Category Archives: GB 513

GB 513 All Assignment Recent

GB 513 All Assignment Recent

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GB 513 All Assignment Recent

GB 513 Unit 1 Assignment Questions

GB 513 Unit 2 Assignment Probability

GB513 Unit 3 Assignment

GB 513 Unit 4 Assignment

GB 513 Unit 5 Assignment

GB 513 Unit 6 Assignment Final Project Colonial Broadcasting Case

GB 513 Unit 1 Assignment Recent

GB 513 Unit 1 Assignment Recent

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GB 513 Unit 1 Assignment Recent

This assignment requires you to use Excel to answer the questions and create the charts. However when presenting reports in business, you will find that most managers will prefer to read Word® documents or PowerPoint® slides rather than go through Excel sheets. Being able to move your work from Excel to Word® is a valuable skill. For this assignment, you should copy all your charts and comments to a Word document and submit that Word file. Clearly label all questions and charts, as well as your answers.

Question 1

According to T-100 Domestic Market, the top seven airlines in the United States by domestic boardings in a recent year were Southwest Airlines with 81.1 million, Delta Airlines with 79.4 million, American Airlines with 72.6 million, United Airlines with 56.3 million, Northwest Airlines with 43.3 million, U.S. Airways with 37.8 million, and Continental Airlines with 31.5 million. Construct a pie chart and a bar graph to depict this information.

Question 2

The U.S. Department of the Interior releases figures on mineral production. Following are the 15 leading states in nonfuel mineral production in the United States in 2008.

State Value ($ billions) Arizona 7.84

Nevada 6.48

Florida 4.20

Utah 4.17 California 4.00 Texas 3.30 Minnesota 3.21 Alaska 2.74 Missouri 2.08 Colorado 2.05 Michigan 2.05 Wyoming 1.89 Georgia 1.85

New Mexico 1.81 Pennsylvania 1.68

a) Using the data analysis toolpak in Excel, calculate the descriptive statistics.

b) Briefly explain what each of the metrics in the summary statistics means.

c) Commentonthefiguresinthereport.Whataretheytellingyouaboutthisdataset?Isit

symmetrical, flat, skewed, does it have outliers, and so on?

Question 3

Suppose Procter & Gamble sells about 20 million bars of soap per week, but the demand is not constant, and production management would like to get a better handle on how sales are distributed over the year. Let the following sales figures given in units of million bars represent the sales of bars per week over one year. Construct a histogram to represent these data. What do you see in the graph that might be helpful to the production (and sales) people?

17.1 17.1 17 25.2 19.6 12.2 18.3 26.3 15.4 19.9 13.6 23.9 17.4 18.7 39.8 30.6

15 20.4 20.7 25.2 18.5 20.3 21.3 26.2 20.6 15.5 22.5 26.9 18.4 16.8 21.4 32.8

20 19.1 23.4 26.3 20.9 20.4 23.1 26.6 19.3 15.4 22.8 24.3 18.2 20.3 21.4 26.2 14.7 17.5 24 23.8

 

GB 513 Unit 2 Assignment Probability Recent

GB 513 Unit 2 Assignment Probability Recent

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GB 513 Unit 2 Assignment Probability Recent

Question 1

An Adweek Media/Harris Poll revealed that 44% of U.S. adults in the 18–34 years category think that “Made in America” ads boost sales. A different Harris Interactive poll showed that 78% of U.S. adults in the 18–34 years category use social media online. Suppose that 85% of U.S. adults in the 18–34 years category think that “Made in America” ads boost sales or use social media online.

If a U.S. adult in the 18–34 years category is randomly selected

a. Whatistheprobabilitythatthepersonthinksthat“MadeinAmerica”adsboostsalesanduses social media online?

b. What is the probability that the person thinks that “Made in America” ads boost sales given that the person does not use social media online?

Question 2

According to a report by Scarborough Research, the average monthly household cellular phone bill is $73. Suppose local monthly household cell phone bills are normally distributed with a standard deviation of $11.35.

a. What is the probability that a randomly selected monthly cell phone bill is more than $100?

b. What is the probability that a randomly selected monthly cell phone bill is between $60 and $83? c. What is the probability that a randomly selected monthly cell phone bill is between $80 and $90? d. What is the probability that a randomly selected monthly cell phone bill is no more than $55?

Question 3

A Travel Weekly International Air Transport Association survey asked business travelers about the purpose for their most recent business trip. 19% responded that it was for an internal company visit. Suppose 950 business travelers are randomly selected.

a. What is the probability that more than 25% of the business travelers say that the reason for their most recent business trip was an internal company visit?

b. What is the probability that between 15% and 20% of the business travelers say that the reason for their most recent business trip was an internal company visit?

c. What is the probability that between 133 and 171 of the business travelers say that the reason for their most recent business trip was an internal company visit?

