan including three priority nursing diagnoses with r/t and AEB factors.4Includes outcomes in Nursing Outcomes Classification language and interventions in Nursing Intervention Classificati.
2. Session 11 contains the Final Prezi Presentation. There are diff.docx
2. Session 11 contains the Final Prezi Presentation. There are different directions for the submission of this assignment than what we have done thus far, so make sure to CAREFULLY read and follow the directions. Please keep in mind that submitting your assignment correctly is part of your grade.
.
2. In generaI, how do the gods and goddesses described in the myth.docx
2. In generaI, how do the gods and goddesses described in the myths resemble human men and women? How do they differ? Are the similarities and differences important to their divine status? Explain why or why not.
1.Do myths of divinities influence how cultures think of the ideal for women and men? If so, explain in what way. If not, explain why. Do you consider these portrayals positive or negative?
.
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RESHMA.pptx
The document presents a study on the effectiveness of home-based exercise intervention on osteoarthritis among old age people. The objectives are to assess and compare joint pain levels before and after the intervention in experimental and control groups, and to examine the association between pain levels and demographic variables. The study will involve 60 subjects, 30 in the experimental group receiving home exercises and 30 controls. Outcomes will be measured using a pain scale. Results will be analyzed using t-tests, frequencies, percentages, and chi-square to evaluate the effectiveness of the home exercises in reducing joint pain for older adults with osteoarthritis.
Changes During Passive Recovery In Lower Limbs Tiredness After Strenuous Workout
Abstract: Lower limbs tiredness is a widely accepted indicator for recovery state prediction. The study was
designed and purposed to know the rate and trend of lower limbs tiredness recovery after strenuous workout in
passive state. Ten athletes from LNIPE, Gwalior having almost similar anthropometric measurements,
physiological capacity, chronological age(18-19 year), training age(5-6 year), event(sprinters) etc. residing in
same campus having similar daily routine were selected as participant in this experiment. The experiment was
conducted in a highly controlled environment using sophisticate equipments. Target Heart Rate Zone of the
workout lasting for 20 minutes was 80%-90% of their Maximum Heart Rate. Three readings including pre, post
and 30 minutes post workout was considered for both the two tests (Isometric Leg Strength Test and Sergeant
Jump Test) selected for the purpose. rANOVA was employed separately to derive out meaningful information
from the raw data. In both the tests well controlled workout for 20 minutes resulted in significant increase state
of post workout readings. With passage of time after 30 minutes post passive recovery there was no
improvement in state of tiredness. Thus scope of future research is there in planning out means and methods to
promote lower limbs tiredness recovery during this post recovery period.
Keyword: Isometric Leg Strength Test, Sergeant Jump Test, Recovery, rANOVA
How Does Exercise Affect Muscle And Fatty Tissue (Compat)
This experiment aims to examine the effects of exercise on fat tissue (adipose tissue) and muscle tissue (lean tissue) distribution in the body. It will randomly assign 30 subjects to a control group or exercise intervention group. Both groups' tissue volumes will be measured before and after a three-week period using MRI. Statistical analysis will compare the tissue volumes within and between groups to determine if exercise significantly changes fat and muscle tissue amounts.
Chapter 5 anova analysis
1) The document discusses how to perform a one-way ANOVA analysis in SPSS to determine if the means of three populations are statistically different.
2) It provides an example comparing the weights of maize plants that received different fertilizer treatments (biological, chemical, none).
3) The one-way ANOVA analysis found that the mean weights were statistically different between the three fertilizer groups, with the chemical fertilizer producing the highest average weight.
Stat170 - Introductory Statistics Semester 2, 2015 Assignmen.docx
Stat170 - Introductory Statistics
Semester 2, 2015 Assignment 2
Instructions:
1. Type your answers directly into this document.
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3. Your assignment should be uploaded as a Word (.doc or .docx) or PDF file (created from a Word processed document) ONLY. Other formats, including a PDF created from an image, will not be accepted by the system.
Information:
Q1
Q2
Q3
Q4
Total
10
13
10
17
50
1) Question 1 (10 marks)
Include an appropriate diagram for each part of this question. You can sketch these diagrams and paste in a photo of your sketch, along with your solutions.
a. BranCrunch is a new breakfast cereal. Boxes of BranCrunch are labelled ‘ 675 grams’ but there is some variation. The actual mean weight is 675 grams with a standard deviation of 21 grams.
i. Dan’s Discount Store sells BranCrunch in mega-packs of 8 boxes. Assuming the weights of boxes of BranCrunch are normally distributed, find the probability that the average weight of a mega-pack of BranCrunch is higher than 665 grams.
ii. Louie’s Convenience Store receives a shipment of 30 boxes of BranCrunch. Louie’s will complain to the manufacturers if the total weight of this shipment is lower than 20 kg. Find the probability that Louie’s Convenience Store will complain about the shipment and explain why the information about the weights of BranCrunch following a normal distribution is not necessary to answer this part of the question.
b. In 2014 the Department of Social Services reported that 32% of current marriages in Australia were expected to end in divorce.
Find the probability that more than 8 marriages out of a random sample of 20 marriages which were current in 2014 would end in divorce.
Question 2 (13 marks)
Lean body mass is the amount of weight carried on the body that is not fat. Metabolic rate is the rate at which the body consumes energy. The following Minitab output was constructed using data recorded in a fitness study which was designed to compare the lean body masses and also the metabolic rates of adolescent males and adolescent females. Use this output to answer the questions which follow.
