De vry math 399 ilabs & discussions latest 2016

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DeVry MATH 399 ilabs & discussions-Latest 2016
Question
DeVry MATH399 Week 1 Discussion Latest 2016 November
Descriptive Statistics (graded)
If you were given a large data set (i.e., sales over the last year of our top 100 customers), what might
you be able to do with these data? What might be the benefits of describing the data?
DeVry MATH399 Week 2 Discussion Latest 2016 November
Regression (graded)
Suppose you are given data from a survey showing the IQ of each person interviewed and the IQ of
his or her mother. That is all the information that you have. Your boss has asked you to put together a
report showing the relationship between these two variables. What could you present and why?
DeVry MATH399 Week 3 Discussion Latest 2016 November
Probability and Odds (graded)
The odds of winning a game are given as 1:25. What is the probability that you will win this game?
What is the probability that you will lose this game? In your follow -up replies, consider which number
in the odds ratio needs to change and how it needs to change in order to increase the probability of
winning. (Note: See page 145 in the text for a discussion on odds.)
DeVry MATH399 Week 4 Discussion Latest 2016 November
Discrete Probability Variables (graded)
Provide an example that follows either the binomial or Poisson distribution, and explain why that
example follows that particular distribution. In your responses to other students, make up numbers for
the example provided by that other student, and ask a related probability question. Then, show the
work (or describe the technology steps), and solve that probability example.
DeVry MATH399 Week 5 Discussion Latest 2016 November
Interpreting Normal Distributions (graded)
Assume that a population is normally distributed with a mean of 100 and a standard deviation of
15. Would it be unusual for the mean of a sample of 3 to be 115 or more? Why or why not?
DeVry MATH399 Week 6 Discussion Latest 2016 November
Confidence Interval Concepts (graded)
Consider the formula used for any confidence interval and the elements included in that formula . What
happens to the confidence interval if you
1. increase the confidence level,
2. increase the sample size, or

2. 3. increase the margin of error? Only consider one of these changes at a time. Explain your answer
with words and by referencing the formula.
DeVry MATH399 Week 7 Discussion Latest 2016 November
Rejection Region (graded)
How is the rejection region defined, and how is that related to the p value? When do you reject or fail
to reject the null hypothesis? Why do you think statisticians are asked to complete hypothesis testing?
Can you think of examples in courts, in medicine, or in your area?
DeVry MATH399 Week 2 iLab Latest 2016 November
MATH399 Statistics—Lab Week 2
Question 1 is worth 5 points and each question after that is worth 4.5 points, for a total of 50 points
for the lab.
Name:_______________________
Statistical Concepts:
· Using Excel
· Graphics
· Shapes of distributions
· Descriptive statistics
NOTE: Directions for all labs are given based on Excel 2013 for Windows. If you have another version
of Excel, you may need to research how to do the same steps.
Data in Excel
Ø Excel is a powerful, yet user-friendly, data analysis software package. You can launch Excel by
finding the icon and double clicking on it.There are detailed instructions on how to obtain the graphs
and statistics you need for this lab in each question. There is also a link to an Excel how to document
on the iLab page where you opened this file. Further, if you need more explanation of the Excel
functions you can do an internet search on the function like “Excel standard deviation” or “Excel pivot
table” for a variety of directions and video demonstrations.
Ø Data have already been formatted and entered into an Excel worksheet. You will see the link on the
page with this lab document. The names of each variable from the survey are in the first row of the
worksheet. All other rows of the worksheet represent certain students’ answers to the survey
questions. Therefore, the rows are called observations and the columns are called variables. Below,
you will find a code sheet that identifies the correspondence between the variable names and the
survey questions.
SurveyCode Sheet:Do NOT answer these questions. The code sheet just lists the variables name and
the question used by the researchers on the survey instrument that produced the data that are
included in the Excel data file. This is just information. The first question for the lab is after the code
sheet.
Variable Name
Question
Drive Question 1: How long does it take you to drive to the school on average (to the nearest minute)?
State Question 2: In what state/country were you born?
Shoe Question 3: What is your shoe size?
Height Question 4: What is your height to the nearest inch?
Sleep Question 5: How many hours did you sleep last night?
Gender Question 6: What is your gender?
Car Question 7: What color of car do you drive?
TV Question 8: How long (on average) do you spend a day watching TV?
Money Question 9: How much money do you have with you right now?
Coin Question 10: Flip a coin 10 times. How many times did you get tails?

