A researcher is interested in comparing the Christian maturity level.pdf
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A researcher is interested in comparing the Christian maturity level of students who volunteer for community service versus those who do not. The researcher assumes that those who perform community service will have higher Christian maturity scores. The maturity scores tend to be skewed (not normally distributed). Higher scores indicate higher Christian maturity. No Community Service Community Service 32 47 40 48 54 59 13 72 20 80 26 55 a. What statistical test should be used to analyze these data? b. Is this a one- or two- tailed test? c. Identify H0 and Ha for this study d. Conduct the appropriate analysis e. Should H0 be rejected? What should the researcher conclude? Solution The student’s t test for equality means can be used. Let µ_1 and µ_2 denote the mean scores of the no community service and community service groups respectively. H0: µ_1=µ_2 (the mean scores are the same in both groups) H1: µ_1.
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1) A sample of 47 observations is selected from a normal popul.docx
1) A sample of 47 observations is selected from a normal population. The sample mean is 31, and the population standard deviation is 4. Conduct the following test of hypothesis using the 0.05 significance level.
H0 : μ ≤ 30
H1 : μ > 30
a.
Is this a one- or two-tailed test?
"One-tailed"-the alternate hypothesis is greater than direction.
"Two-tailed"-the alternate hypothesis is different from direction.
b.
What is the decision rule? (Round your answer to 3 decimal places.)
H0, when z >
c.
What is the value of the test statistic? (Round your answer to 2 decimal places.)
Value of the test statistic
d.
What is your decision regarding H0?
Reject
Do not reject
There is evidence to conclude that the population mean is greater than 30.
e.
What is the p-value? (Round your answer to 4 decimal places.)
p-value
2) At the time she was hired as a server at the Grumney Family Restaurant, Beth Brigden was told, “You can average $86 a day in tips.” Assume the population of daily tips is normally distributed with a standard deviation of $3.81. Over the first 48 days she was employed at the restaurant, the mean daily amount of her tips was $87.07. At the 0.02 significance level, can Ms. Brigden conclude that her daily tips average more than $86?
a.
State the null hypothesis and the alternate hypothesis.
H0: μ = 86 ; H1: μ ≠ 86
H0: μ ≥ 86 ; H1: μ < 86
H0: μ ≤ 86 ; H1: μ > 86
H0: μ >86 ; H1: μ = 86
b.
State the decision rule.
Reject H0 if z > 2.05
Reject H1 if z < 2.05
Reject H0 if z < 2.05
Reject H1 if z > 2.05
c.
Compute the value of the test statistic. (Round your answer to 2 decimal places.)
Value of the test statistic
d.
What is your decision regarding H0?
Reject H0
Do not reject H0
e.
What is the p-value? (Round your answer to 4 decimal places.)
p-value
3) The Rocky Mountain district sales manager of Rath Publishing Inc., a college textbook publishing company, claims that the sales representatives make an average of 37 sales calls per week on professors. Several reps say that this estimate is too low. To investigate, a random sample of 41 sales representatives reveals that the mean number of calls made last week was 40. The standard deviation of the sample is 5.6 calls. Using the 0.025 significance level, can we conclude that the mean number of calls per salesperson per week is more than 37?
H0 : μ ≤ 37
H1 : μ > 37
1.
Compute the value of the test statistic. (Round your answer to 3 decimal places.)
Value of the test statistic
2.
What is your decision regarding H0?
H0. The mean number of calls is than 37 per week.
4) A United Nations report shows the mean family income for Mexican migrants to the United States is $27,540 per year. A FLOC (Farm Labor Organizing Committee) evaluation of 19 Mexican family units reveals a mean to be $28,956 with a sample standard deviation of $10,250. Does this information disagree with the United Nations report? Apply the 0.01 significance level.
a.
St ...
Statistics and Probability Testing Hypothesis.pptx
Sofia conducted a survey of her friends' daily social media usage to see if it differed from the global average of 142 minutes reported in another survey. She formulated two claims: Claim A stated her friends' usage was the same as the global average, while Claim B stated it was higher. Hypothesis testing would be needed to statistically analyze the data from Sofia's survey to determine if her friends' usage supported Claim A or Claim B. Hypothesis testing involves defining a null hypothesis (Ho) stating no difference and an alternative hypothesis (Ha) stating a difference.
test 3 AAMultiple ChoiceIdentify the choice that best comple.docx
test 3 AA
Multiple Choice
Identify the choice that best completes the statement or answers the question.