 

GB 513 Unit 3 Assignment Recent

GB 513 Unit 3 Assignment Recent

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GB 513 Unit 3 Assignment Recent

Question 1

A group of investors wants to develop a chain of fast-food restaurants. In determining potential costs for each facility, they must consider, among other expenses, the average monthly electric bill. They decide to sample some fast-food restaurants currently operating to estimate the monthly cost of electricity. They want to be 90% confident of their results and want the error of the interval estimate to be no more than $100. They estimate that such bills range from $600 to $2,500. How large a sample should they take?

Question 2

Suppose a study reports that the average price for a gallon of self-serve regular unleaded gasoline is $3.16. You believe that thefigure is higher in your area of the country. You decide to test this claim for your part of the United States by randomly calling gasoline stations. Your random survey of 25 stations produces the following prices (all in $). Assume gasoline prices for a region are normally distributed. Do the data you obtained provide enough evidence to reject the claim? Use a 1% level of significance.

3.27 3.29 3.20 3.23 3.16 3.07 3.15 3.23 3.21 3.14

Question 3

3.16 3.20 3.37 3.19 3.20 3.24 3.27 3.09 3.35 3.14 3.05 3.35 3.14 3.07 3.10

Where do CFOs get their money news? According to Robert Half International, 47% get their money news from newspapers, 15% get it from communication/colleagues, 12% get it from television, 11% from the Internet, 9% from magazines, 5% from radio, and 1% do not know. Suppose a researcher wants to test these results. She randomly samples 67 CFOs and finds that 40 of them get their money news from newspapers. Does the test show enough evidence to reject the findings of Robert Half International? Use a = .05.

Question 4

To answer this question, use the Data Analysis Toolpack in Excel and select “t-Test: Two-Sample Assuming Equal Variances” from the list of available tools. Explain your answer (how did you decide if men spend more) and include the output table. Some studies have shown that in the United States, men spend more than women buying gifts and cards on Valentine’s Day. Suppose a researcher wants to test this hypothesis by randomly sampling nine men and 10 women with comparable demographic characteristics from various large cities across the United States to be in a study. Each study participant is asked to keep a log beginning one month before Valentine’s Day and record all purchases made for Valentine’s Day during that one-month period. The resulting data are shown below. Use these data and a 1% level of significance to test to determine if, on average, men actually do spend significantly more than women on Valentine’s Day. Assume that such spending is normally distributed in the population and that the population variances are equal.

Men Women

107.48 125.98 143.61 45.53 90.19 56.35 125.53 80.62 70.79 46.37 83.00 44.34 129.63 75.21 154.22 68.48 93.80 85.84

126.11

 

GB 513 Unit 4 Assignment Recent

GB 513 Unit 4 Assignment Recent

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GB 513 Unit 4 Assignment Recent

Question 1

Shown below are rental and leasing revenue figures for office machinery and equipment in the United States over a seven-year period according to the U.S. Census Bureau. Use these data to run a linear regression and then forecast the rental and leasing revenue for the year 2012.

Year Rental and Leasing ($ millions)

2004. 2004 5,860

2005. 2005 6,632

2006. 2006 7,125

2007. 2007 6,000

2008. 2008 4,380

2009. 2009 3,326

2010. 2010 2,642

Question 2

Suppose a researcher gathered survey data from 19 employees and asked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following data represent the results of this survey. Assume that relationship with supervisor is rated on a scale from 0 to 50 (0 represents poor relationship and 50 represents an excellent relationship), overall quality of the work environment is rated on a scale from 0 to 100 (0 represents poor work environment and 100 rep resents an excellent work environment), and opportunities for advancement is rated on a scale from 0 to 50 (0 represents no opportunities and 50 represents excellent opportunities).

Answer the following questions:

A) What is the regression formula?

B) How reliable do you think the estimates will be based on this formula? How can you tell?

C) Are there any variables that do not appear to be good predictors of Job satisfaction? How can

you tell?

D) If a new employee reports that her relationship with her supervisor is 40, finds the quality of the work environment to be scored at 75, works 60 hours per week and rates her opportunities for advancement to be at 30, what would you expect her job satisfaction score to be?

Job satisfaction

55

20

85

65

45

70

35

60

95

65

85

10

75

80

50

90

75

45

65

Relationship with supervisor

Overall quality of work environment

Total hours worked per week

Opportunities for advancement

Question 3

27 65 12 13 40 79 35 53 29 43 42 62 22 18 34 75 50 84 33 68 40 72 510 37 64 42 82 31 46 47 95 36 82 20 42 32 73

50 42 60 28 45 7 65 48 40 32 50 41 75 18 40 32 45 48 60 11 55 33 50 21 45 42 40 46 60 48 55 30 70 39 40 22 55 12

Investment analysts generally believe the interest rate on bonds is inversely related to the prime interest rate for loans; that is, bonds perform well when lending rates are down and perform poorly when interest rates are up. Can the bond rate be predicted by the prime interest rate?

