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BUS
308 WEEK 1 DQ 1 DATA SCALES (NEW)
Week 1
Data Scales.
A marketing agency is interested
in the buying habits of those who shop online versus those who shop in person.
In your discussion post, address each of the following and explain your
reasoning as to why you picked the specific scale:
a. A database is created
and shoppers are classified as online or in-person shoppers. Such
classifications represent data of which scale? Explain your reasoning.
b. Online and in-person
shoppers are to be compared on their relative incomes. Income data represent
data of which scale? Explain your reasoning.
c. If shoppers are also
ranked from the most to the least frequent shoppers, those rankings represent
data of which scale? Explain your reasoning.
d. Shoppers are asked to
complete a customer satisfaction survey. In response to each question on the
survey, the shoppers circle one of five answers: strongly agree, agree,
neutral, disagree, or strongly disagree. Their responses are data of which
scale? Explain your reasoning.
e. What measure(s) of
central tendency will be most informative for each of the above data? Justify
why each measure is most informative.
f. What would be more
critical for the marketing agency to utilize; descriptive or inferential
statistics? Why?
BUS 308 WEEK 1 DQ 2 PROBABILITY (NEW)
Probability.
The manager of a sandwich shop
gathers data on what people spend on lunch on a particular day of the week.
The results are $4.20, $4.22,
$2.35, $4.32, $5.25, $6.48, $6.78, $8.59, $6.95, $5.52, $6.83, $7.35, $4.36,
$9.39, $6.42.
To the degree that this represents
the population of all those who eat lunch at sandwich shops, what percentage of
customers spend:
a. less than $4.34?
b. between $3.50 and $4.80?
c. less than $2.35?
Imagine that you are the manager of
a sandwich shop. Based on your calculations, what do you think is the best pricing
point for your shop? What would you do to increase sales at the sandwich shop?
For additional information on
calculating probability refer to the Week One Recommended Resources.
BUS 308 WEEK 1 QUIZ (NEW)
1. Question
: Data on
the city from which members of a board of directors come represent interval
data.
2. Question
: Inferential
statistics infer the characteristics of samples.
3. Question
: The mode
is which of the following?
4. Question
: The
standard error of the mean can be calculated by dividing μ by the square root
of the number of values in the distribution.
5. Question
: If a
certifying agency raises the requirements for real estate agents, what sort of
decision error is the agency protecting against?
6. Question
: Which of
the following defines statistical significance?
7. Question
: In a
frequency distribution such as a bell-shaped curve, what does the vertical
height of the curve indicate?
8. Question
: Which of
the following is a provision of the central limit theorem?
9. Question
: In
statistical notation, M is to μ as s is to σ.
10. Question
: Technically,
“statistic” refers to which?
BUS 308 WEEK 1 PROBLEM SET WEEK ONE (NEW)
Problem Set Week One.
Problem 1
The performances of a group of
interns are evaluated by their supervisors at the end of their internships.
Their scores are: 55, 47, 62, 27,
50, 49, 66, 53, 50, 44, 63, 59.
Complete the calculations below
using this data. Show all of your work and clearly label each of
your calculations.
a. the mean
b. the median
c. the range
d. the standard deviation
e. the variance
Problem 2
The Anxiety General Stress Test
(ANGST) has been designed to gauge the level of psychological stress management
trainees experience when they are under pressure.
For a random sample of trainees the
scores are as follows: 47, 49, 53, 53, 54, 58, 61, 64, 75, 81.
Complete the calculations below
using this data. Show all of your work and clearly label each of
your calculations.
a. What is the z score equivalent
of ?
b. What is the probability that
someone selected at random will score 81 or lower?
c. What percentage of all trainees
will score between 60 and 75?
BUS 308 WEEK 2 JOURNAL (NEW)
BUS 308 Week 2 Journal
BUS 308 WEEK 2 DQ 1 T-TESTS (NEW)
t-Tests.
Imagine a shift manager at a
manufacturing plant is gathering data on the number of units workers assemble
during two different shifts over 10 different days. If the number of units
assembled by each shift varies greatly from day to day, what impact will that
have on the likelihood of a significant difference between the two shifts?
Explain and support your response.
BUS 308 WEEK 2 DQ 2 ANOVA TESTING (NEW)
ANOVA Testing.
The manager of an agency
providing temporary employees to city offices is analyzing the number of days
temporary hires typically work in various types of industries.
The data are as follows:
Legal clerical: 2, 1, 4,
4, 2, 5, 6
Accounting firms: 3, 6, 4,
5, 5, 7, 8
Insurance: 5, 4, 7, 9,
9, 8, 11
Using the data above,
answer the following questions:
a. Are there significant
differences in the length of time temporary employee’s work in the different
industries?
b. How much of the
differences can be explained by the industry?
c. Which groups are
significantly different from others?
d. Why would a manager
be focused on measuring the number of days that a temporary works each week?