____ 1. For an ANOVA comparing three treatment conditions, what is stated by the alternative hypothesis (H1)?
a.
There are no differences between any of the population means.
b.
At least one of the three population means is different from another mean.
c.
All three of the population means are different from each other.
d.
None of the other choices is correct.
____ 2. On average, what value is expected for the F-ratio if the null hypothesis is true?
a.
0
c.
k – 1
b.
1.00
d.
N – k
____ 3. A research study comparing three treatments with n = 5 in each treatment produces T1 = 5, T2 = 10, T3 = 15, with SS1 = 6, SS2 = 9, SS3 = 9, and SX2 = 94. For this study, what is SSbetween?
a.
10
c.
34
b.
24
d.
68
____ 4. An analysis of variance produces SSbetween = 30, SSwithin = 60, and an F-ratio with df = 2, 15. For this analysis, what is the F-ratio?
a.
30/60 = 0.50
c.
15/4 = 3.75
b.
60/30 = 2.00
d.
4/15 = 0.27
____ 5. If an analysis of variance is used for the following data, what would be the effect of changing the value of M1 to 20?
Sample Data
M1 = 15 M2 = 25
SS1 = 90 SS2 = 70
a.
Increase SSbetween and increase the size of the F-ratio
b.
Increase SSbetween and decrease the size of the F-ratio
c.
Decrease SSbetween and increase the size of the F-ratio
d.
Decrease SSbetween and decrease the size of the F-ratio
____ 6. In general, what factors are most likely to reject the null hypothesis for an ANOVA?
a.
Small mean differences and small variances
b.
Small mean differences and large variances
c.
Large mean differences and small variances
d.
Large mean differences and large variances
____ 7. A two-factor study with two levels of factor A and three levels of factor B uses a separate group of n = 5 participants in each treatment condition. How many participants are needed for the entire study?
a.
5
c.
25
b.
10
d.
30
____ 8. The following data represent the means for each treatment condition in a two-factor experiment. Note that one mean is not given. What value for the missing mean would result in no A´B interaction?
B1 B2
A1
20
30
A2
10
?
a.
10
c.
30
b.
20
d.
40
____ 9. If a two-factor analysis of variance produces a statistically significant interaction, what can you conclude about the main effects?
a.
Either the main effect for factor A or the main effect for factor B is also significant
b.
Both the man effect for factor A and the main effect for factor B are significant
c.
Neither the main effect for factor A nor the main effect for factor B is significant
d.
The significance of the main effects is not related to the significance of the interaction
____ 10. What is indicated by a positive value for a correlation?
a.
Increases in X tend to be accompanied by increases in Y
b.
Increases in X tend to be accompanied by decreases in Y
c.
A much ...
HYPOTHESIS TESTING
Hypothesis tests are used to statistically determine the probability that a hypothesis is accepted at a given significance level. The purpose is to determine if there is enough statistical evidence to support a hypothesis. A hypothesis predicts the relationship between variables and can be tested, whereas a research question does not make a prediction. Good hypotheses are compatible with current knowledge, logically consistent, clearly stated, and testable. The null hypothesis asserts there is no difference or relationship, while the alternative or research hypothesis predicts a difference or relationship. Setting a significance level helps determine if results reject the null hypothesis.
Introduction-to-Statistics.pptx
1. The document discusses key concepts in statistics including populations, samples, descriptive statistics, inferential statistics, qualitative and quantitative data, and scales of measurement.
2. It provides examples of statistical tests that can be used including one-sample t-tests, two-sample t-tests, paired t-tests, one-way ANOVA tests, and examples of how they can be applied.
3. The guidelines for designing a statistical study are outlined including identifying variables of interest, developing a data collection plan, collecting and describing data, and interpreting results.
One-Sample Hypothesis Tests
A researcher tested the effectiveness of an herbal supplement on physical fitness using the Marine Physical Fitness Test. 25 college students took the supplement for 6 weeks and averaged a score of 38.68 on the test, compared to the average population score of 35. Using a t-test with α=.05 and df=24, the researcher found the average score of 38.68 was not significantly different than the population mean of 35 (t=2.041, p=.052). Therefore, there is not enough evidence to conclude the supplement had an effect on fitness levels, as the higher average score could be due to chance for this small sample.
