##
MATH
533COMPLETE COURSE MATH533 COMPLETE COURSE

**Click below link for Answers**

**MATH 533 PROJECT PART A Exploratory Data Analysis**

**AJ DAVIS is a department store chain, which has many credit customers and wants to find out**more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables:

LOCATION (Rural, Urban, Suburban) INCOME (in $1,000′s – be
careful with this) SIZE (Household Size, meaning number of people living in the
household) YEARS (the number of years that the customer has lived in the current
location) CREDIT BALANCE (the customers current credit card balance on the
store’s credit card, in $).

The data appears below, and is available in Doc Sharing Course
Project Data Set as an EXCEL file:LOCATION INCOME($1000) SIZE YEARS CREDIT
BALANCE($) Urban 54 3 12 4016 Rural 30 2 12 3159 Suburban 32 4 17 5100 Suburban
50 5 14 4742 Rural 31 2 4 1864 Urban 55 2 9 4070 Rural 37 1 20 2731 Urban 40 2
7 3348 Suburban 66 4 10 4764 Urban 51 3 16 4110 Urban 25 3 11 4208 Urban 48 4
16 4219 Rural 27 1 19 2477 Rural 33 2 12 2514 Urban 65 3 12 4214 Suburban 63 4
13 4965 Urban 42 6 15 4412 Urban 21 2 18 2448 Rural 44 1 7 2995 Urban 37 5 5
4171 Suburban 62 6 13 5678 Urban 21 3 16 3623 Suburban 55 7 15 5301 Rural 42 2
19 3020 Urban 41 7 18 4828 Suburban 54 6 14 5573 Rural 30 1 14 2583 Rural 48 2
8 3866 Urban 34 5 5 3586 Suburban 67 4 13 5037 Rural 50 2 11 3605 Urban 67 5 1
5345 Urban 55 6 16 5370 Urban 52 2 11 3890 Urban 62 3 2 4705 Urban 64 2 6 4157
Suburban 22 3 18 3579 Urban 29 4 4 3890 Suburban 39 2 18 2972 Rural 35 1 11
3121 Urban 39 4 15 4183 Suburban 54 3 9 3730 Suburban 23 6 18 4127 Rural 27 2 1
2921 Urban 26 7 17 4603 Suburban 61 2 14 4273 Rural 30 2 14 3067 Rural 22 4 16
3074 Suburban 46 5 13 4820 Suburban 66 4 20 5149 Open the file MATH533 Project
Consumer.xls from the Course Project Data Set folder in Doc Sharing.

**PROJECT PART A: Exploratory Data Analysis**

For each of the five variables,
process, organize, present and summarize the data. Analyze each variable by
itself using graphical and numerical techniques of summarization. Use MINITAB
as much as possible, explaining what the printout tells you. You may wish to
use some of the following graphs: stem-leaf diagram, frequency/relative
frequency table, histogram, boxplot, dotplot, pie chart, bar graph. Caution:
not all of these are appropriate for each of these variables, nor are they all
necessary. More is not necessarily better. In addition be sure to find the
appropriate measures of central tendency, and measures of dispersion for the
above data. Where appropriate use the five number summary (the Min, Q1, Median,
Q3, Max). Once again, use MINITAB as appropriate, and explain what the results
mean. Analyze the connections or relationships between the variables. There are
ten pairings here (Location and Income, Location and Size, Location and Years,
Location and Credit Balance, income and Size, Income and Years, Income and
Balance, Size and Years, Size and Credit Balance, Years and Credit Balance).
Use graphical as well as numerical summary measures. Explain what you see. Be
sure to consider all 10 pairings. Some variables show clear relationships,
while others do not. Prepare your report in Microsoft Word (or some other word
processing package),