Two-sample T for LeanBodyMass
Sex N Mean StDev SE Mean
Male 75 52.63 6.66 0.77
Female 75 43.42 6.05 0.70
Difference = μ (Male) - μ (Female)
Estimate for difference: 9.21
95% CI for difference: (****, ****)
T-Test of difference = 0 (vs ≠): T-Value = **** P-Value = **** DF = ****
Both use Pooled StDev = 6.3633
Two-sample T for MetRate
SE
Sex N Mean StDev Mean
Male 75 1626 227 26
Female 75 1258 172.
1. The following are body mass index (BMI) scores measured in 12.docx
1. The following are body mass index (BMI) scores measured in 12 patients who are free of diabetes and participating in a study of risk factors for obesity. Body mass index is measured as the ratio of weight in kilograms to height in meters squared. Generate a 95% confidence interval estimate of the true BMI.
25
27
31
33
26
28
38
41
24
32
35
40
2. Consider the data in Problem 1. How many subjects would be needed to ensure that a 95% confidence interval estimate of BMI had a margin of error not exceeding 2 units?
3. The mean BMI in patients free of diabetes was reported as 28.2. The investigator conducting the study described in Problem 1 hypothesizes that the BMI in patients free of diabetes is higher. Based on the data in Problem 1 is there evidence that the BMI is significantly higher that 28.2? Use a 5% level of significance.
4. Peak expiratory flow (PEF) is a measure of a patient’s ability to expel air from the lungs. Patients with asthma or other respiratory conditions often have restricted PEF. The mean PEF for children free of asthma is 306. An investigator wants to test whether children with chronic bronchitis have restricted PEF. A sample of 40 children with chronic bronchitis are studied and their mean PEF is 279 with a standard deviation of 71. Is there statistical evidence of a lower mean PEF in children with chronic bronchitis? Run the appropriate test at =0.05.
5. Consider again the study in Problem 4, a different investigator conducts a second study to investigate whether there is a difference in mean PEF in children with chronic bronchitis as compared to those without. Data on PEF are collected and summarized below. Based on the data, is there statistical evidence of a lower mean PEF in children with chronic bronchitis as compared to those without? Run the appropriate test at =0.05.
Group
Number of Children
Mean PEF
Std Dev PEF
Chronic Bronchitis
25
281
68
No Chronic Bronchitis
25
319
74
6. Using the data presented in Problem 5,
a) Construct a 95% confidence interval for the mean PEF in children without chronic bronchitis.
b) How many children would be required to ensure that the margin of error in (a) does not exceed 10 units?
7. A clinical trial is run to investigate the effectiveness of an experimental drug in reducing preterm delivery to a drug considered standard care and to placebo. Pregnant women are enrolled and randomly assigned to receive either the experimental drug, the standard drug or placebo. Women are followed through delivery and classified as delivering preterm (< 37 weeks) or not. The data are shown below.
Preterm Delivery
Experimental Drug
Standard Drug
Placebo
Yes
17
23
35
No
83
77
65
Is there a statistically significant difference in the proportions of women delivering preterm among the three treatment groups? Run the test at a 5% level of significance.
8. Using the data in Problem 7, generate a 95% confidence interval for the difference in proportions of women ...
1T1 Conduct one-way ANOVA analysis on the height using the .docx
1
T1: Conduct one-way ANOVA analysis on the height using the "Weight and Height.xlsx" sample data under the Data Sets (See Attachment) folder (Note that you will need to change the format of the data set to conduct the analysis). Based on your results, what conclusion would you draw regarding the average height of students in the three states?
Solution
:
Null Hypothesis: All the states have the same mean height of the students.
Alternate Hypothesis: Not all the states have the same mean height of the students.
The One-Way Analysis of Variance was performed in SPSS. The SPSS output is given as follows:
Descriptives
Height
N
Mean
Std. Deviation
Std. Error
95% Confidence Interval for Mean
Minimum
Maximum
Lower Bound
Upper Bound
KS
28
67.5714
3.30184
.62399
66.2911
68.8517
62.00
75.00
MO
41
69.9756
3.24220
.50635
68.9522
70.9990
61.00
75.00
NE
23
67.8696
4.18593
.87283
66.0594
69.6797
61.75
74.00
Total
92
68.7174
3.65929
.38151
67.9596
69.4752
61.00
75.00
Test of Homogeneity of Variances
Height
Levene Statistic
df1
df2
Sig.
1.697
2
89
.189
Levene Statistic (2, 89) = 1.697, p-value = 0.189Comment by Bo Yan: I don’t have SPSS installed on my computer. But the your results are slightly different from the numbers I got from using Excel and another statistical package.
The p-value is significant at α=0.05. From this test we conclude that we do not have the homogeneity of variance. Comment by Bo Yan: Does the evidence support your conclusion here when p > 0.05?
ANOVA
Height
Sum of Squares
df
Mean Square
F
Sig.
Between Groups
118.211
2
59.105
4.781
.011
Within Groups
1100.316
89
12.363
Total
1218.527
91
F (2, 89) = 4.781, p-value = 0.011
The p-value is significant at α=0.05. We reject the null hypothesis. From our analysis there is sufficient evidence to conclude that not all the states have the same mean height of the students, at a significance level of 0.05. This can be further emphasized from the results of the post-hoc tests. The following table shows the results of the Turkey’s HSD post hoc tests:Comment by Bo Yan: Good.