3. Frequency Distributions
1. Create a frequency table for the variable State.In the Excel file, you can click onDataand
thenSortand chooseStateas the variable on which to sort.Once sorted, you can count how many
students are from each state. From that table, use a calculator to determine the relative percentages,
as well as the cumulative percentages.
In the box below, type the states from the database in a column to the left, then type the counts, and
relative and cumulative frequencies to the right of the respective state. Using the data in the table,
make a statement about what the frequency counts or percentages tell about the data.
Creating Graphs
2. Create a bar chart for the frequency table in Question 1. Select the State variable values. Click
onInsertand then click on the arrow on the bottom right of theChartsarea and selectClustered
Columnand clickOK. (Again, different versions of Excel may need different directions.) Add an
appropriate title and axis label.Copy and paste the graph here.
3. Create a pie chart for the variable Car. Select the column with the Car variable, including the title of
Car. Click onInsert, and thenRecommended Charts. It should show a clustered column and
clickOK. Once the chart is shown, right click on the chart (main area)and selectChange Chart
Type.SelectPieandOK. Click on the pie slices, right clickAdd Data Labels, and selectAdd Data
Callouts. Add an appropriate title.Copy and paste the chart here.
4. Create a histogram for the variable Height. Use the strategies in the text to create a frequency
table of the heights using the categories of 60–64, 65–69, 70–74, and 75–79. It may be helpful to
sort the data based on the Height variable first. Create a new worksheet in Excel by clicking on the +
along the bottom of the screen and type in the categories and the frequency for each category. Then,
select the frequency table, click onInsert, thenRecommended Chartsand choose the column chart
shown and clickOK. Right-click on one of the bars and selectFormat Data Series. In the pop up box,
change theGap Widthto 0. Add an appropriate title and axis label.Copy and paste the graph here.
5. Create a stem and leaf chart for the variable Money, using only the whole dollar amounts. This
must be done by hand, as Excel cannot do this type of chart. Using the tens value as the stem and the
ones value for the leaves, type a stem and leaf plot into the box below. It may be helpful to sort the
data based on the Money variable first.
Calculating Descriptive Statistics
6. Calculate descriptive statistics for the variable Height by Gender. Click onInsertand thenPivot
Table. Click in the top box and select all the data (including labels) from Height through Gender. Also
click on new worksheet and thenOK. On the right of the new sheet, click on Height and Gender,
making sure that Gender is in theRowsbox and Height is in theValuesbox. Click on the down arrow
next to Heightin the Values box and selectValue Field Settings. In the pop up box,
clickAverage,thenOK. Type in the averages below. Then, click on the down arrow next to Height in the
Values box again and select Value Field Settings. In the pop up box, click onStdDevthenOK. Type the
standard deviations below.
Mean Standard Deviation
Females
Males
Ø SelectFile>Save Worksheet Asto save the data set. You must either keep a copy of this data or
download it again off the website for future labs.
Short Answer Writing Assignment
All answers should be complete sentences.
7. What is the most common color of car for students who participated in this survey? Explain how you
arrived at your answer.

4. 8. What is seen in the histogram created for the heights of students in this class (include the shape)?
Explain your answer.
9. What is seen in the stem and leaf plot for the money variable (including the shape)? Explain your
answer.
10. Compare the mean for the heights of males and the mean for the heights of females in these
data. Compare the values and explain what can be concluded based on the numbers.
11. Compare the standard deviation for the heights of males and the standard deviation for the
heights of females in the class.Compare the values and explain what can be concluded based on the
numbers.
DeVry MATH399 Week 4 iLab Latest 2016 November
MATH399 Statistics
Week 4 Lab
Name: _______________________
Statistical Concepts:
· Probability
· Binomial Probability Distribution
Calculating Binomial Probabilities
Ø Open a new Excelworksheet.
1. Open spreadsheet
2. In cell A1 type “success” as the label
3. Under that in column A, type 0 through 10 (these will be in rows 2 through 12)
4. In cell B1, type “one fourth”
5. In cell B2, type “=BINOM.DIST(A2,10,0.25,FALSE)” [NOTE: if you have Excel 2007, then the
formula is BINOMDIST without the period]
6. Then copy and paste this formula in cells B3 through B12
7. In cell C1, type “one half”
8. In cell C2, type “=BINOM.DIST(A2,10,0.5,FALSE)”
9. Copy and paste this formula in cells C3 through C12
10. In cell D1 type “three fourths”
11. In cell D2, type “=BINOM.DIST(A2,10,0.75,FALSE)”
12. Copy and paste this formula in cells D3 through D12
Plotting the Binomial Probabilities
1. Create plots for the three binomial distributions above. You can create the scatter plots in Excel by
selecting the data you want plotted, clicking on INSERT, CHARTS, SCATTER, then selecting the first

