Pietro is a member of the local business Chamber of Commerce

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Finance for Strategic Managers                         Level 7                      

Pietro Yon, a local businessman, owns and manages a number of retail stores that sell a range of homewares.

Pietro is a member of the local business Chamber of Commerce and has been asked to chair a committee to research and study the success of Samsung PLC. The Chamber believes that there may be some useful learning from this study which members of the Chamber could use. You have been asked to provide specialist support to the committee and you are required to produce a range of materials for members of the committee to use.

You have been provided with the following link to view Samsung PLC’s annual reports and investor information.

https://www.samsung.com/global/ir/financial-information/audited-financial-statements/

 

Task 1 – Financial Data and Strategic Decision Making

 

You must produce a presentation for Pietro Yon to use at the next meeting of the Chamber of Commerce. The presentation should be based on your research of Samsung PLC and other relevant information. It must be accompanied by supporting notes.

Your presentation must include the following:

 

  • An evaluation of the sources of financial data which can be used to inform business strategy.
  • An assessment of the need for financial data and information in relation to the formulation of business strategy.
  • An analysis of the risks related to financial business decisions.
  • A review of methods that can be used for appraising strategic capital expenditure projects and strategic direction.

 

Task 2 – Discussion Paper

 

A meeting has been arranged with Pietro Yon and other members of the committee and you have been asked to produce a paper for discussion which provides:

 

  • An interpretation of the financial statements of Samsung PLC to assess the current viability of the organisation.
  • A comparative analysis of financial data using ratio analysis for Samsung PLC.  You are advised to download consecutive year’s accounts from the Samsung PLC website.

 

 

Extension activities:

 

To gain a merit grade you must add further sections to your discussion paper that:

 

  • Makes recommendations to Samsung PLC based on your analysis and interpretation of the financial position.

 

 

Task 3 – Information Leaflet

 

Extension activities:

 

To gain a merit grade you must produce an information leaflet for the Chamber of Commerce to distribute to the members. The leaflet should assess the following:

 

  • The impact of ‘creative accounting’ techniques when making strategic decisions.
  • The limitations of ratio analysis as a tool for strategic decision making.
  • The importance of cash flow management when evaluating proposals for capital expenditure.

 

To gain a distinction grade you must prepare an additional section for the leaflet that:

 

  • Recommends, with justifications, methods and tools that allow businesses to analyse financial data for strategic decision making purposes.

 

 

Task 4 – Capital Expenditure Appraisal

 

Pietro Yon has been supplied with information from a component manufacturer who has asked for advice on the best project to accept for the purchase / replacement of a piece of machinery.

 

The company are considering selling their old machine that has a capital cost of £260 000 and replacing it with an up to date model costing £220 000.  For immediate purchase the company will receive £120 000-part exchange allowance.

 

Both the current and new machines are able to meet the expected company demand, estimated at:

 

Year Units
1 90 000
2 50 000
3 30 000

 

After three years, it is predicted that demand will be zero due to the technological developments in the industry.

 

The following data has been provided for the existing and new machine:

 

  Current Machine

£ per unit

 New Machine

£ per unit
Direct Materials 1.80 1.80
Direct Labour 0.75 0.60
Variable Overheads 0.45 0.30
Depreciation 0.35 0.55

 

Additional information

 

  • The selling price for each component is £5.00 and this will remain constant for the next three years.
  • The company expect the cost of direct materials and direct labour to increase by 5% each year.
  • The company predicts that repair and maintenance costs for the current machine will be £7000 per annum.
  • The current machine is expected to have a zero-residual value at the end of year 3.
  • The company predicts that repair and maintenance costs for the new machine will be £1000 per annum.
  • The new machine is expected to have a £75 000 residual value at the end of year 3.

 

 

 

 

 

The company’s cost of capital is 15%

 

Extract from the present value table for £1 at 15%

 

Year Units
1 0.870
2 0.756
3 0.658
4 0.572

 

 

Pietro would like you to produce a business report that can be given to the company offering advice on the best course of action for the purchase / replacement machine.

 

REQUIRED

 

Prepare a report that evaluates the capital expenditure proposals using appropriate financial techniques.

 

Extension activities:

 

To gain a distinction grade you must include an assessment of the impact of the business proposal on the strategic direction of the organisation.