**integrating your graphs and tables with text explanations and interpretations.**Be sure that you have graphical and numerical back up for your explanations and interpretations. Be selective in what you include in the report. I’m not looking for a 20 page report on every variable and every possible relationship (that’s 15 things to do). Rather what I want you do is to highlight what you see for**three individual variables**(no more than 1 graph for each, one or two measures of central tendency and variability (as appropriate), and two or three sentences of interpretation). For the 10 pairings, identify and report only on**three of the pairings**, again using graphical and numerical summary (as appropriate), with interpretations.**Please note that at least one of your pairings must include Location and at least one of your pairings must not include Location**. All DeVry University policies are in effect, including the plagiarism policy. Project Part A report is due by the end of Week 2. Project Part A is worth 100 total points. See grading rubric below.**Submission: The report from part 4 including all relevant graphs and numerical analysis along with interpretations.**

**Format for report:**

Brief Introduction

Discuss your 1st individual variable, using graphical, numerical summary and interpretation

Discuss your 2nd individual variable, using graphical, numerical summary and interpretation

Discuss your 3rd individual variable, using graphical, numerical summary and interpretation

Discuss your 1st pairing of variables, using graphical, numerical summary and interpretation

Discuss your 2nd pairing of variables, using graphical, numerical summary and interpretation

Discuss your 3rd pairing of variables, using graphical, numerical summary and interpretation

Conclusion

##
MATH 533 Project Part B Hypothesis Testing and Confidence
Intervals

Your manager has speculated the
following:

the average (mean) annual income was less than $50,000, the true
population proportion of customers who live in an urban area exceeds 40%, the
average (mean) number of years lived in the current home is less than 13 years,
the average (mean) credit balance for suburban customers is more than $4300.
Using the sample data, perform the hypothesis test for each of the above
situations in order to see if there is evidence to support your manager’s
belief in each case a.-d. In each case use the Seven Elements of a Test of
Hypothesis, in Section 6.2 of your text book with Î± = .05, and explain your
conclusion in simple terms. Also be sure to compute the p-value and interpret.
Follow this up with computing 95% confidence intervals for each of the
variables described in a.-d., and again interpreting these intervals. Write a
report to your manager about the results, distilling down the results in a way
that would be understandable to someone who does not know statistics. Clear
explanations and interpretations are critical. All DeVry University policies
are in effect, including the plagiarism policy. Project Part B report is due by
the end of Week 6. Project Part B is worth 100 total points. See grading rubric
below.

**Submission: The report from part 3 + all of the relevant work done in the hypothesis testing (including Minitab) in 1., and the confidence intervals (Minitab) in 2 as an appendix.**

**Format for report:**

Summary Report (about 1 paragraph on each of the speculations
a.-d.) Appendix with all of the steps in hypothesis testing (the format of the
Seven Elements of a Test of Hypothesis, in Section 6.2 of your text book) for
each speculation a.-d.as well as the confidence intervals, and including all
Minitab output

##
MATH 533 Project Part C Regression and Correlation Analysis

Using MINITAB perform the
regression and correlation analysis for the data on CREDIT BALANCE (Y) and SIZE
(X) by answering the following.

Generate a scatterplot for CREDIT BALANCE vs. SIZE, including
the graph of the “best fit” line. Interpret. Determine the equation of the
“best fit” line, which describes the relationship between CREDIT BALANCE and
SIZE. Determine the coefficient of correlation. Interpret. Determine the
coefficient of determination. Interpret. Test the utility of this regression
model (use a two tail test with Î± =.05). Interpret your results, including the
p-value. Based on your findings in 1-5, what is your opinion about using SIZE
to predict CREDIT BALANCE? Explain. Compute the 95% confidence interval for .
Interpret this interval. Using an interval, estimate the average credit balance
for customers that have household size of 5. Interpret this interval. Using an
interval, predict the credit balance for a customer that has a household size
of 5. Interpret this interval. What can we say about the credit balance for a
customer that has a household size of 10? Explain your answer.

In an attempt to improve the model, we attempt to do a multiple
regression model predicting CREDIT BALANCE based on INCOME, SIZE and YEARS.