BUS 308 WEEK 2 QUIZ (NEW)
1. Question
: How is
the sum of squares unlike either the standard deviation or the variance?
2. Question
: If sums
of squares statistics are calculated for shoppers at three different retail
outlets, what statistic will indicate the variability among those at each
outlet?
3. Question
: Which is
the symbol used for the test statistic in ANOVA?
4. Question
: If ANOVA
reveals that four different departments have significantly different levels of
productivity, what will a post-hoc test indicate?
5. Question
: The
independent t-test is based on which distribution?
6. Question
: What does
omega-squared indicate?
7. Question
: Each
different t-distribution is defined by which of the following?
8. Question
: When a
significant interaction is graphed, what is indicated on the vertical axis?
9. Question
: Four
different groups of employees are randomly selected from a common population
for a study of differences in the impact of a wage increase. Why will
there be differences even before the incentive is applied?
10. Question
: What is
the probability of type II error when the null hypothesis is rejected?
BUS 308 WEEK 2 PROBLEM SET (NEW)
Problem Set Week Two.
Problem One
Suppose that an automotive parts
and accessories chain is experimenting with a new sales promotion. Two similar
stores are selected for the experiment. For Store 1, nothing changes. This
store constitutes the control group. For Store 2, the treatment group, the
promotion is implemented.
Sales in hundreds of dollars over a
five-day period are as follows:
Control: 6, 6, 7, 10, 12, 9, 6, 5,
5, 7
Treatment: 2, 5, 2, 4, 7, 1, 2, 3,
4, 5
The expectation that sales will be
higher in the treatment group makes this a one-tailed test; the alternate
hypothesis is m1 < m2. Use Excel to determine whether differences between
the two groups are statistically significant.
Show all of your work and clearly
label each of your calculations. Share your calculations and your interpretations
of your findings in your Word document.
Problem Two
Suppose that a home builder is
approached by a customer who wants to move in as soon as possible. The customer
chooses three home designs that she likes and asks the home builder which one could
be completed the fastest. To compare the three designs on speed of completion,
the builder randomly selects 10 homes that he built in the past based on each
of the three designs.
Use the Excel Analysis ToolPak to
run an ANOVA test in order to determine which design would be best for the
customer. Show all of your work and clearly label each of your calculations.
Make sure to also clearly describe the respective data and your conclusions.
The data for the number of days to
build each home are as follows:
Design A: 15, 17, 19, 21, 23, 25,
27, 29, 31, 33
Design B: 29, 34, 39, 44, 49, 54,
59, 64, 69, 74
Design C: 22, 24, 25, 27, 28, 28,
29, 31, 33, 34
For more information on conducting
an ANOVA test in Excel reference the Week Two Recommended Resources.
Problem Three
An insurance company is reviewing
its current policy rates. When originally setting the rates they believed that
the average claim amount was $1,800. Now there are concerns that if the true
mean is actually higher than this they could potentially lose a lot of money.
They randomly select 40 claims, and calculate a sample mean of $1,950. Assuming
that the standard deviation of claims is $500, and set significance , test to
see if the insurance company should be concerned
BUS 308 WEEK 3 DQ 1 INTERVAL DATA (NEW)
Interval Data.
A courier service in a large city
tracks the number of deliveries they are asked to make by 10 clients both
before and after offering a progressive discount for repeat business. Their
goal is to assess the effects of the discount.
a. What is the most appropriate
statistical test in this situation? Why?
b. Are there significant
differences in the number of deliveries?
c. If the goal is to promote repeat
business, should the discount be continued?
BUS 308 WEEK 3 DQ 2 CORRELATION (NEW)
Correlation.
An employment agency gathers the
following data on its clients:
a) Age
b) Gender
c) Educational level (no high
school, high school, associate’s, bachelor’s, master’s)
d) Years of past experience
e) Whether or not they have been successfully
placed in employment by the agency
Additionally, the following data is
gathered for those who have been successfully placed:
a) Starting salary
b) Current salary
c) Tenure in months
Based on the information above
answer the following questions:
a. Which type of correlation
procedure would be most appropriate to gauge the relationship between each pair
of variables?
b. Do you expect each pair of
variables to be significantly correlated or not? Why?
c. For the variables you expect to
be significantly correlated, what do you expect the direction of the
relationship to be? Why?
BUS 308 WEEK 3 ASSIGNMENT EVALUATION OF CORRELATIONS
(NEW)
Evaluation of
Correlations.
Data are gathered regarding the
length of tenure top executives have at a major corporation and whether those
executives have been divorced. The Human Resources department is evaluating
this data to drive decision-making in regard to their hiring process. The data
for eight executives is as follows:
In a three to five page paper,
excluding title page and reference page(s), answer the following questions to
analyze the data. Include clearly labeled calculations, if applicable.