Multiple Comparisons
Dependent Variable: Height
Tukey HSD
(I) State
(J) State
Mean Difference (I-J)
Std. Error
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
KS
MO
-2.40418*
.86202
.018
-4.4588
-.3495
NE
-.29814
.98948
.951
-2.6566
2.0603
MO
KS
2.40418*
.86202
.018
.3495
4.4588
NE
2.10604
.91601
.061
-.0773
4.2894
NE
KS
.29814
.98948
.951
-2.0603
2.6566
MO
-2.10604
.91601
.061
-4.2894
.0773
*. The mean difference is significant at the 0.05 level.
KS & MO:
The 95% confidence interval for the difference of means is given as (-4.4588, -.3495).
As the confidence interval does not contain 0, we can conclude that there is statistically significant difference between the mean height of students belonging to the states KS and MO.Comment by Bo Yan: Now you should understand the difference between statistically significant and practically significant difference. So I expect you to be mor.
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2. The results showed no significant differences between the creatine and placebo groups in pre-sprint or post-sprint times, rates of perceived exertion, concentric and eccentric peak torque, or jump heights.
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This document contains a series of exercises related to biostatistics and research methods. It includes exercises on categorizing variables, designing a questionnaire, different sampling methods like simple random sampling, systematic random sampling, stratified sampling and cluster sampling. It also includes exercises on ordering and presenting data in frequency distribution tables, calculating measures of central tendency and dispersion, the normal distribution and confidence intervals. The final exercises are on the chi-square test and t-test, including examples of applying these statistical tests to compare groups.
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WEEK 6 – EXERCISES Enter your answers in the spaces pr.docx
WEEK 6 – EXERCISES
Enter your answers in the spaces provided. Save the file using your last name as the beginning of the file name (e.g., ruf_week6_exercises) and submit via “Assignments.” When appropriate,
show your work
. You can do the work by hand, scan/take a digital picture, and attach that file with your work.
1
.
A psychotherapist studied whether his clients self-disclosed more while sitting in an easy chair or lying down on a couch. All clients had previously agreed to allow the sessions to be videotaped for research purposes. The therapist randomly assigned 10 clients to each condition. The third session for each client was videotaped and an independent observer counted the clients’ disclosures. The therapist reported that “clients made more disclosures when sitting in easy chairs (
M
= 18.20) than when lying down on a couch (
M
= 14.31),
t
(18) = 2.84,
p
< .05, two-tailed.” Explain these results to a person who understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
2.
A researcher compared the adjustment of adolescents who had been raised in homes that were either very structured or unstructured. Thirty adolescents from each type of family completed an adjustment inventory. The results are reported in the table below. Explain these results to a person who understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
Means on Four Adjustment Scales for
Adolescents from Structured versus Unstructured Homes
Scale
Structured Homes
Unstructured Homes
t
Social Maturity
106.82
113.94
–1.07
School Adjustment
116.31
107.22
2.03*
Identity Development
89.48
94.32
1.93*
Intimacy Development
102.25
104.33
.32
______________________
*
p
< .05
3.
Do men with higher levels of a particular hormone show higher levels of assertiveness? Levels of this hormone were tested in 100 men. The top 10 and the bottom 10 were selected for the study. All participants took part in a laboratory simulation in which they were asked to role-play a person picking his car up from a mechanic’s shop. The simulation was videotaped and later judged by independent raters on each of four types of assertive statements made by the participant. The results are shown in the table below. Explain these results to a person who fully understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
Mean Number of Assertive Statements
Type of Assertive Statement
Group
1
2
3
4
Men with High Levels
2.14
1.16
3.83
0.14
Men with Low Levels
1.21
1.32
2.33
0.38
t
3.81**
0.89
2.03*
0.58
______________________
*
p
< .05;
**
p
< 0.1
4.
A manager of a small store wanted to discourage shoplifters by putting signs around the store saying “Shoplifting is a crime!” However, he wanted to make sure this would not result in customers buying less. To test this, he displayed the signs every other W.
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Running head: Research report 11
Research report 13Business Research Project Part 5:Research Report
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Jonathan Edelman
Research Report
Due to the new fitness and health awareness fad, gym memberships are growing rapidly. In order to better understand the demographics and cater to the needs of gym members, research is required. Fitness Gymnasium is a large fitness gym in Lincoln, Nebraska. Members of Learning Team A are a part of the management team. The management team has been tasked to provide health and wellness checkups for 40 random female gym members.
The purpose of this research is to obtain an overall understanding of the female demographics of the gym. The results of this research will provide Fitness Gymnasium with enough information to create fitness programs based on the needs of its female members. Blood pressure is an important variable to consider before allowing customers to obtain gym memberships. Varying results have been observed amongst the Blood Pressure and Body Mass Index (BMI) of female gym members.
Hypothesis
H0: There is no correlation between an applicant's BP and their BMI.
Ha: There is a correlation between an applicant's BP and their BMI.
Study
The purpose of this study is to find a correlation between Body Mass Index (BMI) and Blood Pressure (BP). Studies have shown those who have an above average BMI are more likely to have long term health problems such as high BP or hypertension. BMI is the calculation of a person's weight and height, and provides a reliable indicator of body fat in a person (Centers for Disease Control, 2013).BP is the measurement of the force of blood running through veins and arteries, which is measured in two numbers as a ratio: Systolic and Diastolic (S/D) (American Heart Association, 2014). According to a past research study, those who increased their BMI also increased their BP, which put them at risk of hypertension (Droyvold, Midthjell, Nilsen, & Holmen, 2005). From this, Fitness Gymnasium will create a program with the needs and the well-being of its female members in mind.
Population and Size
The current population and size is the amount of gym members. Fitness Gymnasium’s population is the amount of all male and female gym members, which is 100 members. With that being said, the population for Fitness Gymnasium is all male and female gym members, and the size is 100 members.