Using MINITAB run the multiple regression analysis using the
variables INCOME, SIZE and YEARS to predict CREDIT BALANCE. State the equation
for this multiple regression model. Perform the Global Test for Utility
(F-Test). Explain your conclusion. Perform the t-test on each independent
variable. Explain your conclusions and clearly state how you should proceed. In
particular, which independent variables should we keep and which should be
discarded. Is this multiple regression model better than the linear model that
we generated in parts 1-10? Explain. All DeVry University policies are in
effect, including the plagiarism policy. Project Part C report is due by the
end of Week 7. Project Part C is worth 100 total points. See grading rubric
below.

**Summarize your results from 1-14 in a report that is three pages or less in length and explains and interprets the results in ways that are understandable to someone who does not know statistics.**

**Submission: The summary report + all of the work done in 1-14 (Minitab Output + interpretations) as an appendix.**

**Format:**

Summary Report Points 1-14 addressed with appropriate output,
graphs and interpretations. Be sure to number each point 1-14

##
MATH 533 DeVry (Applied Managerial Statistics) Course Project;
AJ Davis Department

**AJ DAVIS is a department store chain, which has many credit customers and wants to find out**more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables:

LOCATION (Rural, Urban, Suburban) INCOME (in $1,000′s – be
careful with this) SIZE (Household Size, meaning number of people living in the
household) YEARS (the number of years that the customer has lived in the
current location) CREDIT BALANCE (the customers current credit card balance on
the store’s credit card, in $).

The data appears below, and is available in Doc Sharing Course
Project Data Set as an EXCEL file:LOCATION INCOME($1000) SIZE YEARS CREDIT
BALANCE($) Urban 54 3 12 4016 Rural 30 2 12 3159 Suburban 32 4 17 5100 Suburban
50 5 14 4742 Rural 31 2 4 1864 Urban 55 2 9 4070 Rural 37 1 20 2731 Urban 40 2
7 3348 Suburban 66 4 10 4764 Urban 51 3 16 4110 Urban 25 3 11 4208 Urban 48 4
16 4219 Rural 27 1 19 2477 Rural 33 2 12 2514 Urban 65 3 12 4214 Suburban 63 4
13 4965 Urban 42 6 15 4412 Urban 21 2 18 2448 Rural 44 1 7 2995 Urban 37 5 5
4171 Suburban 62 6 13 5678 Urban 21 3 16 3623 Suburban 55 7 15 5301 Rural 42 2
19 3020 Urban 41 7 18 4828 Suburban 54 6 14 5573 Rural 30 1 14 2583 Rural 48 2
8 3866 Urban 34 5 5 3586 Suburban 67 4 13 5037 Rural 50 2 11 3605 Urban 67 5 1
5345 Urban 55 6 16 5370 Urban 52 2 11 3890 Urban 62 3 2 4705 Urban 64 2 6 4157
Suburban 22 3 18 3579 Urban 29 4 4 3890 Suburban 39 2 18 2972 Rural 35 1 11
3121 Urban 39 4 15 4183 Suburban 54 3 9 3730 Suburban 23 6 18 4127 Rural 27 2 1
2921 Urban 26 7 17 4603 Suburban 61 2 14 4273 Rural 30 2 14 3067 Rural 22 4 16
3074 Suburban 46 5 13 4820 Suburban 66 4 20 5149 Open the file MATH533 Project
Consumer.xls from the Course Project Data Set folder in Doc Sharing.

**PROJECT PART A: Exploratory Data Analysis**

For each of the five variables,
process, organize, present and summarize the data. Analyze each variable by
itself using graphical and numerical techniques of summarization. Use MINITAB
as much as possible, explaining what the printout tells you. You may wish to
use some of the following graphs: stem-leaf diagram, frequency/relative
frequency table, histogram, boxplot, dotplot, pie chart, bar graph. Caution:
not all of these are appropriate for each of these variables, nor are they all
necessary. More is not necessarily better. In addition be sure to find the
appropriate measures of central tendency, and measures of dispersion for the
above data. Where appropriate use the five number summary (the Min, Q1, Median,
Q3, Max). Once again, use MINITAB as appropriate, and explain what the results
mean. Analyze the connections or relationships between the variables. There are
ten pairings here (Location and Income, Location and Size, Location and Years,
Location and Credit Balance, income and Size, Income and Years, Income and
Balance, Size and Years, Size and Credit Balance, Years and Credit Balance).
Use graphical as well as numerical summary measures. Explain what you see. Be
sure to consider all 10 pairings. Some variables show clear relationships,
while others do not. Prepare your report in Microsoft Word (or some other word
processing package),