Calculations conducted in Excel must be copied and pasted into the Word
document. This paper should be formatted according to APA guidelines outlined
in the Ashford Writing Center.
a. What’s the most appropriate
procedure for evaluating the relationship between tenure and divorce?
b. What is the correlation and how
can it be interpreted in terms of magnitude, direction and practical
importance?
c. How much of whether executives
have been divorced can be accounted for by their length of tenure with the
organization? How much of tenure can be explained by whether there has been a
divorce?
d. Make a logical argument for why lengthy
tenure may be causing divorce.
e. Make another logical argument
for why divorce may be causing lengthy tenure.
BUS 308 WEEK 4 DQ 1 SIMPLE REGRESSION ANALYSIS (NEW)
Simple Regression
Analysis.
Use the data in the
chart to answer the questions below. The data indicates the number of “sick
days” appliance installers take during a three month period, and the number of
complaints filed by customers during the same interval. Use the Analysis Toolpak
in Excel to perform this simple regression and answer the questions.
a. Is the correlation
between number of sick days and number of customer complaints statistically
significant?
b. What is the best
prediction for the number of complaints that will be registered for an
installer who takes five sick days during the period?
BUS 308 WEEK 4 DQ 2 MULTIPLE REGRESSIONS ANALYSIS
(NEW)
Multiple Regression
Analysis.
Develop a multiple linear
regression equation that describes the relationship between tenure and the
other variables in the chart above. Use the Analysis Toolpak located in Excel
to perform this multiple regression.
Do these two variables explain a
reasonable amount of the variation in the dependent variable?
Estimate the tenure of someone that
could have $5.8($k) and 15 years of job satisfaction. Make sure to state your
multiple regression equation in your example. What are some of things that you
can estimate from the model? How effective is evaluating the R-squared of the
model? What is the relationship between the independent and dependent
variables?
Use Excel to help you answer the
questions in the forum but do not attach your Excel document to the discussion
post.
Guided Response: Review several of
your classmates’ postings. Respond to at least two classmates by commenting on
how this information might be used to make business decisions.
BUS 308 WEEK 4 PROBLEM SET (NEW)
Problem Set Week Four.
Problem One
The manager of a
catering company is using the number of people in the party to predict the cost
of the drinks that are required for the event. The following are the data for
12 recently catered events:
Complete the
calculations below using this data. Show all of your work and
clearly label each of your calculations.
a. Provide a scatterplot
b. Calculate a linear
regression
c. Calculate the
residuals
d. Calculate the
correlation between the two variables
e. Calculate the mean,
median, and standard deviation of the number of people and cost of drinks
For additional
assistance with these calculations reference the Recommended Materials for Week
Four.
Problem Two
You are a real estate
agent and you are trying to predict home prices for your clients that want to
list their house for sale. You have a very small city without much data. You
will need to use the data that you have available for the past year on homes
that have been sold.
Complete the
calculations below using this data. Show all of your work and
clearly label each of your calculations.
Conduct a multiple
regression analysis to predict home prices. In your analysis complete the
following:
a. Calculate the
multiple regression analysis and report your data.
b. Determine the list
price for your client’s home if it has three bedrooms, three bathrooms, and
1900 square footage. Provide your analysis and show all of your calculations.
For additional
assistance with these calculations reference the Recommended Materials for Week
Four.
BUS 308 WEEK 4 QUIZ (NEW)
1. Question
: With
reference to problem 1, what statistic determines the correlation of experience
with productivity, controlling for age in experience?
2. Question
: In a
problem where interest rates and growth of the economy are used to predict
consumer spending, which of the following will increase prediction error?
3. Question
: With
reference to problem 3, how is the regression constant or the a value
interpreted?
4. Question
: Which of
the following is a problem in simple regression?
5. Question
: In a
problem where average temperature and number of daylight hours are used to
predict energy consumption in homes, what does the standard error of multiple
estimate gauge?
6. Question
: What does
“shrinkage” mean in reference to regression solutions?
7. Question
: The
degree to which years of education and years of experience together correlate
with annual salary is indicated in multiple correlation.
8. Question
: The
criterion variable in regression is the variable used to predict the value of
y.
9. Question
: Which of
the following are consistent with the requirements of simple regression?
10. Question
: Larger
sample diminish the standard error of the estimate.
BUS 308 WEEK 5 DQ 1 CONFIDENCE INTERVALS (NEW)
Confidence Intervals.
A hardware retailer has average
sales of $64,235 with a standard deviation of $5,918 for a 12-month period. The
mean monthly sales for all retailers in the chain are $59,844. Is this hardware
retailer’s sales significantly different from all retailers in the chain at ?