5. chart shown which is dots with no connecting lines.Do this two more times and for graph 2 set Y equal
to ‘one half’ and X to ‘success’, and for graph 3 set Y equal to ‘three fourths’ and X to ‘success’. Paste
those three scatter plots in the grey area below. (12 points)
Calculating Descriptive Statistics
Ø You will use the same class survey results that were entered into the Excel worksheet for the Week
2 iLab Assignment for question 2.
2. Calculate descriptive statistics for the variable(Coin) where each of the students flipped a coin 10
times. Round your answers to three decimal places and typethe mean and the standard deviation in
the grey area below. (4 points)
Mean:
Standard deviation:
Short Answer Writing Assignment – Both the calculated binomial probabilities and the descriptive
statistics from the class database will be used to answer the following questions. Round all numeric
answers to three decimal places.
3. List the probability value for each possibility in the binomial experimentcalculated at the beginning
of this lab, which was calculated with the probability of a success being ½. (Complete sentence not
necessary; round your answers to three decimal places) (10 points)
P(x=0) P(x=6)
P(x=1) P(x=7)
P(x=2) P(x=8)
P(x=3) P(x=9)
P(x=4) P(x=10)
P(x=5)
4. Give the probability for the following based on the calculationsin question 3 above, with the
probability of a success being ½. (Complete sentence not necessary; round your answers to three
decimal places) (12 points)
P(x?1) P(x<0)
P(x>1) P(x?4)
P(4<x ?7) P(x<4 or x?7)
5. Calculate (by hand) the mean and standard deviation for the binomial distribution with the
probability of a success being ½and n = 10. Either show work or explain how your answer was
calculated. Use these formulas to do the hand calculations: Mean =np, Standard Deviation = (4
points)
Mean =np:
Standard Deviation =:
6. Using all four of the properties of a Binomial experiment (see page 201 in the textbook) explain in a
short paragraph of several complete sentences why the Coin variable from the class survey represents
a binomial distribution from a binomial experiment. (4 points)
7. Compare the mean and standard deviation for the Coin variable (question 2) with those of the
mean and standard deviation for the binomial distribution that was calculated by hand in question
5. Explain how they are related in a short paragraph of several complete sentences. (4 points)
Mean from question #2:
Standard deviation from question #2:
Mean from question #5:
Standard deviation from question #5:

6. Comparison and explanation:
DeVry MATH399 Week 6 iLab Latest 2016 November
MATH 399N Statistics for Decision Making
Week 6 iLab
Name:_______________________
Statistical Concepts:
· Data Simulation
· Confidence Intervals
· Normal Probabilities
Short Answer Writing Assignment
All answers should be complete sentences.
We need to find the confidence interval for the SLEEP variable. To do this, we need to find the mean
and then find the maximum error. Then we can use a calculator to find the interval, (x – E, x + E).
First, find the mean. Under that column, in cell E37, type=AVERAGE(E2:E36). Under that in cell E38,
type=STDEV(E2:E36). Now we can find the maximum error of the confidence interval. To find the
maximum error, we use the “confidence” formula. In cell E39,
type=CONFIDENCE.NORM(0.05,E38,35). The 0.05 is based on the confidence level of 95%, the
E38 is the standard deviation, and 35 is the number in our sample. You then need to calculate the
confidence interval by using a calculator to subtract the maximum error from the mean (x-E) and add
it to the mean (x+E).
1. Give and interpret the 95% confidence interval for the hours of sleep a student gets. (5 points)
Then, you can go down to cell E40 and type=CONFIDENCE.NORM(0.01,E38,35)to find the
maximum error for a 99% confidence interval. Again, you would need to use a calculator to subtract
this and add this to the mean to find the actual confidence interval.
2. Give and interpret the 99% confidence interval for the hours of sleep a student gets. (5 points)
3. Compare the 95% and 99% confidence intervals for the hours of sleep a student gets. Explain the
difference between these intervals and why this difference occurs. (10 points)
4. Find the mean and standard deviation of the DRIVE variable by
using=AVERAGE(A2:A36)and=STDEV(A2:A36). Assuming that this variable is normally
distributed, what percentage of data would you predict would be less than 40 miles? This would be
based on the calculated probability. Use the formula=NORM.DIST(40, mean, stdev,TRUE). Now
determine the percentage of data points in the dataset that fall within this range. To find the actual
percentage in the dataset, sort the DRIVE variable and count how many of the data points are less
than 40 out of the total 35 data points. That is the actual percentage. How does this compare with
your prediction? (15 points)
Mean ______________ Standard deviation ____________________
Predicted percentage ______________________________
Actual percentage _____________________________
Comparison ___________________________________________________
______________________________________________________________
5. What percentage of data would you predict would be between 40 and 70 and what percentage
would you predict would be more than 70 miles? Subtract the probabilities found
through=NORM.DIST(70, mean, stdev, TRUE)and=NORM.DIST(40, mean, stdev, TRUE)for the

7. “between” probability. To get the probability of over 70, use the same=NORM.DIST(70, mean,
stdev, TRUE)and then subtract the result from 1 to get “more than”. Now determine the percentage
of data points in the dataset that fall within this range, using same strategy as above for counting
data points in the data set. How do each of these compare with your prediction and why is there a
difference? (15 points)
Predicted percentage between 40 and 70 ______________________________
Actual percentage _____________________________________________
Predicted percentage more than 70 miles ________________________________
Actual percentage ___________________________________________
Comparison ____________________________________________________
_______________________________________________________________
Why? __________________________________________________________
________________________________________________________________
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