**integrating your graphs and tables with text explanations and interpretations.**Be sure that you have graphical and numerical back up for your explanations and interpretations. Be selective in what you include in the report. I’m not looking for a 20 page report on every variable and every possible relationship (that’s 15 things to do). Rather what I want you do is to highlight what you see for**three individual variables**(no more than 1 graph for each, one or two measures of central tendency and variability (as appropriate), and two or three sentences of interpretation). For the 10 pairings, identify and report only on**three of the pairings**, again using graphical and numerical summary (as appropriate), with interpretations.**Please note that at least one of your pairings must include Location and at least one of your pairings must not include Location**. All DeVry University policies are in effect, including the plagiarism policy. Project Part A report is due by the end of Week 2. Project Part A is worth 100 total points. See grading rubric below.**Format for report:**

Brief Introduction

Discuss your 1st individual variable, using graphical, numerical summary and interpretation

Discuss your 2nd individual variable, using graphical, numerical summary and interpretation

Discuss your 3rd individual variable, using graphical, numerical summary and interpretation

Discuss your 1st pairing of variables, using graphical, numerical summary and interpretation

Discuss your 2nd pairing of variables, using graphical, numerical summary and interpretation

Discuss your 3rd pairing of variables, using graphical, numerical summary and interpretation

Conclusion

**MATH 533 (GM 533 DeVry Applied Managerial Statistics) Course Project; AJ Davis Department Stores (PART B)**

**Project Part B: Hypothesis Testing and Confidence Intervals**

Your manager has speculated the following:

the average (mean) annual income was less than $50,000, the true
population proportion of customers who live in an urban area exceeds 40%, the
average (mean) number of years lived in the current home is less than 13 years,
the average (mean) credit balance for suburban customers is more than $4300.
Using the sample data, perform the hypothesis test for each of the above
situations in order to see if there is evidence to support your manager’s
belief in each case a.-d. In each case use the Seven Elements of a Test of
Hypothesis, in Section 6.2 of your text book with Î± = .05, and explain your
conclusion in simple terms. Also be sure to compute the p-value and interpret.
Follow this up with computing 95% confidence intervals for each of the
variables described in a.-d., and again interpreting these intervals. Write a
report to your manager about the results, distilling down the results in a way
that would be understandable to someone who does not know statistics. Clear
explanations and interpretations are critical. All DeVry University policies
are in effect, including the plagiarism policy. Project Part B report is due by
the end of Week 6. Project Part B is worth 100 total points. See grading rubric
below.

**Format for report:**

Summary Report (about 1 paragraph on each of the speculations
a.-d.) Appendix with all of the steps in hypothesis testing (the format of the
Seven Elements of a Test of Hypothesis, in Section 6.2 of your text book) for
each speculation a.-d.as well as the confidence intervals, and including all
Minitab output

**Project Part C: Regression and Correlation Analysis**

Using MINITAB perform the regression and correlation analysis
for the data on CREDIT BALANCE (Y) and SIZE (X) by answering the following.

Generate a scatterplot for CREDIT BALANCE vs. SIZE, including
the graph of the “best fit” line. Interpret. Determine the equation of the
“best fit” line, which describes the relationship between CREDIT BALANCE and
SIZE. Determine the coefficient of correlation. Interpret. Determine the
coefficient of determination. Interpret. Test the utility of this regression
model (use a two tail test with Î± =.05). Interpret your results, including the
p-value. Based on your findings in 1-5, what is your opinion about using SIZE
to predict CREDIT BALANCE? Explain. Compute the 95% confidence interval for .
Interpret this interval. Using an interval, estimate the average credit balance
for customers that have household size of 5. Interpret this interval. Using an
interval, predict the credit balance for a customer that has a household size
of 5. Interpret this interval. What can we say about the credit balance for a
customer that has a household size of 10? Explain your answer.

