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Apply: Connect Week 1 Exercise

Review the glossary in your textbook in preparation for this assignment.

Complete the Week 1 Exercise in Connect.

Note: You have only 1 attempt available to complete assignments.

Apply: Connect Week 2 Case

Part 1

You manage the inventory for a car dealership. Your management would like you to review current

inventory on the dealership lot.

Review the Week 2 Data Set.

Create and calculate the following in Excel®:

Create a Pie Chart which summarizes colors of the cars in the sample.

Create a Bar Chart which summarizes the frequency of the models of the cars in the sample.

Create a Frequency Table for classes of MPG, including Frequency and Relative Frequency for

the cars in the sample.

Calculate the mean Days in Inventory for the cars in the sample.

Compare that to the median and the mode.

Highlight the value that would be a better representation of the “typical” price of a car

in inventory?

Calculate the standard deviation of the Days in Inventory for the cars in the sample.

Calculate the 5 number summary for the suggested retail prices of the cars in the sample.

This consists of the 1st, 2nd, 3rd, 4th quartile and the IQR.

Note: Part 1 is not submitted. It is only to be completed in preparation for Part 2.

Part 2

Reference your Excel® spreadsheet from Part 1.

Complete the Week 2 Case in Connect.

Note: You have only 1 attempt available to complete assignments.

Apply: Connect Week 3 Case

Part 1

Three hundred consumers between 21 and 49 years old were randomly selected. After sampling a

new wine cooler, each was asked to rate the appeal of the phrase: “Not sweet like wine coolers,

not filling like beer, and more refreshing than wine or mixed drinks” as it relates to the new

wine cooler. The rating was made on a scale from 1 to 5, with 5 representing “extremely

appealing” and with 1 representing “not at all appealing”.

As a manager overseeing the development of the concept, you bottle the wine cooler and placed

it into distribution in one test store.

Your manager has asked you to assess the data and determine the most likely customer based on

the ratings. Additionally, your manager would like you to review sales in the test store.

Use the Week 3 Data Set to create and calculate the following in Excel®:

Estimate the probability that a randomly selected 21 to 49 year old consumer:

Would give the phrase a rating of 5

Would give the phrase a rating of 3 or higher

Is in the 21-24 age group

Is a male who gives the phrase a rating of 4

Is a 35 to 49 year old who gives the phrase a rating of 1

Based on the probabilities for the ratings of 4 and 5, which age/gender demographic

would be the best target audience for the new concept?

Create a probability distribution using the data which shows how many cartons of the wine

cooler were bought per customer in a month.

Calculate the mean and the standard deviation of your probability distribution.

Calculate the probability that exactly 3 six packs will be bought in a month.

Calculate the probability that between 4 and 8 six packs will be bought in a month.

Calculate the probability that at least 5 six packs will be bought in a month.

Calculate the probability that no more than 5 six packs will be bought in a month.

Create a relative frequency distribution based on the wine cooler drinking temperatures.

Create 6 bins with the same interval in each.

Create a histogram

Considering the mean and standard deviation for the ideal drinking temperature:

Calculate z values then refer to Table 6.1 – Cumulative Areas Under the Standard Normal

Curve

Calculate the probability of the wine cooler being less than 45 degrees.

Calculate the probability of the wine cooler being greater than 60 degrees.

Calculate the percentage of wine coolers served at the ideal temperature, between 49

and 55 degrees.

Part 2

Reference your Excel® spreadsheet from Part 1.

Complete the Week 3 Case in Connect.

Note: You have only 1 attempt available to complete assignments.

Apply: Connect Week 4 Case

Part 1

You manage Human Relations for your company. One of your sales managers has retired, leaving an

opening. You are considering two different employees for the position. Both are highly

qualified so you have decided to evaluate their sales performance for the past year.

Use the Week 4 Data Set to create and calculate the following in Excel®:

Determine the range of values in which you would expect to find the average weekly sales

for the entire sales force in your company 90% of the time.

Calculate the impact of increasing the confidence level to 95%?

Calculate the impact of increasing the sample size to 150, assuming the same mean and

standard deviation, but allowing the confidence level to remain at 90%?

Based on the calculated confidence interval for weekly sales on the sample of 50 reps at a

90% confidence level:

Calculate both Reps’ average weekly performance and highlight if it is greater than the

population mean.

You want to determine whether there is a statistically different average weekly sales

between Sales Rep A and Sales Rep B.

Create Null and Alternative Hypothesis statements that would allow you to determine

whether their sales performance is statistically different or not.

Use a significance level of .05 to conduct a t-test of independent samples to compare

the average weekly sales of the two candidates.

Calculate the p-value?