 

Blank Paper

The purpose of this assignment is to critically watch and review a movie with popular culture themes

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Purpose: The purpose of this assignment is to critically watch and review a movie with popular culture themes/symbols in terms of the sociological perspective and cultural theories.

Instructions:

1) Select a movie: For this assignment, you will need to select one movie.  Even if it is a movie you have seen before, you need to re-watch the movie with a critical eye towards the social construction of reality and illustrations of other sociological/cultural concepts.  If you would like to analyze a movie that is not on the list, please send me a message to clear it with me.

Suggested Movie Options:

Hotel Rwanda         Brazil                                  Million Dollar Baby

Office Space          Gandhi                                  Boys Don’t Cry

The Village             Cape Fear (deNiro version)      Mystic River

Last Samurai         Mothman Prophecies                Traffic

The Wall              Glory                                        Stepford Wives

Pretty in Pink        Hoop Dreams                            The Terminal

The Breakfast Club    It’s a Wonderful Life     Bowling for Columbine

Grapes of Wrath    Pretty Woman                           The Hours

To Kill a Mockingbird   Citizen Kane                         Cabin Fever

Clockwork Orange     Fight Club                               Radio

Crash                      Nosferatu                                 Titanic

The Gods Must be Crazy   Taxi Driver                 Coming to America

American History X      Roger & Me                     Fight Club

Inherit the Wind     Dead Poet’s Society             Mona Lisa’s Smile

Bullworth              Life is Beautiful                     American Beauty

Lord of the Flies     The Truman Show                   The Matrix

With Honors            Affluenza                              Erin Brokovich

Working Girl           Risky Business                     Baby Boom

Rain Man               Philadelphia                       NDogma

Chocolate                Parenthood                 Shawshank Redemption

Last Castle            Witness                           Meet Joe Black

2) Analyze the movie: After watching the movie, you will write a 2-4 page review, consisting of:

a) introductory paragraph noting the relevance of the movie to the course

b) one-page description/summary of the contents of the film; some questions you could address are:

-Major substantive points of the movie?

-Any secondary points made?

c) 1-2 pages in which you use at least 4 sociological/pop cultural concepts and theories covered in this course to analyze the movie (cite class materials and outside sources as you do so)

 

General requirements:

  • Submissions should be typed, double-spaced, 1″ margins, times new roman 12 pt font, and saved as .doc, .docx, .pdf.
  • Use APA format for citations and references
  • View the grading rubric so you understand how you will be assessed on this Assignment.
  • Disclaimer- Originality of attachments will be verified by Turnitin. Both you and your instructor will receive the results.
  • This course has “Resubmission” status enabled to help you if you realized you submitted an incorrect or blank file, or if you need to submit multiple documents as part of your Assignment. Resubmission of an Assignment after it is grades, to attempt a better grade, is not permitted.

Research the organizational structure of the United Nations Human Rights Council

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Research the organizational structure of the United Nations Human Rights Council. What are the goals of the organization? How is it structured to accomplish those goals? Discuss if it is accomplishing those goals, and if it is not accomplishing those goals, suggest possible changes to streamline the organization.

The essay should be three pages in length and properly formatted to include a title page and reference list. The paper should follow APA guidelines for all resources for in-text citations, paraphrasing, and references. Remember to use the CSU Online Library to assist you in the research for this assignment.

What were Brandywine net income, total profit, margin and cash flow

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Problem 3.5

 

Brandy Wine Homecare

Income Statement

December 31, 2011

 

Revenues:

Total revenues                                                                         $12,000,000

 

Expenses:

Expenses                                                                                     $9,000,000

Depreciation                                                                             $1,500,000

Total expenses                                                          $10,500,000

Revenue over expenses (Net Income)                         $1,500,000

 

  1. What were Brandywine’s net income, total profit, margin and cash flow?

Net income = Total revenue – Total expenses

= $12,000,000 – $10,500,000

=$1,500,000

Its net income would be $1,500,000

 

Total profit margin = Net Income / Total Revenues

=1,500,000 / $12,000,000

=0.125 = 12.5%

Its total profit margin is 12.5%

 

Cash flow = Net Income + Depreciation Expense

= $1,500,000 + $1,500,000

= $3,000,000

Its total cash flow is $3,000,000

 

  1. Now, suppose the company changed its depreciation calculation procedures such that its depreciation expense doubled. How would this change affect Brandywine’s net income, total profit margin and cash flow?