In an attempt to improve the model, we attempt to do a multiple
regression model predicting CREDIT BALANCE based on INCOME, SIZE and YEARS.

Using MINITAB run the multiple regression analysis using the
variables INCOME, SIZE and YEARS to predict CREDIT BALANCE. State the equation
for this multiple regression model. Perform the Global Test for Utility
(F-Test). Explain your conclusion. Perform the t-test on each independent
variable. Explain your conclusions and clearly state how you should proceed. In
particular, which independent variables should we keep and which should be
discarded. Is this multiple regression model better than the linear model that
we generated in parts 1-10? Explain. All DeVry University policies are in
effect, including the plagiarism policy. Project Part C report is due by the
end of Week 7. Project Part C is worth 100 total points. See grading rubric
below.

**Summarize your results from 1-14 in a report that is three pages or less in length and explains and interprets the results in ways that are understandable to someone who does not know statistics.**

**Submission: The summary report + all of the work done in 1-14 (Minitab Output + interpretations) as an appendix.**

**Format:**

Summary Report Points 1-14 addressed with appropriate output,
graphs and interpretations. Be sure to number each point 1-14.

##
MATH 533 Final Exam Set 1

1. (TCO A) The number of service
calls made in the past 60 days by a sample of 20 technical representatives for
AJ TECH is given below.

a. Compute the mean, median, mode, and standard deviation, Q1,
Q3, Min, and Max for the above sample data on number of service calls made in
the past 60 days.

b. In the context of this situation, interpret the Median, Q1,
and Q3. (Points : 33)

2. (TCO B) Consider the following data on customers at an office
supply store. These customers are categorized by their previous volume
purchases and their age.

If you choose one customer at random, then find the probability
that the customer

a. is a new customer.

b. is a high volume customer and is in the 40′s

c. is in the 20′s, given that the customer is low volume

3. (TCO B) DCW Chemical is planning to implement an acceptance
sampling plan for raw materials. A random sample of 22 batches from a large
shipment (having a large number of batches) is selected. If two or more of the
22 batches fail to meet specifications, then the entire shipment is returned.
Otherwise, the shipment is accepted.

In a sample of 22 batches from a population that is 1% defective
(1% of the batches fail to meet specifications), find the probability that

a. two or more batches fail to meet specifications.

b. exactly two batches fail to meet specifications.

c. fewer than two batches fail to meet specifications.

4. (TCO B) CJ Computer Disks stocks and sells recordable CDs.
The monthly demand for these CDs is closely approximated by a normal
distribution with a mean of 20,000 disks and standard deviation of 4,000 disks.
CJ receives shipments from the supplier once per month (at the beginning of
each month).

a. Find the probability that the demand for recordable CDs
exceeds 30,000 for a particular month.

b. Find the probability that the demand for recordable CDs is
between 12,000 and 18,000.

c. How large an inventory must CJ have available at the
beginning of the month so that the probability of running out of recordable CDs
(a stock out) during the month is no more than .05?

5. (TCO C) A tool manufacturing company wants to estimate the
mean number of bolts produced per hour by a specific machine. A simple random
sample of 9 hours of performance by this machine is selected and the number of
bolts produced each hour is noted. This leads to the following results.

Sample Size = 9

Sample Mean = 62.3 bolts/hr

Sample Standard Deviation = 6.3 bolts/hr

a. Compute the 90% confidence interval for the average number
bolts produced per hour.

b. Interpret this interval

c. How many hours of performance by this machine should be
selected in order to be 90% confident of being within 1 bolt/hr of the
population mean number of bolts per hour by this specific machine?

6. (TCO C) A clock company is concerned about errors in assembly
of their custom made clocks. A random sample of 120 clocks from today’s
production yields nine clocks with assembly errors.

a. Compute the 95% confidence interval for the percentage of
clocks with assembly errors in today’s production

b. Interpret this confidence interval

c. How many clocks should be selected in order to be 95%
confident of being within 2% of the population percentage of clocks with
assembly errors in today’s production?