Use the following data to construct a scatter graph and then fit a regression line to the data. Report the regression formula and the r-squared value from the chart (right click on the line, select “Add Trendline” and select options to show these metrics).

Bond Rate Prime Interest Rate

5% 16% 12 6 98

15 4 77

GB 513 Unit 5 Assignment Recent

GB 513 Unit 5 Assignment Recent

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GB 513 Unit 5 Assignment Recent

Question 1

Determine the error for each of the following forecasts. Compute MAD and MSE.

Period Value Forecast Error

1

2

3

4

5

6

7

8

9

10

11

Question 2

202— — 191 202

173 192

169 181

171 174 175 172 182 174 196 179 204 189 219 198 227 211

The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and nondurable goods industries. Shown here are factory orders in the United States over a 13-year period ($ billion).

1. Usethesedatatodevelopforecastsfortheyears6through13usinga5-yearmovingaverage.

2. Usethesedatatodevelopforecastsfortheyears6through13usinga5-yearweighted moving average. Weight the most recent year by 6, the previous year by 4, the year before that by 2, and the other years by 1.

3. Compute the errors of the forecasts in parts (a) and (b) and then the MAD. Which forecast is better?

1. 1 2,512.7

2. 2 2,739.2

3. 3 2,874.9

4. 4 2,934.1

5. 5 2,865.7

6. 6 2,978.5

7. 7 3,092.4

8. 8 3,356.8

9. 9 3,607.6

10. 10 3,749.3

11. 11 3,952.0

12. 12 3,949.0

13. 13 4,137.0

Question 3

The “Economic Report to the President of the United States” included data on the amounts of manufacturers’ new and unfilled orders in millions of dollars. Shown here are the figures for new orders over a 21-year period. Use Excel to develop a regression model to fit the trend effects for these data. Use a linear model and then try a quadratic model. How well does either model fit the data?

Year Total Number of New Orders

1. 1 55,022

2. 2 55,921

3. 3 64,1 82

4. 4 76,003

5. 5 87,327

6. 6 85,139

7. 8 115,109

9. 9 131,629

10. 10 147,604

11. 11 156,359

12. 12 168,025

13. 13 162,140

14. 14 175,451

15. 15 192,879

16. 16 195,706

17. 17 195,204

18. 18 209,389

19. 19 227,025

20. 20 240,758

21. 21 243,643

 

GB 513 Unit 6 Assignment Final Project Colonial Broadcasting Case Recent

GB 513 Unit 6 Assignment Final Project Colonial Broadcasting Case Recent

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GB 513 Unit 6 Assignment Final Project Colonial Broadcasting Case Recent

This is your final project. You will prepare a PowerPoint

presentation to present your findings. This assignment requires you to use Excel; make sure you also submit the Excel file to show your work. Place all calculations for each of the questions on a separate worksheet. Then, using the results of your work from Excel, prepare PowerPoint slides to answer the questions in a presentation format. Search the Internet to ensure that you are using the best PowerPoint tips to display an appropriate presentation. Check the Webliography tab at the top of the course page for help.

For the final project, you will be analyzing the “Colonial Broadcasting” case. Answer the questions listed below, NOT the questions listed in the case. Ignore everything in the case after the end of page 6.

The executives at CBC want to see how they are doing in ratings against the other networks and how the ratings will continue to change in the upcoming months. They also want to know if hiring stars makes a difference and the impact of fact based programming compared to hiring stars. You will create a PowerPoint presentation to answer the questions below. Remember that your audience is the management of CBC: Make sure your presentation is professional and provides sufficient explanation.

1. Descriptive statistics:

What is the average rating for all CBC movies? How about ABN movies and BBS movies? Include a table that shows the average and the other descriptive statistics for the ratings of the three networks (one column for each network). Comment on which network is doing best and what you learn from the other key metrics in the table.

2. Charting:

Create a line graph of the monthly average ratings for CBC for the year. Note that there are multiple ratings data for the months; you will need to calculate an average for each month and then plot the averages. After you create the graph, fit a linear trend line, displaying the formula and the r-squared. Explain to the executives if you can use this time series data to forecast the ratings of upcoming months. How accurate can you expect this forecast to be?

3. Hypothesistesting:

Should the CBC hire stars for their movies? To answer this question, run a hypothesis test to see if there is a significant difference between the ratings of movies with stars vs. movies without stars. Use the data for CBC movies only. Use 95% confidence. Explain your answer- do not simply say yes or no without referring to the relevant figures.

4. Regression:

CBC Management has several questions: Which has more impact on a movie’s rating: that it is fact based or that it has one star? How much does each of these factors change the ratings? Do you expect a fact based movie that does not have any stars to get better ratings than a fiction movie with one star? Run a multiple regression where the dependent variable is ratings and the independent variables are star and fact. Use data from all networks, not just CBC movies. How well does this regression analysis explain the ratings? Justify your answers based on the results.