 

Revenue                                                                        $12,000,000

Total revenue                                                            $12,000,000

Expenses:

Depreciation ($1,500,000×2)                           $3,000,000

Other   ($12,000,000 x 75/100)                       $9,000,000

 

Total expenses= Depreciation + other expenses

$1,500,000 x 2 + $9,000,000 =   $12,000,000

 

Total revenue – total expenses = Net income or Profit

$12,000,000 – $12,000,000= $0

 

What were Brandywine’s 2007 net income, total profit margin, and cash flow?

 

The net income =                                                                                   $0

Total profit margin=                                                                            $0

Cash flow=                                                                                                 $3,000,000

 

  1. Suppose the change has halved, rather than doubled, the firm’s depreciation expense. Now, what would be the impact on net income, total profit margin, and cash flow?

 

Net income = $12,000,000 – $9,000,000 – .75 = $2,250,000

Total profit margin = $2,250,000 / 12,000,000 = 0.188 = 18.8%

Cash flow = $2,250,000 + 0.75 = $3,000,000

 

 

Problem 4.5

 

BestCare HMO

Balance Sheet

June 30, 2011

(in thousands)

 

Assets

Current Assets:

Cash                                                                        $2,737

Net premiums receivable                                 $821

Supplies                                                                  $387

Total current assets                             $3,945

Net Property and equipment                           $5,924

Total Assets                                                           $9,869

 

Liabilities and Net Assets

Accounts payable-medical service                 $2,145

Accrued Expenses                                                $929

Notes Payable                                                        $382

Total Current Liabilities                        $3,456

Long –term debt                                                    $4,295

Total liabilities                                                         $7,751

Net assets-unrestricted equity                                        $2,118

Total Liabilities and Net Assets                                       $9,869

 

 

  1. How does this balance sheet differ from the one presented in Exhibit 4.1 for Sunnyvale?

The balance sheet differences between BestCare and Sunnyvale are:

-BestCare doesn’t have long and short-term investments.

-Sunnyvales short and long-term investments cover 58,059,000 of their assets.

-BestCare has unrestricted net assets

 

  1. What is BestCare’s net working capital for 2011?

Net working capital = Total current assets  – total current liabilities

$xxx– $3,456,000

net working capital = xxx

 

PLACE YOUR ORDER AT WWW.WRITERBAY.NET/ORDER

 

  1. What is BestCare’s debt ratio? How does it compare with Sunnyvale’s debt ratio?

Debt ratio = total debt / total assets

$7751/$9869=0.7854 = 78.54%

The debt ratio is less than Sunnyvale’s.

 

 

Problem 4.6

 

Green Valley Nursing Home, Inc.

Balance Sheet

December 31, 2011

 

 

 

Assets

 

Current Assets:

Cash                                                                                               $ 105,737

Investments                                                                              $ 200,000

Net patient accounts receivable                                      $ 215,600

Supplies                                                                                       $ 87,655

Total current assets                                               $ 608,992

Property and equipment                                                                   $ 2,250,000

Less accumulated depreciation                                                      $ 356,000

Net property and equipment                                            $ 1,894,000

Total assets                                                                                              $ 2,502,992

 

Liabilities and Shareholders’ Equity

 

Current Liabilities:

Accounts payable                                                                    $ 72,250

Accrued expenses                                                                  $ 192,900

Notes payable                                                                           $ 180,000

Total current liabilities                                         $ 445,150

Long-term debt                                                                                       $ 1,700,000

 

Shareholders’ Equity:

Common stock, $10 par value                                          $ 100,000

Retained earnings                                                                  $ 257,842

Total shareholders’ equity                                  $ 357,842

Total liabilities and shareholders’ equity                   $ 2,502,992

 

  1. How does this balance sheet differ from the ones presented in Exhibit 4.1 and problem 4.5?

This balance sheet has net premiums receivable line. Those are premiums that are collected through accounts receivable. The notation of a premium signifies a capitation system that receives premiums up front before services are performed.