7. (TCO D) An article about women in business claims that 28% of
all small businesses in the United States are owned by women. Sally Parks
believes that this figure is overstated. A random sample of 2,000 small
businesses is selected with 546 being owned by women. Does the sample data
provide evidence to conclude that less than 28% of small businesses in the United
States are owned by women (with a = .10)? Use the hypothesis testing procedure
outlined below.

a. Formulate the null and alternative hypotheses

b. State the level of significance

c. Find the critical value (or values), and clearly show the
rejection and nonrejection regions

d. Compute the test statistic

e. Decide whether you can reject Ho and accept Ha or not.

f. Explain and interpret your conclusion in part e. What does
this mean?

g. Determine the observed p-value for the hypothesis test and
interpret this value. What does this mean?

h. Does the sample data provide evidence to conclude that less
than 28% of small businesses in the United States are owned by women (with a =
.10)?

8. (TCO D) Bill Smith is the Worthington Township manager. When
citizens request a traffic light, the staff assesses the traffic flow at the
requested intersection. Township policy requires the installation of a traffic
light when an intersection averages more than 150 vehicles per hour. A random
sample of 48 vehicle counts is done. The results are as follows:

Sample Size = 48

Sample Mean = 158.3 vehicles/hr.

Sample Standard Deviation = 27.6 vehicles/hr.

Does the sample data provide evidence to conclude that the
installation of the traffic light is warranted (using a = .10)? Use the
hypothesis testing procedure outlined below.

a. Formulate the null and alternative hypotheses

b. State the level of significance

c. Find the critical value (or values), and clearly show the
rejection and nonrejection regions

d. Compute the test statistic

e. Decide whether you can reject Ho and accept Ha or not

f. Explain and interpret your conclusion in part e. What does
this mean?

g. Find the observed p-value for the hypothesis test and
interpret this value. What does this mean?

h. Does this sample data provide evidence (with a = 0.10), that
the installation of the traffic light is warranted?

##
MATH 533 Final Exam (Set 2)

**1.**

**(TCO A)Seventeen salespeople reported the following number of sales calls completed last month**

a. Compute the

**mean**,**median**,**mode**, and**standard deviation, Q**for the above sample data on number of sales calls per month_{1}, Q_{3}, Min, and Max
b. In the context of this
situation, interpret the Median, Q

_{1}, and Q_{3}**2.**

**(TCO B) Cedar Home Furnishings has collected data on their customers in terms of whether they reside in an urban location or a suburban location, as well as rating the customers as either “good,” “borderline,” or “poor.” The data is below.**

If you choose a customer at random, then find the probability
that the customer

a. is considered “borderline.”

b. is considered “good” and resides in an urban location

c. is suburban, given that customer is considered “poor.”

**3.**

**(TCO B)Historically, 70% of your customers at Rodale Emporium pay for their purchases using credit cards. In a sample of 20 customers, find the probability that**

a. exactly 14 customers will pay for their purchases using
credit cards

b. at least 10 customers will pay for their purchases using
credit cards

c. at most 12 customers will pay for their purchases using
credit cards

**4.**

**(TCO B) The demand for gasoline at a local service station is normally distributed with a mean of 27,009 gallons per day and a standard deviation of 4,530 gallons per day.**

a. Find the probability that the demand for gasoline exceeds
22,000 gallons for a given day

b. Find the probability that the demand for gasoline falls
between 20,000 and 23,000 gallons for a given day

c. How many gallons of gasoline should be on hand at the
beginning of each day so that we can meet the demand 90% of the time (i.e., the
station stands a 10% chance of running out of gasoline for that day)?

**5.**

**(TCO C) An operations analyst from an airline company has been asked to develop a fairly accurate estimate of**

the mean refueling and baggage handling time at a foreign
airport. A random sample of 36 refueling and baggage handling times yields the
following results.