ScenarioStatistical significance is found in a study, but the ef.docx
Scenario
Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?
An independent samples t test was conducted to determine whether differences exist between men and women on cultural competency scores. The samples consisted of 663 women and 650 men taken from a convenience sample of public, private, and non-profit organizations. Each participant was administered an instrument that measured his or her current levels of cultural competency. The cultural competency score ranges from 0 to 10, with higher scores indicating higher levels of cultural competency. The descriptive statistics indicate women have higher levels of cultural competency ( M = 9.2, SD = 3.2) than men ( M = 8.9, SD = 2.1). The results were significant t (1311) = 2.0, p <.05, indicating that women are more culturally competent than are men. These results tell us that gender-specific interventions targeted toward men may assist in bolstering cultural competency.
Instructions: Critically evaluate the scenario you selected based upon the following points:
Critically evaluate the sample size.
Critically evaluate the statements for meaningfulness.
Critically evaluate the statements for statistical significance.
Based on your evaluation, provide an explanation of the implications for social change.
I attached the scenario to this message
add at least two references and citations
Number of Pages: 1 Page
Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?
According to The American Statistical Association's Statement on the Use of P Values (2016), Statistical reasoning should not be replaced by P-values. Once significance is noted and the effect is very small, the researcher should not conclude significance just because the P-value suggested so. Other tests should be performed which include construction of confidence intervals. If after several tests significance is still being seen, then the researcher can conclude significance otherwise, he/she should opt for other approaches for the research such as increasing the sample size.
Sample Sizes
Sample sizes used were 663 for women and 650 for men. The data was collected from three points that is public, private and non-profit organizations. Though the sample seems good enough, the entire population figure is not provided. Another problem is that, sample sizes from the three locations were not disclosed which probably means that the samples were all added up and used in the analysis. Sample sizes from each location should be carefully determined based on the population of each location. Since Convenience sampling is error bound, the samples shouldn’t be summed up and used in the analysis. Each location should be examined separately. Thi.
Classroom research
This document outlines the basic process and key concepts for conducting classroom research. It discusses identifying a research problem and formulating hypotheses. It describes the typical research process which involves problem identification, designing a study, collecting and analyzing data, and drawing conclusions. The document also covers different research designs like correlational studies, group comparison studies, and experimental studies. It provides examples and steps for implementing each type of design, including determining variables, developing hypotheses, collecting and analyzing data, and interpreting results. Overall, the document provides guidance on conceptualizing and implementing various quantitative research designs to study classroom phenomena.
Recommended
1) A sample of 47 observations is selected from a normal popul.docx
1) A sample of 47 observations is selected from a normal population. The sample mean is 31, and the population standard deviation is 4. Conduct the following test of hypothesis using the 0.05 significance level.
H0 : μ ≤ 30
H1 : μ > 30
a.
Is this a one- or two-tailed test?
"One-tailed"-the alternate hypothesis is greater than direction.
"Two-tailed"-the alternate hypothesis is different from direction.
b.
What is the decision rule? (Round your answer to 3 decimal places.)
H0, when z >
c.
What is the value of the test statistic? (Round your answer to 2 decimal places.)
Value of the test statistic
d.
What is your decision regarding H0?
Reject
Do not reject
There is evidence to conclude that the population mean is greater than 30.
e.
What is the p-value? (Round your answer to 4 decimal places.)
p-value
2) At the time she was hired as a server at the Grumney Family Restaurant, Beth Brigden was told, “You can average $86 a day in tips.” Assume the population of daily tips is normally distributed with a standard deviation of $3.81. Over the first 48 days she was employed at the restaurant, the mean daily amount of her tips was $87.07. At the 0.02 significance level, can Ms. Brigden conclude that her daily tips average more than $86?
a.
State the null hypothesis and the alternate hypothesis.
H0: μ = 86 ; H1: μ ≠ 86
H0: μ ≥ 86 ; H1: μ < 86
H0: μ ≤ 86 ; H1: μ > 86
H0: μ >86 ; H1: μ = 86
b.
State the decision rule.
Reject H0 if z > 2.05
Reject H1 if z < 2.05
Reject H0 if z < 2.05
Reject H1 if z > 2.05
c.
Compute the value of the test statistic. (Round your answer to 2 decimal places.)
Value of the test statistic
d.