Target Population and Sample Size
The current target population for the gym is female gym members. At Fitness Gymnasium, the current percentage of female members is 50% of 100 total gym members, which makes the target population 50 females. For Fitness Gymnasium, the sample size is 40 using a 95% confidence level, 5% margin of error with a target population of 40 females (Appendix A).
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ELEMENTS OF STATISTICS / TUTORIALOUTLET DOT COM
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REMEMBER, these are assessed preparatory problems related to the content of Unit 3. The Unit 3 Exam will consist of similar types of
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Running head Final Project Data Analysis1Final Project Data A.docx
Running head: Final Project Data Analysis 1
Final Project Data Analysis 2
Final Project Data Analysis:
Luz Rodriguez
Southern New Hampshire University
Process and calculations
In completing the research on the influence that gender (male/female) has over the length of the hospital stay. We can use several types of statistical tests in analysis a more accurate analysis of the research question. This involves a dot plot and a histogram. In responding to this question, we can place gender in one category but studying it under two separate samples, male and female and the effects of length of stay after a myocardial infarction. We can compute this by resolving quantitative data and the relationship between the two factors s dot plot and a histogram would be effective in achieving this analysis.
Research question
To what extent does gender influence length of hospital stay for MI patients?
Response and predictor variables
Response: Length of hospital stay (LOS)
-Predictor: Gender (female and male)
Type of variable for predictor variable
Predictor: gender (female or male)
Type of diagram for analysis
Dot plot
Histogram
Data analysis
As shown the data tries to compare the differences between gender (male and Female) and the length of stay in hospitals with respect to each other. It’s clear that the length of hospital stay which is represented by 0 is shorter as compared to that of the female which is represented by 1. If there is a larger differences between the two genders, then there is a meaning which would reduce the standard deviation (Gerstman, 2015).
gender
n
mean
variance
Std. dev
Std. err.
median
range
min
max
Q1
Q3
0
65
0
0
0
0
0
0
0
0
0
0
1
35
1
0
0
0
1
0
1
1
1
1
Hypothesis test results:
Difference
Sample Diff.
Std. Err.
DF
T-Stat
P-value
μ1 - μ2
6.49
0.59375453
198
10.930443
<0.0001
References
Gerstman, B. B. (2015). Basic Biostatistics Statistics for Public Health (2nd ed.). Burlington, MA: Jones & Bartlett Learning.
gender 1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 2.0 17.0 34.0 3.0 6.0 1.0 3.0 gender 1 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 2.0 17.0 34.0 3.0 6.0 1.0 3.0
Course ProjectCriteriaPointsDescribes the patient that is the subject of the project including diagnoses, medications, and history OR describes the community, its strengths and problems and the mental health issue that will be the subject of the paper.4Includes any substance abuse or violence issues for the patient or community 2Discusses attempted interventions, what has been successful and what has not.4Describes own personal thoughts about the patient's or community's mental health issues. 4Describes any cognitive concerns and possible interventions.2Writes a nursing care plan including three priority nursing diagnoses with r/t and AEB factors.4Includes outcomes in Nursing Outcomes Classification language and interventions in Nursing Intervention Classificati ...
Running head Final Project Data Analysis1Final Project Data A.docx
Running head: Final Project Data Analysis 1
Final Project Data Analysis 2
Final Project Data Analysis:
Luz Rodriguez
Southern New Hampshire University
Process and calculations
In completing the research on the influence that gender (male/female) has over the length of the hospital stay. We can use several types of statistical tests in analysis a more accurate analysis of the research question. This involves a dot plot and a histogram. In responding to this question, we can place gender in one category but studying it under two separate samples, male and female and the effects of length of stay after a myocardial infarction. We can compute this by resolving quantitative data and the relationship between the two factors s dot plot and a histogram would be effective in achieving this analysis.
Research question
To what extent does gender influence length of hospital stay for MI patients?
Response and predictor variables
Response: Length of hospital stay (LOS)
-Predictor: Gender (female and male)
Type of variable for predictor variable
Predictor: gender (female or male)
Type of diagram for analysis
Dot plot
Histogram
Data analysis
As shown the data tries to compare the differences between gender (male and Female) and the length of stay in hospitals with respect to each other. It’s clear that the length of hospital stay which is represented by 0 is shorter as compared to that of the female which is represented by 1. If there is a larger differences between the two genders, then there is a meaning which would reduce the standard deviation (Gerstman, 2015).
gender
n
mean
variance
Std. dev
Std. err.
median
range
min
max
Q1
Q3
0
65
0
0
0
0
0
0
0
0
0
0
1
35
1
0
0
0
1
0
1
1
1
1
Hypothesis test results:
Difference
Sample Diff.
Std. Err.
DF
T-Stat
P-value
μ1 - μ2
6.49
0.59375453
198
10.930443
<0.0001
References
Gerstman, B. B. (2015). Basic Biostatistics Statistics for Public Health (2nd ed.). Burlington, MA: Jones & Bartlett Learning.
gender 1 0.0 10.0 20.0 30.0 40.0 50.0 60.0 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 2.0 17.0 34.0 3.0 6.0 1.0 3.0 gender 1 30.0 4.0 0.0 0.0 0.0 0.0 1.0
gender 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 2.0 17.0 34.0 3.0 6.0 1.0 3.0
Course ProjectCriteriaPointsDescribes the patient that is the subject of the project including diagnoses, medications, and history OR describes the community, its strengths and problems and the mental health issue that will be the subject of the paper.4Includes any substance abuse or violence issues for the patient or community 2Discusses attempted interventions, what has been successful and what has not.4Describes own personal thoughts about the patient's or community's mental health issues. 4Describes any cognitive concerns and possible interventions.2Writes a nursing care plan including three priority nursing diagnoses with r/t and AEB factors.4Includes outcomes in Nursing Outcomes Classification language and interventions in Nursing Intervention Classificati.