Sample Size = 36

Sample Mean = 24.2 minutes

Sample Standard Deviation = 4.2 minutes

Sample Mean = 24.2 minutes

Sample Standard Deviation = 4.2 minutes

a. Compute the 90% confidence interval for the population mean
refueling and baggage time

b. Interpret this interval

c. How many refueling and baggage handling times should be
sampled so that we may construct a 90% confidence interval with a sampling
error of .5 minutes for the population mean refueling and baggage time?

**6.**

**(TCO C) The manufacturer of a certain brand of toothpaste claims that a high percentage of dentists recommend the use of their toothpaste. A random sample of 400 dentists results in 310 recommending their toothpaste.**

a. Compute the 99% confidence interval for the population
proportion of dentists who recommend the use of this toothpaste.

b. Interpret this confidence interval

c. How large a sample size will need to be selected if we wish
to have a 99% confidence interval that is accurate to within 3%?

**7.**

**(TCO D) A Ford Motor Company quality improvement team believes that its recently implemented defect reduction program has reduced the proportion of paint defects. Prior to the implementation of the program, the proportion of paint defects was .03 and had been stationary for the past 6 months. Ford selects a random sample of 2,000 cars built after the implementation of the defect reduction program. There were 45 cars with paint defects in that sample. Does the sample data provide evidence to conclude that the proportion of paint defects is now less than .03 (with a = .01)? Use the hypothesis testing procedure outlined below.**

a. Formulate the null and alternative hypotheses

b. State the level of significance

c. Find the critical value (or values), and clearly show the
rejection and non-rejection regions

d. Compute the test statistic

e. Decide whether you can reject Ho and accept Ha or not

f. Explain and interpret your conclusion in part e. What does
this mean?

g. Determine the observed p-value for the hypothesis test and
interpret this value. What does this mean?

h. Does the sample data provide evidence to conclude that the
proportion of paint defects is now less than .03 (with a = .01)?

**8.**

**(TCO D) A new car dealer calculates that the dealership must average more than 4.5% profit on sales of new cars. A random sample of 81 cars gives the following result.**

Sample Size = 81

Sample Mean = 4.97%

Sample Standard Deviation = 1.8%

Sample Mean = 4.97%

Sample Standard Deviation = 1.8%

Does the sample data provide evidence to conclude that the
dealership averages more than 4.5% profit on sales of new cars (using a = .10)? Use the hypothesis testing procedure outlined below.

a. Formulate the null and alternative hypotheses

b. State the level of significance

c. Find the critical value (or values), and clearly show the
rejection and nonrejection regions

d. Compute the test statistic

e. Decide whether you can reject Ho and accept Ha or not

f. Explain and interpret your conclusion in part e. What does
this mean?

g. Determine the observed p-value for the hypothesis test and
interpret this value. What does this mean?

h. Does the sample data provide evidence to conclude that the
dealership averages more than 4.5% profit on sales of new cars (using a = .10)?

**9.**

**(TCO E) Bill McFarland is a real estate broker who specializes in selling farmland in a large western state. Because Bill advises many of his clients about pricing their land, he is interested in developing a pricing formula of some type. He feels he could increase his business significantly if he could accurately determine the value of a farmer’s land. A geologist tells Bill that the soil and rock characteristics in most of the area that Bill sells do not vary much. Thus the price of land should depend greatly on acreage. Bill selects a sample of 30 plots recently sold. The data is found below (in Minitab),**

**where X=Acreage and Y=Price ($1,000s)**.

a. Analyze the above output to determine the regression equation

b. Find and interpret in the context of this problem.

c. Find and interpret the coefficient of determination
(r-squared).

d. Find and interpret coefficient of correlation

e. Does the data provide significant evidence (a = .05) that the acreage can be used to predict the price? Test
the utility of this model using a two-tailed test. Find the observed p-value
and interpret

f. Find the 95% confidence interval for mean price of plots of
farmland that are 50 acres. Interpret this interval

g. Find the 95% prediction interval for the price of a single
plot of farmland that is 50 acres. Interpret this interval

h. What can we say about the price for a plot of farmland that
is 250 acres?