 

  1. What is Green Valley’s net working capital for 2011?

Net working capital = Total current assets  – total current liabilities

$608,992 – $72,250

Net working Capital = $536,742

 

  1. What is Green Valley’s debt ratio? How does it compare with the debt ratios for Sunnyvale and BestCare?

Debt ratio = total debt / total assets

445,150 / $2,502,992 = 0.1778 = 17.78 %

The debt ratio is less in comparison.

 

 

 

Austral and Pacific Realms

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Topic 1. Austral and Pacific Geography in the News

For this discussion, find a recent news article (within the past 12 months) that describes the latest developments in a conflict, issue, or other major event in this the Austral or Pacific realm. Provide a brief summary of the conflict/issue/event that your article describes, and your own analysis of how this issue might affect the realm, and might be resolved.

Be sure that the topic of the news article has some connection with the geographical issues and concepts we’ve been discussing, and be sure to highlight these connections in your discussion.

 

Remember that your article summary must be in your own words to avoid plagiarism.

Chapter 13 Basic Multiple Regression Analysis

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File: Ch13, Chapter 13: Basic Multiple Regression Analysis

 

 

 

True/False

 

 

 

 

  1. Regression analysis with one dependent variable and two or more independent variables is called multiple regression.

 

Ans: True

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. The model y = b 0+ b 1x1+ b 2x2 + e is a second-order regression model.

 

Ans: False

Response: See section 13.1 The Multiple Regression Model

Difficulty: Medium

 

 

 

  1. The model y = b 0+ b 1x1+ b 2x2 + b 3x3 + e is a first-order regression model.

 

Ans: True

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. In the multiple regression model y = b 0+ b 1x1+ b 2x2 + b 3x3 + e, the b coefficients of the x variables are called partial regression coefficients.

 

Ans: True

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. In the model y = b 0+ b 1x1+ b 2x2 + b 3x3 + e, y is the independent variable.

 

Ans: False

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. In a multiple regression model, the partial regression coefficient of an independent variable represents the increase in the y variable when that independent variable is increased by one unit if the values of all other independent variables are held constant.

 

Ans: True

Response: See section 13.1 The Multiple Regression Model

Difficulty: Medium

 

 

 

  1. In the estimated multiple regression model y = b0+ b1x1+ b 2 x2 if the values of x1 and x2 are both increased by one unit, the value of y will increase by (b1+ b 2) units.

 

Ans: False

Response: See section 13.1 The Multiple Regression Model

Difficulty: Hard

 

 

 

  1. In the model y = b 0+ b 1x1+ b 2x2 + b 3x3 + e, e is a constant.

 

Ans: False

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. In the estimated multiple regression model y = b0+ b1x1+ b 2 x2 if the value of x1 is increased by 2 and the value of x2 is increased by 3 simultaneously, the value of y will increase by (2b1+ 3b 2) units.

 

Ans: False

Response: See section 13.1 The Multiple Regression Model

Difficulty: Hard

 

 

 

  1. Multiple t-tests are used to determine whether the overall regression model is significant.

 

Ans: False

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. The F test is used to determine whether the overall regression model is significant.

 

Ans: True

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. The F value that is used to test for the overall significance a multiple regression model is calculated by dividing the mean square regression (MSreg) by the mean square error (MSerr).

 

Ans: True

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. The F value that is used to test for the overall significance a multiple regression model is calculated by dividing the sum of mean squares regression (SSreg) by the sum of squares error (SSerr).

 

Ans: False

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

  1. The mean square error (MSerr) is calculated by dividing the sum of squares error (SSerr) by the number of observations in the data set (N).

 

Ans: False

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Medium

 

 

 

  1. The mean square error (MSerr) is calculated by dividing the sum of squares error (SSerr) by the number of error degrees of freedom (dferr).

 

Ans: True

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. In a multiple regression analysis with N observations and k independent variables, the degrees of freedom for the residual error is given by (N – k – 1).

 

Ans: True

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Medium

 

 

 

  1. In a multiple regression analysis with N observations and k independent variables, the degrees of freedom for the residual error is given by (N – k).

 

Ans: False

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Medium

 

 

 

  1. The standard error of the estimate of a multiple regression model is essentially the standard deviation of the residuals for the regression model.