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Stat170 - Introductory Statistics Semester 2, 2015 Assignmen.docx
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Running head Research report11Research report13Business Resea.docx
Running head Research report11Research report13Business Resea.docx
Running head Final Project Data Analysis1Final Project Data A.docx
Running head Final Project Data Analysis1Final Project Data A.docx
Running head Final Project Data Analysis1Final Project Data A.docx
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"Charismatic Leadership"
:
It is true that charisma has no genetic link. Charisma is a characteristic which often leaves people in awe. Some seem to naturally possess it, yet many do not. Prepare a paper on the powerful element of charisma. Discuss whether or not charisma can be developed through practice and acquired skill. The 'Body' of the paper must be 5 pages.
this must be in apa format. Five pages for the body. and the final page is references
.
2. What information could not be told from this map3. After revie.docx
2. What information could not be told from this map?
3. After reviewing the passage, review each answer for validity or relevance to the passage and eliminate answers to find the correct answer.
The Enlightenment, Seven Years War started and American War of Independence were all events leading up to the French Revolution. Most of the country was hungry and malnourished due to rising costs and low grain harvest. A high emotion coursing through the French was resentment.
4. Use the table below to find the best most comprehensive answer.
Century
Period
Information
14th Century
Renaissance era
Cultural movement
David, by Michelangelo is an example of high Renaissance art
16th Century
Protestant reformation
A division between churches and Western Christianity
Initiated by Martin Luther Kind and John Calvin
5. What information can be gathered from the picture below?
Modern World Studies – Questions 5-10
Shopping online is about to explode. Retailers of all types are expanding product offerings, adding in-store pickup, free shipping and experimenting with social media. It’s getting harder to tell pure play Internet retailers from the bricks and mortar shops with online portals, and all of them are reinventing how we’ll shop online in the future. Be it via a mobile device, tablet computer, in-store kiosk or computer, the lines are blurring and the result will be both good and bad for consumers.
6. Using the information above and common knowledge would it be safe to say that technology has made it easier to purchase products?
Telecommute jobs have become popular alternatives to going to an office everyday. Telecommute careers allow you to work from the comfort and privacy of your own home doing many of the same jobs that you would perform in a corporate setting. If you are looking to find a telecommute job that is right for you, then start with this list of popular options.
7. Using the above information and your basic knowledge about different jobs which of the below fields is least likely to be done telecommuting?
The United States is in the midst of a profound demographic transformation that will long outlast the current economic downturn. In 2011, the first of the baby boomers—Americans born between 1946 and 1964—turned 65 years old. There are 77 million baby boomers, comprising nearly one quarter of the total population, and their eventual retirement will have an enormous impact on the U.S. economy. This daunting fact is central to the January 2012 employment and labor force projections from the Bureau of Labor Statistics (BLS). As the BLS projects, the retirement of the baby boomers will slow labor force growth significantly over the coming decade. Yet, at the same time, demand will grow for new workers to take the place of those who retire from the labor force, as well as for both highly skilled and less-skilled healthcare workers to look after the growing ranks of elderly Americans. In addition, the Social Security and Medicare programs w.
2-13CreatingaSolutionofKnownMolarityIn this a.docx
2-13:
Creating
a
Solut
i
on
of
Known
Molarity
In this assignment,
y
o
u will weigh out asa
m
p
le of baking soda (NaHC
O
3
) and create a solution ofknown
m
o
l
arit
y
.
1.
Start
VirtualChemLab,
select
Reactions and Stoichiometry,
and then select
Creating aSolut
i
on of Known
M
o
larity
from
t
he list of assig
n
m
ents.The lab will open in the Ti
t
ration laborato
r
y
.
2.
In the labora
t
o
r
y
, a bot
t
le of baking soda (sodiumbicarbonate, NaHCO
3
) will be next to thebalance, and an e
m
ptybeaker will be on the stir plate. Drag the e
m
ptybeaker to the spot
l
ight next
t
o
t
h
e balance, clickin the
Ba
l
an
c
e
area to zoomin, place aweigh paper on the balan
c
e, and tare the
balance.
3.
Open the bot
t
le by clicking on the l
i
d (
Remove Li
d
). Pick up the
S
c
oo
p
and scoop out so
m
e sa
m
ple by first dragging the scoop tothe
m
outh of the bottle and then pull
i
ngthe scoop down the face of the
bottle. As the scoop is dragged down
t
h
e face of the bottle it will p
i
ckup different quantities ofsolid. Select the largest sa
m
ple possible and d
r
ag the scoop
t
othe weighing paper on
th
e balance until it
snaps in place and then let go. This will put app
r
oximately1 gofsa
m
ple on the balance. Repeat
with a second
Scoop
. Record the
m
a
ss of the NaHCO
3
in the data table.
4.
Drag the we
i
gh paper to the beaker and add the NaHC
O
3
sa
m
p
le
t
othe beaker. Click on thegreen
Zoom
Out
arrow to return
t
othe laborator
y
.
5.