**10.**

**(TCO E)An insurance firm wishes to study the relationship between driving experience (X1, in years), number of driving violations in the past three years (X2), and current monthly auto insurance premium (Y). A sample of 12 insured drivers is selected at random. The data is given below (in MINITAB):**

a. Analyze the above output to determine the multiple regression
equation

b. Find and interpret the multiple index of determination
(R-Sq).

c. Perform the

**t-tests**on and on (use two tailed test with (a = .05). Interpret your results
d. Predict the monthly premium for an individual having 8 years
of driving experience and 1 driving violation during the past 3 years. Use both
a point estimate and the appropriate interval estimate

##
MATH 533 Week 8 Final Exam SET 3

1. (TCO A)Consider the following
raw data, which is the result of selecting a random sample of 20 Bank Common
Stocks and noting the dividend yields (as a %).

2. (TCO B) The general manager of Oak Place Mall has collected
data on where each customer lives and the gender of each customer. A random
sample of 500 customers was selected with the results below.

3. (TCO B)In a recent survey, 80% of the citizenry in a
community favored the building of a municipal golf course. If you ask 15
citizens about this project, find the probability that

4. (TCO B) A study of homeowners in the 5th congressional
district in Maryland found that their annual household incomes are normally
distributed with a mean of $41,182 and a standard deviation of $11,990 (based
on data from Nielsen Media Research).

5. (TCO C) Until this year, the mean braking distance of a
Nikton automobile moving at 60 mi per hour was 175 ft. Nikton engineers have
developed what they consider a better braking system. They test the new brake
system on a random sample of 81 cars and determine the sample mean braking
distance. The results are the following

6. (TCO C) You are in charge of selling advertising for radio
station WQAA. The fee you can set for airtime is directly related to the share
of the listening market your station reaches. From time to time, you conduct
surveys to determine WQAA’s share of the market. This month, when you contacted
200 randomly selected residential phone numbers, 12 respondents said they
listen to WQAA

7. (TCO D) Persons living near a smelting plant have complained
that the plant violates the city’s noise pollution code. The code states that
to be in compliance, noise levels are only allowed to exceed 120 decibels less
than 10% of the time. You monitor the noise levels at 150 randomly selected
times and found that 11 were above 120 decibels. Does the sample data provide
evidence to conclude that the plant is in compliance with the noise pollution
code (witha = .05)? Use the hypothesis testing procedure outlined below.

8. (TCO D)Bill Smith is the Worthington Township manager. When
citizens request a traffic light, the staff assesses the traffic flow at the
requested intersection. Township policy requires the installation of a traffic
light when an intersection averages more than 150 vehicles per hour. A random
sample of 48 vehicle counts is done. The results are as follows:

(TCO E) Management at New England Life wants to establish the
relationship between the number of sales calls made each week (CALLS, X) and
the number of sales made each week (SALES, Y). A random sample of 18 life
insurance salespeople were surveyed yielding the data found below

(TCO E) A local realtor wishes to study the relationship between
selling price (PRICE in $), house size (HOUSESIZE in square feet), lot size
(LOTSIZE in acres), and number of bathrooms (BATHROOM). A sample of 10 homes is
selected at random. The data is given below (in MINITAB)

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MATH 533 All 7 Weeks Discussions

Week 1 DQ -

**Descriptive Stats: ETHICS and Workplace Applications**
Week 2 DQ -

**Case: Let’s Make a Deal**
Week 3 DQ –

**Workplace Applications of the Normal Distribution and Sampling Distributions**
Week 4 DQ -

**Case: Statistics in Action: Medicare Fraud Investigations**
Week 5 DQ -

**Case: Statistics in Action: Diary of a Kleenex User**
Week 6 DQ -

**Case: Statistics in Action: Legal Advertising—Does It Pay?**
Week 7 DQ -

**Case: Statistics in Action: Bid-Rigging in the Highway Construction Industry**##
MATH 533 Entire Course + Final Exam ( 2 sets )

MATH 533 All 7 Weeks Discussions

MATH 533 Final Exam (2 sets )

MATH 533 Course Project

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MATH 533 COMPLETE COURSE
MATH533 COMPLETE COURSE

**Click below link for Answers**