 

Ans: True

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The standard error of the estimate of a multiple regression model is computed by taking the square root of the mean squares of error.

 

Ans: True

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Hard

 

 

 

  1. In a multiple regression model, the proportion of the variation of the dependent variable, y, accounted for the independent variables in the regression model is given by the coefficient of multiple correlation.

 

Ans: False

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

Multiple Choice

 

 

 

  1. A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). The response variable in this model is ______.
  2. a) batch size
  3. b) production shift
  4. c) production plant
  5. d) total cost
  6. e) variable cost

 

Ans: d

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, “shift” is ______.
  2. a) a response variable
  3. b) an independent variable
  4. c) a quantitative variable
  5. d) a dependent variable
  6. e) a constant

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, “batch size” is ______.
  2. a) a response variable
  3. b) an indicator variable
  4. c) a dependent variable
  5. d) a qualitative variable
  6. e) an independent variable

 

Ans: e

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The response variable in this model is _____.
  2. a) family size
  3. b) expenditures on groceries
  4. c) household income
  5. d) suburban
  6. e) household neighborhood

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The “neighborhood” variable in this model is ______.
  2. a) an independent variable
  3. b) a response variable
  4. c) a quantitative variable
  5. d) a dependent variable
  6. e) a constant

 

Ans: a

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A market analyst is developing a regression model to predict monthly household expenditures on groceries as a function of family size, household income, and household neighborhood (urban, suburban, and rural). The “income” variable in this model is ____.
  2. a) an indicator variable
  3. b) a response variable
  4. c) a qualitative variable
  5. d) a dependent variable
  6. e) an independent variable

 

Ans: e

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A human resources analyst is developing a regression model to predict electricity production plant manager compensation as a function of production capacity of the plant, number of employees at the plant, and plant technology (coal, oil, and nuclear). The response variable in this model is ______.
  2. a) plant manager compensation
  3. b) plant capacity
  4. c) number of employees
  5. d) plant technology
  6. e) nuclear

 

Ans: a

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A human resources analyst is developing a regression model to predict electricity production plant manager compensation as a function of production capacity of the plant, number of employees at the plant, and plant technology (coal, oil, and nuclear). The “plant technology” variable in this model is ______.
  2. a) a response variable
  3. b) a dependent variable
  4. c) a quantitative variable
  5. d) an independent variable
  6. e) a constant

 

Ans: d

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A human resources analyst is developing a regression model to predict electricity production plant manager compensation as a function of production capacity of the plant, number of employees at the plant, and plant technology (coal, oil, and nuclear). The “plant technology” variable in this model is ______.
  2. a) a qualitative variable
  3. b) a dependent variable
  4. c) a response variable
  5. d) an indicator variable
  6. e) an independent variable

 

Ans: a

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A real estate appraiser is developing a regression model to predict the market value of single family residential houses as a function of heated area, number of bedrooms, number of bathrooms, age of the house, and central heating (yes, no). The response variable in this model is _______.
  2. a) heated area
  3. b) number of bedrooms
  4. c) market value
  5. d) central heating
  6. e) residential houses

 

Ans: c

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A real estate appraiser is developing a regression model to predict the market value of single family residential houses as a function of heated area, number of bedrooms, number of bathrooms, age of the house, and central heating (yes, no). The “central heating” variable in this model is _______.
  2. a) a response variable
  3. b) an independent variable
  4. c) a quantitative variable
  5. d) a dependent variable
  6. e) a constant

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A real estate appraiser is developing a regression model to predict the market value of single family residential houses as a function of heated area, number of bedrooms, number of bathrooms, age of the house, and central heating (yes, no). The “central heating” variable in this model is _______.
  2. a) a response variable
  3. b) an indicator variable
  4. c) a dependent variable
  5. d) a qualitative variable
  6. e) an independent variable

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. The multiple regression formulas used to estimate the regression coefficients are designed to ________________.
  2. a) minimize the total sum of squares (SST)
  3. b) minimize the sum of squares of error (SSE)
  4. c) maximize the standard error of the estimate
  5. d) maximize the p-value for the calculated F value
  6. e) minimize the mean error

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 616.6849 154.5534 3.990108 0.000947
x1 -3.33833 2.333548 -1.43058 0.170675
x2 1.780075 0.335605 5.30407 5.83E-05

 

Source df SS MS F p-value
Regression 2 121783 60891.48 14.76117 0.000286
Residual 15 61876.68 4125.112
Total 17 183659.6

 

The regression equation for this analysis is ____________.