What is your decision regarding H0?
Reject H0
Do not reject H0
e.
What is the p-value? (Round your answer to 4 decimal places.)
p-value
3) The Rocky Mountain district sales manager of Rath Publishing Inc., a college textbook publishing company, claims that the sales representatives make an average of 37 sales calls per week on professors. Several reps say that this estimate is too low. To investigate, a random sample of 41 sales representatives reveals that the mean number of calls made last week was 40. The standard deviation of the sample is 5.6 calls. Using the 0.025 significance level, can we conclude that the mean number of calls per salesperson per week is more than 37?
H0 : μ ≤ 37
H1 : μ > 37
1.
Compute the value of the test statistic. (Round your answer to 3 decimal places.)
Value of the test statistic
2.
What is your decision regarding H0?
H0. The mean number of calls is than 37 per week.
4) A United Nations report shows the mean family income for Mexican migrants to the United States is $27,540 per year. A FLOC (Farm Labor Organizing Committee) evaluation of 19 Mexican family units reveals a mean to be $28,956 with a sample standard deviation of $10,250. Does this information disagree with the United Nations report? Apply the 0.01 significance level.
a.
St ...
Statistics and Probability Testing Hypothesis.pptx
Sofia conducted a survey of her friends' daily social media usage to see if it differed from the global average of 142 minutes reported in another survey. She formulated two claims: Claim A stated her friends' usage was the same as the global average, while Claim B stated it was higher. Hypothesis testing would be needed to statistically analyze the data from Sofia's survey to determine if her friends' usage supported Claim A or Claim B. Hypothesis testing involves defining a null hypothesis (Ho) stating no difference and an alternative hypothesis (Ha) stating a difference.
test 3 AAMultiple ChoiceIdentify the choice that best comple.docx
test 3 AA
Multiple Choice
Identify the choice that best completes the statement or answers the question.
____ 1. For an ANOVA comparing three treatment conditions, what is stated by the alternative hypothesis (H1)?
a.
There are no differences between any of the population means.
b.
At least one of the three population means is different from another mean.
c.
All three of the population means are different from each other.
d.
None of the other choices is correct.
____ 2. On average, what value is expected for the F-ratio if the null hypothesis is true?
a.
0
c.
k – 1
b.
1.00
d.
N – k
____ 3. A research study comparing three treatments with n = 5 in each treatment produces T1 = 5, T2 = 10, T3 = 15, with SS1 = 6, SS2 = 9, SS3 = 9, and SX2 = 94. For this study, what is SSbetween?
a.
10
c.
34
b.
24
d.
68
____ 4. An analysis of variance produces SSbetween = 30, SSwithin = 60, and an F-ratio with df = 2, 15. For this analysis, what is the F-ratio?
a.
30/60 = 0.50
c.
15/4 = 3.75
b.
60/30 = 2.00
d.
4/15 = 0.27
____ 5. If an analysis of variance is used for the following data, what would be the effect of changing the value of M1 to 20?
Sample Data
M1 = 15 M2 = 25
SS1 = 90 SS2 = 70
a.
Increase SSbetween and increase the size of the F-ratio
b.
Increase SSbetween and decrease the size of the F-ratio
c.
Decrease SSbetween and increase the size of the F-ratio
d.
Decrease SSbetween and decrease the size of the F-ratio
____ 6. In general, what factors are most likely to reject the null hypothesis for an ANOVA?
a.
Small mean differences and small variances
b.
Small mean differences and large variances
c.
Large mean differences and small variances
d.
Large mean differences and large variances
____ 7. A two-factor study with two levels of factor A and three levels of factor B uses a separate group of n = 5 participants in each treatment condition. How many participants are needed for the entire study?
a.
5
c.
25
b.
10
d.
30
____ 8. The following data represent the means for each treatment condition in a two-factor experiment. Note that one mean is not given. What value for the missing mean would result in no A´B interaction?
B1 B2
A1
20
30
A2
10
?
a.
10
c.
30
b.
20
d.
40
____ 9. If a two-factor analysis of variance produces a statistically significant interaction, what can you conclude about the main effects?
a.
Either the main effect for factor A or the main effect for factor B is also significant
b.
Both the man effect for factor A and the main effect for factor B are significant
c.
Neither the main effect for factor A nor the main effect for factor B is significant
d.