Are they significantly different at ? Calculate a .95 confidence interval for
the data in problem.
Explain your findings and determine
what question the confidence interval answers.
Guided Response: Review several of
your classmates’ postings. Respond to at least two classmates by commenting on
whether or not you think changing the confidence intervals will result in a
different outcome. Explain if you agree or not with the role of a confidence
interval in the interpretation of the answer
BUS 308 WEEK 5 DQ 2 CORRELATION AND CONFIDENCE
INTERVALS (NEW)
Correlation and
Confidence Intervals.
A car dealer is using
the number of years customers have owned their vehicles to predict how long it
will be before they elect to replace them. The correlation between the two is
(the longer they have owned their present vehicles, the more quickly they are
expected to replace them). The other relevant data are as follows for 32
customers:
Based on the information
above, answer the following questions:
a. How long is the time
to expected replacement for a customer who has owned a vehicle 6.5 years?
b. Calculate .95 and .99
confidence intervals and explain your results.
c. How will a larger
standard deviation in the criterion variable affect the width of the confidence
intervals? Why?
BUS 308 WEEK 5 FINAL PAPER (NEW)
Writing the Final Paper
Assignment Instructions:
A retail store has
recently hired you as a consultant to advise on economic conditions. One
important indicator that the retail store is concerned about is the
unemployment rate. The retail store has found that an increase in the
unemployment rate will cause a lack of consumer spending in their stores.
Retail stores use the unemployment rate to estimate how much inventory to keep
at their stores, which is important in maintaining cost effectiveness. In this
consultant role you will apply calculations and research to create a predictive
sales report.
You will complete this
project in two parts, but will submit your work as one Word document. Copy and
paste your calculations from your Excel workbook into the Word document.
The Final Project must
be eight to ten pages in length, excluding title page and reference page(s) and
must include at least three scholarly sources, in addition to the Job and Labor
Statistics site. Be sure to format your work in accordance with APA guidelines
outlined in the Ashford Writing Center.
Part I
Reference the data in
this Excel workbook to complete the following quantitative components of the
predictive sales report. You will complete the calculations below in your own
Excel workbook and then copy and paste from your Excel workbook into the Word
document.
1. Calculate the mean
yearly value using the average unemployment rate by month found in the “Final
Project Data Set.”
2. Using the years as
your x-axis and the annual mean as your y-axis, create a scatter plot and a
linear regression line.
3. Answer the following
questions using your scatter plot and linear regression line:
a. Compute the slope of
the linear regression line.
b. Identify the
Y-intercept of the linear regression line.
c. Identify the equation
of the linear regression line in slope-intercept form.
d. Calculate the
unemployment rate in 2016, based on the linear regression line.
e. Calculate the
residuals of each year.
f. Find the latest
unemployment rate in your state. You will need to go to the Bureau of Labor
Statistics website (www.bls.gov) and hover over “Subject Areas” in the top menu
panel then select “State and Local Unemployment Rates” from the drop down menu
under “Unemployment Rate”. Determine whether the rate in your state is within
the range of the linear regression line or if it is an outlier.
g. Interpret your
results of the model and explain how a company could use the results to drive
decision making.
PART II
Next interpret the
analysis from Part I to complete the following qualitative components of the
predictive sales report:
1. Introduce the project
and its significance to the retail store.
2. Reference the
statistical analysis that you completed in Part I and explain where the data
came from, what type of analysis was done, what the findings were, and whether
or not you believe the data to be accurate.
3. Explain your
data-driven conclusions regarding the effects of the changing unemployment rate
on the retail store.
4. Predict what could
occur in the future that would change your linear regression line and therefore
your prediction of sales.
BUS 308 ENTIRE COURSE (NEW)
BUS 308 Week 1 DQ 1 Data Scales
BUS 308 Week 1 DQ 2 Probability
BUS 308 Week 1 Quiz
BUS 308 Week 1 Problem Set Week One
BUS 308 Week 2 Journal
BUS 308 Week 2 DQ 1 t-Tests
BUS 308 Week 2 DQ 2 ANOVA Testing
BUS 308 Week 2 Quiz
BUS 308 Week 2 Problem Set
BUS 308 Week 3 DQ 1 Interval Data
BUS 308 Week 3 DQ 2 Correlation
BUS 308 Week 3 Assignment Evaluation of Correlations
BUS 308 Week 4 DQ 1 Simple Regression Analysis
BUS 308 Week 4 DQ 2 Multiple Regressions Analysis
BUS 308 Week 4 Problem Set
BUS 308 Week 4 Quiz
BUS 308 Week 5 DQ 1 Confidence Intervals
BUS 308 Week 5 DQ 2 Correlation and Confidence Intervals
BUS 308 Week 5 Final Paper
BUS
308 Complete Course BUS308 Complete Course
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