Drag the beaker to the 50mL graduated c
y
l
i
nder (thelargest one) by the sink and e
m
ptythe sa
m
ple
into the
c
y
linder. Hold thec
y
l
i
nder under the tap unt
i
l it fills withwater to
m
a
k
e an aqueous solution
of NaHC
O
3
. (When the graduated c
y
linder is full it will auto
m
at
i
ca
l
ly snap back into place.) Note that the solid is added and dissolved before the volu
m
e ismeasured when
m
aking a
m
ol
ar solution.
Che
m
ists normallyuse a volu
m
etric flask for
m
aking
m
o
l
ar solutions, but
t
his is not available in the s
i
m
ulation.
6.
Determine the liters of solution
i
nthe
c
ylinder and
r
ecord the da
t
a in thedata
t
able.
7.
Determine the moles of NaHCO
3
in
the sample and r
e
cord the datain the da
t
a table.
Data
T
a
ble
ma
s
s N
a
HC
O
3
m
o
l
es
N
aH
C
O
3
liters solution
8.
The
m
olarityis calcula
t
ed using the fo
r
m
u
l
a:
mass
solute
molarity
=
=
molarmasssolute
moles
solute
L
solution
L
solution
67
Virtual ChemLab: General Chemistry, Student Lab Manual/Workbook, v4.5
, Third Edition, by Brian F. Woodfield and Matthew C. Asplund. Published by Prentice Hall.
Copyright © 2013 by Pearson Education, Inc.
Rea
c
tionsandS
t
oichiom
e
t
r
y
Calculate
the molarity of
t
h
e NaHCO
3
solution
inun
i
ts of mol/
L
.
.
2-3 page APA with 3-4 cites Prepare a 2-3 page paper using APA f.docx
2-3 page APA with 3-4 cites
Prepare a 2-3 page paper using APA format discussing how the Coase Theorem provides an alternative to government regulation and provision of services. How is the definition of private property a critical part of this analysis? Paper requires 2-4 cites from scholarly works.
.
2-3 page essay question selected from one out of three possible .docx
2-3 page essay question selected from
one
out of three possible questions:
Consider the term censorship. Although we have talked primarily about censorship within the context of China, it has been influential in both Japan (see John Dower text) and Korea (Suzy Kim and lectures) as well. Reflect on the role of censorship in two East Asian countries since the end of World War II. How have decisions about thought control in the mid-twentieth century continued to influence these societies today?
What are the arguments for and against the democratization of China? Do you believe China’s eventual democratization is inevitable? Why or why not?
Internet access has been lauded by some commentators as the prescription for bringing an end to nationalism across the world. It has also been seen as a way to give oppressed peoples a voice. What is your assessment of the utility of the internet for precipitating political and cultural change in East Asia?
.
2) CompareContrast the life of an indentured servant with that of a.docx
2) Compare/Contrast the life of an indentured servant with that of an African slave
How were these groups similar and/or different? What were their reasons for relocating to the New World? Discuss their previous circumstances. Describe their circumstances after coming to the New World. Discuss any issues associated with the historical/political atmosphere of this period. Where did they settle? Why did they settle in a particular area? Identify any specific characteristics associated with each group. Was life in the New World what they had previously expected? Why or why not? Support your essay with historical facts by using scholarly resources
.
2 part task APA FormatPart 1The role of the nurse educator requ.docx
2 part task: APA Format
Part 1
The role of the nurse educator requires specialized knowledge and skills. One of the essential competencies necessary for the role is the ability to develop relevant curricula for the preparation of future nurses. It is therefore important that nurse educators comprehend and stay well-informed of trends and issues which may impact nursing education.
This task is intended to facilitate your ability to develop competency statements and related learning objectives; select relevant learning assessment and evaluation tools; create learning activities that promote critical thinking and reflective skills; and actively engage and support students with diverse learning needs. As an educator, you are also required to demonstrate effective analytical skills in the evaluation of methods used to determine the achievement of program outcomes. In addition, in this task you write an element of an exam. This will help you comprehend different item types and the process involved when you develop items for course exams. These learning activities assist in building an educational foundation between the classroom setting and the clinical setting.
Scenario:
The nursing faculty at Hartford University have developed a new BSN curriculum and begun the work of designing and developing individual courses. You are a full-time, tenure-track faculty member assigned to develop courses in level one—the first year of the nursing program. Students at this level have completed all prerequisites for the BSN program.
You are asked to develop the Nursing Fundamentals course, the first clinical course students engage in once admitted to the BSN nursing program. According to the results of the nursing program entrance exam, the students who will be taking the Nursing Fundamentals course were found to have an equal distribution of visual, auditory, and kinesthetic learning styles. The Nursing Fundamentals course will introduce students to nursing care across the lifespan. It will also provide students with the tools necessary to perform basic nursing care in clinical settings and will provide the framework for future clinical courses (e.g., medical/surgical, pediatric, obstetrics/gynecology, mental health, and community nursing specialties).
Requirements:
A. Develop
four
competency statements specific to the Nursing Fundamentals course that are based on contemporary professional nursing standards and guidelines.
1. Explain how
each
of the
four
competencies you developed aligns with
one
of the following national nursing standards and guidelines:
• Commission on Collegiate Nursing Education (CCNE)
• National League for Nursing (NLN)
• Quality and Safety Education for Nurses (QSEN)
2. Create
three
learning objectives for
one
of the course competencies that you developed.
a. Discuss
one
criterion you will use to select appropriate learning resources to achieve the learning objectives you created.
3. Discuss
one
of the following a.
2 pages Comparison and Contrast and one page for sourcesPage No .docx
2 pages Comparison and Contrast and one page for sources
Page No 4 Chosen One of Analytical Skills and write one page
Page No 4 Chosen One of Information Technology (IT) Knowledge and Skills and write one page
Text should be 12-point, Times-Roman font, single-spaced.
one page is dedicated to the bibliography section (APA citations).