The significance of the main effects is not related to the significance of the interaction
____ 10. What is indicated by a positive value for a correlation?
a.
Increases in X tend to be accompanied by increases in Y
b.
Increases in X tend to be accompanied by decreases in Y
c.
A much ...
HYPOTHESIS TESTING
Hypothesis tests are used to statistically determine the probability that a hypothesis is accepted at a given significance level. The purpose is to determine if there is enough statistical evidence to support a hypothesis. A hypothesis predicts the relationship between variables and can be tested, whereas a research question does not make a prediction. Good hypotheses are compatible with current knowledge, logically consistent, clearly stated, and testable. The null hypothesis asserts there is no difference or relationship, while the alternative or research hypothesis predicts a difference or relationship. Setting a significance level helps determine if results reject the null hypothesis.
Introduction-to-Statistics.pptx
1. The document discusses key concepts in statistics including populations, samples, descriptive statistics, inferential statistics, qualitative and quantitative data, and scales of measurement.
2. It provides examples of statistical tests that can be used including one-sample t-tests, two-sample t-tests, paired t-tests, one-way ANOVA tests, and examples of how they can be applied.
3. The guidelines for designing a statistical study are outlined including identifying variables of interest, developing a data collection plan, collecting and describing data, and interpreting results.
One-Sample Hypothesis Tests
A researcher tested the effectiveness of an herbal supplement on physical fitness using the Marine Physical Fitness Test. 25 college students took the supplement for 6 weeks and averaged a score of 38.68 on the test, compared to the average population score of 35. Using a t-test with α=.05 and df=24, the researcher found the average score of 38.68 was not significantly different than the population mean of 35 (t=2.041, p=.052). Therefore, there is not enough evidence to conclude the supplement had an effect on fitness levels, as the higher average score could be due to chance for this small sample.
ScenarioStatistical significance is found in a study, but the ef.docx
Scenario
Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?
An independent samples t test was conducted to determine whether differences exist between men and women on cultural competency scores. The samples consisted of 663 women and 650 men taken from a convenience sample of public, private, and non-profit organizations. Each participant was administered an instrument that measured his or her current levels of cultural competency. The cultural competency score ranges from 0 to 10, with higher scores indicating higher levels of cultural competency. The descriptive statistics indicate women have higher levels of cultural competency ( M = 9.2, SD = 3.2) than men ( M = 8.9, SD = 2.1). The results were significant t (1311) = 2.0, p <.05, indicating that women are more culturally competent than are men. These results tell us that gender-specific interventions targeted toward men may assist in bolstering cultural competency.
Instructions: Critically evaluate the scenario you selected based upon the following points:
Critically evaluate the sample size.
Critically evaluate the statements for meaningfulness.
Critically evaluate the statements for statistical significance.
Based on your evaluation, provide an explanation of the implications for social change.
I attached the scenario to this message
add at least two references and citations
Number of Pages: 1 Page
Statistical significance is found in a study, but the effect in reality is very small (i.e., there was a very minor difference in attitude between men and women). Were the results meaningful?
According to The American Statistical Association's Statement on the Use of P Values (2016), Statistical reasoning should not be replaced by P-values. Once significance is noted and the effect is very small, the researcher should not conclude significance just because the P-value suggested so. Other tests should be performed which include construction of confidence intervals. If after several tests significance is still being seen, then the researcher can conclude significance otherwise, he/she should opt for other approaches for the research such as increasing the sample size.
Sample Sizes
Sample sizes used were 663 for women and 650 for men. The data was collected from three points that is public, private and non-profit organizations. Though the sample seems good enough, the entire population figure is not provided. Another problem is that, sample sizes from the three locations were not disclosed which probably means that the samples were all added up and used in the analysis. Sample sizes from each location should be carefully determined based on the population of each location. Since Convenience sampling is error bound, the samples shouldn’t be summed up and used in the analysis. Each location should be examined separately. Thi.
Classroom research
This document outlines the basic process and key concepts for conducting classroom research. It discusses identifying a research problem and formulating hypotheses. It describes the typical research process which involves problem identification, designing a study, collecting and analyzing data, and drawing conclusions. The document also covers different research designs like correlational studies, group comparison studies, and experimental studies. It provides examples and steps for implementing each type of design, including determining variables, developing hypotheses, collecting and analyzing data, and interpreting results. Overall, the document provides guidance on conceptualizing and implementing various quantitative research designs to study classroom phenomena.