Considering that individual you did not promote:

Determine whether this person’s average weekly sales are greater than the average

weekly sales for the 50 sales reps whose data you used to develop confidence intervals.

Create Null and Alternative Hypothesis statements that would allow you to determine

whether the new Sales Manager’s weekly average sales are greater than the sample of Sales Reps.

Use a significance level of .05 to conduct a t-test of independent samples to compare

the average weekly sales of both.

Calculate the p-value?

Part 2

Reference your Excel® spreadsheet from Part 1.

Complete the Week 4 Case in Connect.

Note: You have only 1 attempt available to complete assignments.

Apply: Connect Week 5 Case

Part 1

You are the manager of a retail store. You want to investigate how metrics can improve the way

you manage your business.

Use the Week 5 Data Set to create and calculate the following in Excel®:

Conduct a goodness of fit analysis which assesses orders of a specific item by size and

items you received by size.

Conduct a hypothesis test with the objective of determining if there is a difference

between what you ordered and what you received at the .05 level of significance.

Identify the null and alternative hypotheses.

Generate a scatter plot, the correlation coefficient, and the linear equation that

evaluates whether a relationship exists between the number of times a customer visited the

store in the past 6 months and the total amount of money the customer spent.

Set up a hypothesis test to evaluate the strength of the relationship between the two

variables.

Use a level of significance of .05.

Use the regression line formula to forecast how much a customer might spend on merchandise

if that customer visited the store 13 times in a 6 month period. Consider the average monthly

sales of 2014, $1310, as your base to:

Calculate indices for each month for the next two years.

Graph a time series plot.

In the Data Analysis Toolpak, use Excel’s Exponential Smoothing option.

Apply a damping factor of .5, to your monthly sales data.

Create a new time series graph that compares the original and the revised monthly sales

data.

Part 2

Reference your Excel® spreadsheet from Part 1.

Complete the Week 5 Case in Connect.

Note: You have only 1 attempt available to complete assignments.

Week 1 Practice: Connect Knowledge Check

1.

Daily temperature in a local community collected over a 30-day time period is an example of cross-sectional data.

True

False

2.

Time series data are data collected at the same time period.

True

False

3.

Primary data are data collected by an individual.

True

False

4.

A random sample is selected so that every element in the population has the same chance of being included in the sample.

True

False

5.

__________ consists of a set of concepts and techniques that are used to describe populations and samples.

Data mining

Traditional statistics

Random sampling

Time series analysis

6.

A sequence of operations that takes inputs and turns them into outputs is a ____________.

statistical inference

process

random sampling

runs plot

7.

Processes produce outputs over time.

True

False

8.

_________ uses traditional or newer graphics to present visual summaries of business information.

Data mining

Descriptive analytics

Predictive analytics

Association learning

9.

The number of sick days taken by employees in 2008 for the top 10 technology companies is an example of time series data.

True

False

10.

A population is a set of existing units.

True

False

11.

A(n) _____________ variable is a qualitative variable such that there is no meaningful ordering or ranking of the categories.

interval

ordinal

ratio

nominative

12.

Judgment sampling occurs when a person who is extremely knowledgeable about the population under consideration selects the population element(s) that they feel is(are) most representative of the population.

True

False

Week 2 Practice: Connect Knowledge Check

1.

Award: 0.50 out of 0.50 points

In a statistics class, 10 scores were randomly selected with the following results: 74, 73, 77, 77, 71, 68, 65, 77, 67, 66.

What is the IQR?

11.00

10

5.00

5.25

12.00

2.

A quantity that measures the variation of a population or a sample relative to its mean is called the ____________.

range

interquartile range

standard deviation

coefficient of variation

variance

3.

Award: 0.50 out of 0.50 points

An observation separated from the rest of the data is a(n) ___________.

absolute extreme

outlier

quartile

mode

4.

Award: 0.50 out of 0.50 points

Quality control is an important issue at ACME Company, which manufactures light bulbs. To test the life-hours of their light bulbs, they randomly sampled nine light bulbs and measured how many hours they lasted: 378, 361, 350, 375, 200, 391, 375, 368, 321.

What is the mean?

375

389.9

368

346.6

200

5.

Award: 0.50 out of 0.50 points

In a statistics class, 10 scores were randomly selected with the following results (mean = 71.5): 74, 73, 77, 77, 71, 68, 65, 77, 67, 66.

What is the range?

516.20

144.00

22.72

4.77

12.00

6.

Award: 0.50 out of 0.50 points

Which percentile describes the first quartile, Q1?

25th

100th

75th

50th

7.