.
2 PagesAPA StyleYou have been promoted to a member of the mana.docx
You have been promoted to a management position in the financial department of Krona and must prepare a new employee for their role in assisting with the board of directors meeting and annual financial reports. You are to write an email explaining to the new employee the components and process for creating an annual report, with a focus on how accounting inputs are formulated into financial statements and reports. The email should also discuss 3 of the following annual report components: financial statements, management discussion and analysis, and financial/operating ratios, explaining what information they provide and why understanding them is important.
2 points Question 2 The EPAs Superfund Trust was establis.docx
The document appears to be a set of multiple choice questions about environmental topics. It includes 50 questions about various laws, agencies, and issues related to the environment, hazardous waste, energy, and natural resources. The questions cover a wide range of topics including the Superfund Trust, Endocrine Disruptor Screening Program, renewable fuels, nuclear waste, wetlands protection, and more.
2 parts 1st. part is answer this QACompared to other countries.docx
2 parts
1st. part is answer this QA
Compared to other countries, why do you think the US is more crime prone? How do you think the criminal justice system is dealing with criminals today? Are we focusing on rehabilitating or punishing offenders? Please provide examples
.
2ed. part is reply to this student's post:
I was very surprised and interested in a lot of the information in chapter 1. I have always been interested in crime shows and talking about crime but it turns out there is a lot I did not know about it. I had no idea there were so many different theories and perspectives on crime. Personally, I believe in the classical theory and have a conformity perspective on human nature. The strain theory was very interesting to me because I believe many feel this way and will do anything they need to do in order to achieve something they want. I also did not know there were so many different data basis and crime reporting systems. Crime is measured in so many different ways, it's very interesting to me.
2 parts split up and half page for each part
.
2 parts 1st. part is answer this QAGive an example from someth.docx
2 parts
1st. part is answer this QA
Give an example from something in chapter one that has stood out to you. Maybe it's changed the way you think about criminals or why people commit crime. Finally respond to another student's post. Be sure to give a detailed response (i.e., I agree will simply not be enough).
2ed. part is reply to this student's post:
I was very surprised and interested in a lot of the information in chapter 1. I have always been interested in crime shows and talking about crime but it turns out there is a lot I did not know about it. I had no idea there were so many different theories and perspectives on crime. Personally, I believe in the classical theory and have a conformity perspective on human nature. The strain theory was very interesting to me because I believe many feel this way and will do anything they need to do in order to achieve something they want. I also did not know there were so many different data basis and crime reporting systems. Crime is measured in so many different ways, it's very interesting to me.
2 parts split up and half page for each part
.
2 pagesOne of the functions of HR is to develop and manage employe.docx
2 pages
One of the functions of HR is to develop and manage employee communication programs. This may involve communicating new programs and procedures, new benefit plans or changes, and other company messages. On the other hand, it also involves gathering feedback from employees to assess how they feel about the organization and ideas they have for helping the organization to succeed.
From a strategic viewpoint, how do you feel communication programs can most effectively be utilized?
What value can they bring to the company in terms of helping the company to remain competitive?
Are there any additional challenges or additional value for communication programs implemented in a multinational organization?
.
2 POwer Point slides with at least 200 words of speaker notes .docx
2 POwer Point slide
s with at least
200 words
of speaker notes per slide and one scholarly source addressing the following:
In the past 2–5 years, employee handbooks and manuals have needed to be updated to include the use of social media and electronic devices. Using an employee handbook from a current or previous workplace, make suggestions for improving these sections, because new sources of social media and more advanced electronic devices are regularly being introduced to the market. Address topics such as: refraining from workplace commentary on social media, maintaining a professional image, what can be shared and what not to share on social media, harassment, privacy, and IT security.
.
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- 1. 152 pts total For Questions 1-2 use the 7 step process to answer. Refer to slides if you are unsure of the 7 step process. PLEASE DON’T OMIT ANY PART OF THE PROCESS!!! (40 pts) THIS IS DONE IN SPSS USING BREAST CANCER AND OBESITY DATASET Dataset Background – PLEASE READ: Obesity is very common in American society and is a risk factor for breast cancer for postmenopausal women. One mechanism explaining why obesity is a risk factor is that it may raise estrogen levels in women. In particular, one type of estrogen, serum estradiol, is a strong risk factor for breast cancer. To better assess this relationship, researchers studied a group of 200 postmenopausal women. The SPSS file is entitled, Breast Cancer and Obesity . Adiposity was measured in two different ways: (a) by body mass index (BMI) = weight (kg) / height(m 2 ) and also (b) by waist-hip ratio (WHR) = waist circumference/hip circumference. BMI is a measure of overall adiposity, whereas WHR is a
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- 3. 3 Ethnicity 1 = African-American, 0 = Caucasian NUMCHILD 4 Parity, number of children AGEFBO 5 Age at 1 st birth (missing a response if never had a child) ANYKIDS 6 Gave birth to any children? 1 = Yes, 0 = No AGEMENAR 7
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- 7. .000 Body mass index .537 .278 .136 1.933 .055 a Dependent Variable: Estradiol 4. What is the dependent variable and what is the independent variable? 5. Please write out the regression prediction equation 6. Please interpret the slope and the intercept in terms of the original variables. a. Are they significant? Why or why not?