  1. a) y = 616.6849 + 3.33833 x1+ 1.780075 x2
  2. b) y = 154.5535 – 1.43058 x1+ 5.30407 x2
  3. c) y = 616.6849 – 3.33833 x1- 1.780075 x2
  4. d) y = 154.5535 + 2.333548 x1 + 0.335605 x2
  5. e) y = 616.6849 – 3.33833 x1+ 1.780075 x2

 

Ans: e

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 616.6849 154.5534 3.990108 0.000947
x1 -3.33833 2.333548 -1.43058 0.170675
x2 1.780075 0.335605 5.30407 5.83E-05

 

Source df SS MS F p-value
Regression 2 121783 60891.48 14.76117 0.000286
Residual 15 61876.68 4125.112
Total 17 183659.6

 

The sample size for this analysis is ____________.

  1. a) 19
  2. b) 17
  3. c) 34
  4. d) 15
  5. e) 18

 

Ans: e

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 616.6849 154.5534 3.990108 0.000947
x1 -3.33833 2.333548 -1.43058 0.170675
x2 1.780075 0.335605 5.30407 5.83E-05

 

Source df SS MS F p-value
Regression 2 121783 60891.48 14.76117 0.000286
Residual 15 61876.68 4125.112
Total 17 183659.6

 

Using a = 0.01 to test the null hypothesis H0: b 1 = b 2 = 0, the critical F value is ____.

  1. a) 68
  2. b) 6.36
  3. c) 8.40
  4. d) 6.11
  5. e) 3.36

 

Ans: b

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 616.6849 154.5534 3.990108 0.000947
x1 -3.33833 2.333548 -1.43058 0.170675
x2 1.780075 0.335605 5.30407 5.83E-05

 

Source df SS MS F p-value
Regression 2 121783 60891.48 14.76117 0.000286
Residual 15 61876.68 4125.112
Total 17 183659.6

 

Using a = 0.05 to test the null hypothesis H0: b1 = 0, the critical t value is ____.

  1. a) ± 1.753
  2. b) ± 2.110
  3. c) ± 2.131
  4. d) ± 1.740
  5. e) ± 2.500

 

Ans: c

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 616.6849 154.5534 3.990108 0.000947
x1 -3.33833 2.333548 -1.43058 0.170675
x2 1.780075 0.335605 5.30407 5.83E-05

 

Source df SS MS F p-value
Regression 2 121783 60891.48 14.76117 0.000286
Residual 15 61876.68 4125.112
Total 17 183659.6

 

These results indicate that ____________.

  1. a) none of the predictor variables are significant at the 5% level
  2. b) each predictor variable is significant at the 5% level
  3. c) x1is significant at the 5% level
  4. d) x2is significant at the 5% level
  5. e) the intercept is not significant at 5% level

 

Ans: d

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 616.6849 154.5534 3.990108 0.000947
x1 -3.33833 2.333548 -1.43058 0.170675
x2 1.780075 0.335605 5.30407 5.83E-05

 

Source df SS MS F p-value
Regression 2 121783 60891.48 14.76117 0.000286
Residual 15 61876.68 4125.112
Total 17 183659.6

 

For x1= 60 and x2 = 200, the predicted value of y is ____________.

  1. a) 1,173.00
  2. b) 772.40
  3. c) 460.97
  4. d) 615.13
  5. e) 987.78

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 752.0833 336.3158 2.236241 0.042132
x1 11.87375 5.32047 2.231711 0.042493
x2 1.908183 0.662742 2.879226 0.01213

 

Source df SS MS F p-value
Regression 2 203693.3 101846.7 6.745406 0.010884
Residual 12 181184.1 15098.67
Total 14 384877.4

 

The regression equation for this analysis is ____________.