Award: 0.50 out of 0.50 points

Personnel managers usually want to know where a job applicant ranked in his or her graduating class. With a grade point average of 3.83, Michelle Robinson graduated above the 93rd percentile of her graduating class. What is the percentile rank of a student whose GPA was the median GPA.

75th

50th

25th

93rd

10th

8.

Award: 0.50 out of 0.50 pointS

All of the following are measures of central tendency except the ____________.

mode

range

mean

median

9.

Award: 0.50 out of 0.50 points

Quality control is an important issue at ACME Company, which manufactures light bulbs. To test the life-hours of their light bulbs, they randomly sampled nine light bulbs and measured how many hours they lasted (mean = 346.6).

378, 361, 350, 375, 200, 391, 375, 368, 321

What is the range?

58.5

191

3424.3

10,609

342.43

10.

The local amusement park was interested in the average wait time at their most popular roller coaster at the peak park time (2 p.m.). They selected 13 patrons and had them get in line between 2 and 3 p.m. Each was given a stopwatch to record the time they spent in line. The times recorded were as follows (in minutes): 118, 124, 108, 116, 99, 120, 148, 118, 119, 121, 45, 130, 118.

What is the mean?

115.5

148

118

114.15

45

11.

Award: 0.50 out of 0.50 points

The local amusement park was interested in the average wait time at their most popular roller coaster at the peak park time (2 p.m.). They selected 13 patrons and had them get in line between 2 and 3 p.m. Each was given a stopwatch to record the time they spent in line. The times recorded were as follows (in minutes): 118, 124, 108, 116, 99, 120, 148, 118, 119, 121, 45, 130, 118.

What is the median?

118

115.5

45

114.15

148

12.

Award: 0.50 out of 0.50 points

When establishing the classes for a frequency table, it is generally agreed that the more classes you use the better your frequency table will be.

True

False

Week 3 Practice: Connect Knowledge Check

Week 4 Practice: Connect Knowledge Check

Week 5 Practice: Connect Knowledge Check

…..

Practice: Week 1 Discussion Question 1

Consider a decision you need to make at work or at home.

Choose one statistical tool that you read about this week.

Explain how this tool will help you make that decision.

Post your response in the discussion area.

Note: This must be original; do not use examples from the Internet.

Practice: Week 1 Discussion Question 2

Measures of Central Tendency

What are the different measures of central tendency?  When will they be used?

Practice: Week 2 Discussion Question 1

Objectives:

Research the Internet for an example of a pie chart or bar chart.

Post a copy along with its source in the discussion area.

Include a question regarding the chart for your classmates to respond to.

Respond to a classmate’s question.

Practice: Week 2 Discussion Question 1

Objectives:

Research the Internet for an example of a pie chart or bar chart.

Post a copy along with its source in the discussion area.

Include a question regarding the chart for your classmates to respond to.

Respond to a classmate’s question.

Practice: Week 3 Discussion Question 1

Objectives:

Reference the Week 2 Case.

Respond to one of the following:

Regarding requirement #4: What impact would an outlier have?

Regarding requirement #5: Why is it important to look at dispersion?  Why is standard deviation a better measure of dispersion than the range?

Post your response in the discussion area.

Practice: Week 3 Discussion Question 2

Objectives:

Variables

Differentiate between discrete and continuous variables?  Give examples of each?

Practice: Week 4 Discussion Question 1

Objectives:

Reference the Week 3 Case study.

Respond to one of the following:

Regarding requirement #2: What does the mean and standard deviation mean in terms of expected sales?

Regarding requirement #2: How can this information be used to benefit the business?

Regarding requirement #3: Can you conclude whether the data is normally distributed?

Regarding requirement #4: What can be interpreted by that percentage?

Post your response in the discussion area.

Practice: Week 4 Discussion Question 2

Objectives:

Normal Distribution

What are the characteristics of the normal distribution?

What are the applications of this distribution?

Practice: Week 5 Discussion Question 1

Objectives:

Reference the Week 4 Case study.

Respond to one of the following:

Regarding requirement #2: What impacted the Reps’ average weekly performance to be greater than the population mean?

Regarding requirement #3: Considering your hypothesis statements, provide an example of a Type I and a Type II error.

Regarding requirement #3: Considering the p-values, is a statistically significant difference between the two reps being considered for the manager’s position? Explain.

Regarding requirement #3: Who would you recommend to be promoted to Sales Manager – Rep A or Rep B?  Why?

Regarding requirement #4: Considering the outcome of the hypothesis test, is your new Sales Manager outperforming the sales force?

Post your response in the discussion area.

Practice: Week 5 Discussion Question 2

Objectives:

Hypothesis

How would you set up the null and the alternative hypothesis?

What are the rules you would follow here?