- 8. b. Please report APA results. 7. The p-value is a probability. Specifically it is the probability of what? Conceptual Problems (3 pts each – 23 pts total) 8. You are a professor and want to report to the class the quiz score that will most accurately depict the value of centrality of everyone’s quiz scores. Below is a table of the 18 students’ results. Enter into SPSS and answer the below questions. 90 90 91 91 100 36 90 89 22 95
- 9. 97 95 40 90 38 90 92 91 a. Is the continuously measured quiz score normally distributed or positively/negatively skewed? Provide evidence for your answer using both a histogram and the skewness/std error value. b. Based off your answer in Part A above, is the mean or median then a more accurate reflection of the class’ quiz score centrality? Why? Be sure to include in your answer the mean and median quiz score values. 9. If I have a a heart rate variable measured as High, Moderate, and Low (bpm) and I want to see if there is a significant difference between the three categories for some dependent variable would I need to run a post hoc analysis?? Why or why
- 10. not?? 10. A study is conducted to assess the effects experience in sports has on coping with stress. Three categories are used for experience, more than ten years, 5-10 years and less than 5 years. We want to see if there is a difference in sress coping (measured continuously) between the three groups. Results are F(2,50) = 5.43, p=.043. It is concluded that because of p<.05 the ten year group is significantly greater than the 5-10 year group and the less than 5 year group. Is this a correct statement?? If not, please state why not. 11. In a correlation study an r=.8 is found. It is therefore concluded that variable x causes an increase in variable y. Is this true or false?? Please state why not if it isn’t. 12.
- 11. In a Levene’s test for homogeneity of variance, a p value of .78 is found. It is concluded because the p value is greater than .05 we reject the null and conclude varaiances can be assumed equal. True or false?? Please correct if false. 13. What is meant when I say a particular statistical test is an omnibus test? Guess the Test – report IV, DV and all levels and type of measurement and the appropriate statistical test (15 pts total) 14. A researcher is interested in the effects muscle soreness has on power. 15 participants come are tested before an intense cardio/plyometric training bout on their vertical jump. After the initial test, they are put through an intense training session to invoke muscle soreness. The participants come back in the following day, and each day after until day 4 to be re-teseted on their vertical jump.
- 12. We want to know if there is a decrease in vertical jump scores across the measurement periods. 15. A researcher wants to see if the the rectus abdominus muscle has higher EMG amplitude while using an Ab Rocket compared to a standared sitting crunch. The participant is tested on the Ab Rocket and then tested doing a crunch. We want to see if the muscle activity is higher in the ab rocket compared to the standard crunch 16. A researcher would like to see if there is a significant difference in exercise enjoyment (measured continuously) between exercise status groups (high intensity, moderate intensity, control). Use the below output to answer the questions. A one way ANOVA was run to see if there were significant differences in mean estradiol between WHR (waist hip ratio) categories. (15 pts total) Descriptives
- 13. Estradiol N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound 0-.69 27 45.7348 16.89906 3.25223 39.0498 52.4199 20.67 78.00 .70-.79 125 40.7233 19.79922 1.77090 37.2182
- 14. 44.2284 12.00 120.00 .8 and greater 48 50.9721 23.32412 3.36655 44.1995 57.7447 17.00 146.00 Total 200 43.8596 20.71044 1.46445 40.9717 46.7474 12.00 146.00 Test of Homogeneity of Variances Estradiol Levene Statistic df1 df2 Sig. .488 2 197 .615
- 15. ANOVA Estradiol Sum of Squares df Mean Square F Sig. Between Groups 3752.703 2 1876.351 4.530 .012 Within Groups 81602.857 197 414.228 Total 85355.560 199 Multiple Comparisons Dependent Variable: Estradiol Bonferroni
- 16. (I) whr_category (J) whr_category Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound 0-.69 .70-.79 5.01153 4.31921 .742 -5.4176 15.4407 .8 and greater -5.23727 4.89607 .858 -17.0593 6.5848 .70-.79 0-.69 -5.01153 4.31921 .742 -15.4407
- 17. 5.4176 .8 and greater -10.24880(*) 3.45595 .010 -18.5935 -1.9041 .8 and greater 0-.69 5.23727 4.89607 .858 -6.5848 17.0593 .70-.79 10.24880(*) 3.45595 .010 1.9041 18.5935 * The mean difference is significant at the .05 level. 17. Please write out the null and research hypothesis 18. What does the homogeneity of variance test tell us? What is the result?
- 18. 19. Please write the results of the ANOVA in APA format. Do we reject the null or fail to reject the null? 20. Are post hocs necessary?? If so, please report which conditions are significant from one another. 21. What are the other assumptions that go into the one way ANOVA? For the next set of questions, please read the datset description and then run the appropriate analysis. No output is required. Please just run the analysis and report JUST the results and your conclusion to the question …BE SURE TO INCLUDE ALL IMPORTANT/RELEVANT INFORMATION TO A CONLUSION! (20pts) 22. Dataset: football punters Description - Investigators studied physical characteristics and
- 19. ability in 13 football punters. Each volunteer punted a football ten times. The investigators recorded the average distance for the ten punts, in feet. They also recorded the average hang time (time the ball is in the air before the receiver catches it) for the ten punts, in seconds. In addition, the investigators recorded five measures of strength and flexibility for each punter: right leg strength (pounds), left leg strength (pounds), right hamstring muscle flexibility (degrees), left hamstring muscle flexibility (degrees), and overall leg strength (foot-pounds). Taken from the study "The relationship between selected physical performance variables and football punting ability" by the Department of Health, Physical Education and Recreation at the Virginia Polytechnic Institute and State University, 1983. a. Question: Is left leg strength significantly different from right leg strength? b. Question: Can overall leg strength predict the average punt distance?