Yuchen's final draft (yy3743)
Yuchen Yang comes from Anhui, China and completed her bachelor's degree in Business Economics at UC Irvine. There, she developed an interest in marketing. To gain experience in the field, she interned at Overseas Student Service Corp from 2018-2019 as a Marketing and Sales Specialist. At OSSC, she was involved in complex WeChat-based marketing campaigns and learned to consider implications for revenue and profits. The internship helped her determine that she wants to begin her career as a marketing professional to continue accumulating insights in the field.
Assessment 3 – Hypothesis, Effect Size, Power, and t Tests.docx
Assessment 3 – Hypothesis, Effect Size, Power, and
t
Tests
Complete the following problems within this Word document. Do not submit other files. Show your work for problem sets that require calculations. Ensure that your answer to each problem is clearly visible. You may want to highlight your answer or use a different type color to set it apart.
Hypothesis, Effect Size, and Power
Problem Set 3.1: Sampling Distribution of the Mean Exercise
Criterion:
Interpret population mean and variance.
Instructions:
Read the information below and answer the questions.
Suppose a researcher wants to learn more about the mean attention span of individuals in some hypothetical population. The researcher cites that the attention span (the time in minutes attending to some task) in this population is normally distributed with the following characteristics: 20
36
. Based on the parameters given in this example, answer the following questions:
1. What is the population mean (μ)? __________________________
2. What is the population variance
? __________________________
3. Sketch the distribution of this population. Make sure you draw the shape of the distribution and label the mean plus and minus three standard deviations.
Problem Set 3.2: Effect Size and Power
Criterion:
Explain effect size and power.
Instructions:
Read each of the following three scenarios and answer the questions.
Two researchers make a test concerning the effectiveness of a drug use treatment. Researcher A determines that the effect size in the population of males is
d
= 0.36; Researcher B determines that the effect size in the population of females is
d
= 0.20. All other things being equal, which researcher has more power to detect an effect? Explain. ______________________________________________________________________
Two researchers make a test concerning the levels of marital satisfaction among military families. Researcher A collects a sample of 22 married couples (
n
= 22); Researcher B collects a sample of 40 married couples (
n
= 40). All other things being equal, which researcher has more power to detect an effect? Explain. ______________________________________________________________________
Two researchers make a test concerning standardized exam performance among senior high school students in one of two local communities. Researcher A tests performance from the population in the northern community, where the standard deviation of test scores is 110 (
); Researcher B tests performance from the population in the southern community, where the standard deviation of test scores is 60 (
). All other things being equal, which researcher has more power to detect an effect? Explain. ______________________________________________________________________
Problem Set 3.3: Hypothesis, Direction, and Population Mean
Criterion:
Explain the relationship between hypothesis, tests, and population mean.
Instructions:
Read the following and answer the questions.
According to Davenport (2014) social media and health care are c.docx
Social media is collaborating with healthcare to meet the needs of providers and patients, and is moving toward using analytics to evaluate its value within healthcare. The document instructs the reader to research areas of social media that could benefit from an analytic model combining data and value-based analytics, then evaluate a resource by discussing five major social media stakeholder roles, whether social media could improve medical practice and provide rationale, and concluding with main points.
Chi square
This document provides an overview of chi-square and analysis of variance (ANOVA) statistical tests. It defines chi-square as a test of independence using contingency tables and as a test of goodness of fit. It also defines ANOVA as a test used to compare three or more population means and determine if they are equal or different. Examples are provided to demonstrate how to perform chi-square and one-way ANOVA calculations and analyses.
Chi-square test.pptx
This document provides an overview of chi-square tests, including:
- Chi-square tests determine if observed and expected frequencies differ significantly. They are used in fields like medical research.
- There are tests for goodness of fit and independence. Goodness of fit compares data to a hypothesized distribution. Independence examines the relationship between two variables.
- Examples demonstrate applying chi-square tests, calculating statistics, determining significance. The independence example found age impacts political party choice.
Exam III Tian Xia
This exam covers hypothesis testing, t-tests, ANOVA, and two-way ANOVA. It provides multiple choice, short answer, and calculation questions to test understanding of key concepts. Students are instructed to show their work, use complete sentences, and justify their responses. The exam also includes a Bible verse and instructions about the honor code.
Data analysis presentation by Jameel Ahmed Qureshi
Presentation is made by the student of M.phil Jameel Ahmed Qureshi Faculty of Education Elsa Kazi campus Hyderabad UoS Jamshoron, This presentation is an assignment assign by the Dr. Mumtaz Khwaja
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The document discusses how pop art, which emerged in the 1950s and 1960s, was influenced by the era of wealth and consumerism experienced in western industrial societies. It specifically focuses on exploring how pop art and consumerism are expressed in the work of British artist Richard Hamilton. The goal is to analyze how Hamilton incorporated elements of popular culture and consumerism into his pop art pieces.
Ewing, Kim, Kinsky, Moore, & Freberg (2018) Teaching Digital and Social Media...
Ewing, Kim, Kinsky, Moore, & Freberg (2018) Teaching Digital and Social Media...AEJMC Journal of Public Relations Education (JPRE)
Teaching Digital and
Social Media Analytics:
Exploring Best Practices and Future
Implications for Public Relations Pedagogy
ABSTRACT
One of the growing areas within public relations is digital and social
media analytics. Teaching the use of analytics to communication
students is not new, but studying what is being taught is almost
non-existent. The public relations research literature has supported
exploring the value of data analysis to gain audience insights, to
measure communication strategies, and to evaluate campaign
efforts. The purpose of this study is to explore the ways in which
faculty are teaching social media analytics. Two content analyses
were conducted to explore trends of digital and social media
analytics training. Authors analyzed related course syllabi and a
Twitter chat on the subject sponsored by the AEJMC PR Division
and PRSA Educators Academy. Findings and future implications
in teaching digital and social media analytics for educators and
public relations practitioners are discussed.SOCIOMETRY final.pptx
This document provides information about sociometry, which is defined as the quantitative study and measurement of social relationships within groups. Some key points:
- Jacob Moreno coined the term sociometry and conducted the first long-term sociometric study in the 1930s. Sociometry uses techniques like sociometric tests to measure social preferences and choices within a group.
- The results are often represented through sociometric matrices, which show social choices between individuals, and sociograms, which visually depict these social networks.
- Analyzing sociometric data can reveal subgroups, leaders, and social dynamics within a group. It provides objective information about a group's structure and social integration.
- Sociometry is used in fields like
Willis (2018) Diagnosing Health Campaigns: A Campaign Evaluation Assignment, ...
Willis (2018) Diagnosing Health Campaigns: A Campaign Evaluation Assignment, ...AEJMC Journal of Public Relations Education (JPRE)
This teaching brief describes a group assignment where students evaluate real-world health communication campaigns developed by the CDC. Students are divided into groups and each analyzes a different CDC campaign. They discuss how the campaign addressed key components of design like research, messaging, and evaluation. They also consider how the CDC communicates about the campaigns on its website. The goal is for students to apply their learning and get experience critically analyzing actual public health campaigns. Student feedback indicates the assignment helps them better understand how theory and research inform strategic health communication in practice.Data analysis
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Experimental Final 11 Jul
This document proposes two experimental research studies. The first study aims to examine the effect of parental guidance on healthy diets by comparing BMI changes in students who receive parental education versus normal education. The second study aims to determine if there is a relationship between using online discussion forums and student learning performance in science by comparing test results between students given access to forums versus not. Both studies would use a pre-test post-test control group design and t-tests to analyze results.
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The document summarizes a research paper that studied the unintended emotional effects of participation in online health communities. It used machine learning models to analyze post-level data from a Chinese social media platform for those with major depressive disorder. The study found that: 1) emotional support targeted at other users had a negative impact on readers' emotions, while 2) auxiliary content had a positive effect. It contributed theoretically by providing a more nuanced understanding of emotional influence within these communities and managerially by suggesting strategies to enhance user mental health.
Statistical tests for independent groups
The document discusses different statistical tests used for analyzing data from independent groups, including the chi-square test, Wilcoxon Mann-Whitney U test, t-test, and analysis of variance (ANOVA). It provides examples of using a t-test to compare math scores between male and female students, and using ANOVA to analyze the effect of different teaching strategies on computational abilities. Factorial ANOVA is introduced as a method to analyze the effects of multiple independent variables.
Experimental Research
The document outlines a research study that aims to determine the relationship between ICT use in the classroom and student academic achievement in social science. The study will compare test scores of two groups of P4 students - one group that studies social science with ICT and one without. If the ICT group scores higher, it will support the hypothesis that ICT use is positively related to student exam results in social science. If not, it may mean ICT is not effectively used or does not improve learning.
Experimental Research
The document outlines a research study that aims to determine the relationship between ICT use in the classroom and student academic achievement in social science. The study will compare exam results of two groups of P4 students - one group that studies social science with ICT and one group that studies without. Statistical analysis will be used to analyze differences in mean scores between the groups and determine whether ICT use is positively related to student exam results.
A researcher is investigating the relationship betweenpersonality .pdf
A researcher is investigating the relationship between
personality and birth order position. A sample of college students is classified
into four birth order categories (1st, 2nd, 3rd, 4thor later) and given a personality
test that measures the degree of extroversion on a 50-point scale. Identify the
statistical procedure that is appropriate for analyzing this data. Explain your
answer.
Solution
use regression analysis to find the equation relating the degree of extroversion to the order of
birth..
A researcher is interested in the effect of St. Johns Wort on memory.pdf
A researcher is interested in the effect of St. Johns Wort on memory. A group of 25 college
students is selected to participate in a research study. The average memory score obtained for the
25 students is a ______.
a. sample
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c. statistic
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Solution
sample a is an answer.
A research report presents the results of an independent measures AN.pdf
A research report presents the results of an independent measures ANOVA as: F(3, 28)=5.36,
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A researcher is comparing samples from 6 different populations. Assume that the
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Assessment 3 – Hypothesis, Effect Size, Power, and
t
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Complete the following problems within this Word document. Do not submit other files. Show your work for problem sets that require calculations. Ensure that your answer to each problem is clearly visible. You may want to highlight your answer or use a different type color to set it apart.
Hypothesis, Effect Size, and Power
Problem Set 3.1: Sampling Distribution of the Mean Exercise
Criterion:
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Instructions:
Read the information below and answer the questions.
Suppose a researcher wants to learn more about the mean attention span of individuals in some hypothetical population. The researcher cites that the attention span (the time in minutes attending to some task) in this population is normally distributed with the following characteristics: 20
36
. Based on the parameters given in this example, answer the following questions:
1. What is the population mean (μ)? __________________________
2. What is the population variance
? __________________________
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Explain effect size and power.
Instructions:
Read each of the following three scenarios and answer the questions.
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Teaching Digital and
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ABSTRACT
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Willis (2018) Diagnosing Health Campaigns: A Campaign Evaluation Assignment, ...
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This teaching brief describes a group assignment where students evaluate real-world health communication campaigns developed by the CDC. Students are divided into groups and each analyzes a different CDC campaign. They discuss how the campaign addressed key components of design like research, messaging, and evaluation. They also consider how the CDC communicates about the campaigns on its website. The goal is for students to apply their learning and get experience critically analyzing actual public health campaigns. Student feedback indicates the assignment helps them better understand how theory and research inform strategic health communication in practice.Data analysis
The document discusses different measures of central tendency (mean, median, mode) and how to determine which is most appropriate based on the type of data. It also covers measures of dispersion like range, standard deviation, and variance which provide information about how spread out values are from the central point. The mean is the most commonly used measure of central tendency but the median is less affected by outliers, while the mode represents the most frequent value.
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The document discusses different statistical tests used for analyzing data from independent groups, including the chi-square test, Wilcoxon Mann-Whitney U test, t-test, and analysis of variance (ANOVA). It provides examples of using a t-test to compare math scores between male and female students, and using ANOVA to analyze the effect of different teaching strategies on computational abilities. Factorial ANOVA is introduced as a method to analyze the effects of multiple independent variables.
Experimental Research
The document outlines a research study that aims to determine the relationship between ICT use in the classroom and student academic achievement in social science. The study will compare test scores of two groups of P4 students - one group that studies social science with ICT and one without. If the ICT group scores higher, it will support the hypothesis that ICT use is positively related to student exam results in social science. If not, it may mean ICT is not effectively used or does not improve learning.
Experimental Research
The document outlines a research study that aims to determine the relationship between ICT use in the classroom and student academic achievement in social science. The study will compare exam results of two groups of P4 students - one group that studies social science with ICT and one group that studies without. Statistical analysis will be used to analyze differences in mean scores between the groups and determine whether ICT use is positively related to student exam results.
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