  1. a) y = 752.0833 + 11.87375 x1+ 1.908183 x2
  2. b) y = 752.0833 + 336.3158 x1+ 2.236241 x2
  3. c) y = 336.3158 + 5.32047 x1+ 0.662742 x2
  4. d) y = 2.236241 + 2.231711 x1 + 2.879226 x2
  5. e) y = 2.236241 + 2.231711 x1- 2.879226 x2

 

Ans: a

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 752.0833 336.3158 2.236241 0.042132
x1 11.87375 5.32047 2.231711 0.042493
x2 1.908183 0.662742 2.879226 0.01213

 

Source df SS MS F p-value
Regression 2 203693.3 101846.7 6.745406 0.010884
Residual 12 181184.1 15098.67
Total 14 384877.4

 

The sample size for this analysis is ____________.

  1. a) 12
  2. b) 15
  3. c) 14
  4. d) 28
  5. e) 24

 

Ans: b

Response: See section 13.1 The Multiple Regression Model

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 752.0833 336.3158 2.236241 0.042132
x1 11.87375 5.32047 2.231711 0.042493
x2 1.908183 0.662742 2.879226 0.01213

 

Source df SS MS F p-value
Regression 2 203693.3 101846.7 6.745406 0.010884
Residual 12 181184.1 15098.67
Total 14 384877.4

 

Using a = 0.05 to test the null hypothesis H0: b1 = b2 = 0, the critical F value is ____.

  1. a) 74
  2. b) 3.89
  3. c) 4.75
  4. d) 4.60
  5. e) 2.74

 

Ans: b

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 752.0833 336.3158 2.236241 0.042132
x1 11.87375 5.32047 2.231711 0.042493
x2 1.908183 0.662742 2.879226 0.01213

 

Source df SS MS

F

 p-value
Regression 2 203693.3 101846.7 6.745406 0.010884
Residual 12 181184.1 15098.67
Total 14 384877.4

 

Using a = 0.10 to test the null hypothesis H0: b2 = 0, the critical t value is ____.

  1. a) ±1.345
  2. b) ±1.356
  3. c) ±1.761
  4. d) ±2.782
  5. e) ±1.782

 

Ans: e

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 752.0833 336.3158 2.236241 0.042132
x1 11.87375 5.32047 2.231711 0.042493
x2 1.908183 0.662742 2.879226 0.01213

 

Source df SS MS F p-value
Regression 2 203693.3 101846.7 6.745406 0.010884
Residual 12 181184.1 15098.67
Total 14 384877.4

 

These results indicate that ____________.

  1. a) none of the predictor variables are significant at the 5% level
  2. b) each predictor variable is significant at the 5% level
  3. c) x1is the only predictor variable significant at the 5% level
  4. d) x2is the only predictor variable significant at the 5% level
  5. e) the intercept is not significant at the 5% level

 

Ans: b

Response: See section 13.2 Significance Tests of the Regression Model and its Coefficients

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 752.0833 336.3158 2.236241 0.042132
x1 11.87375 5.32047 2.231711 0.042493
x2 1.908183 0.662742 2.879226 0.01213

 

Source df SS MS

F

 p-value
Regression 2 203693.3 101846.7 6.745406 0.010884
Residual 12 181184.1 15098.67
Total 14 384877.4

 

For x1= 60 and x2 = 200, the predicted value of y is ____________.

  1. a) 24
  2. b) 711.98
  3. c) 788.09
  4. d) 1,846.15
  5. e) 2,546.98

 

Ans: d

Response: See section 13.1 The Multiple Regression Model

Difficulty: Medium

 

 

 

  1. In regression analysis, outliers may be identified by examining the ________.
  2. a) coefficient of determination
  3. b) coefficient of correlation
  4. c) p-values for the partial coefficients
  5. d) residuals
  6. e) R-squared value

 

Ans: d

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.

 

Source df SS MS F p
Regression 700
Error
Total 1000

 

The number of degrees of freedom for regression is __________.

  1. a) 1
  2. b) 4
  3. c) 34
  4. d) 30
  5. e) 35

 

Ans: b

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.

 

Source df SS MS F p
Regression 700
Error
Total 1000

 

The number of degrees of freedom for error is __________.

  1. a) 1
  2. b) 4
  3. c) 34
  4. d) 30
  5. e) 35

 

Ans: d

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.
Source df SS MS F p
Regression 700
Error
Total 1000

 

The MSR value is __________.

  1. a) 700.00
  2. b) 350.00
  3. c) 233.33
  4. d) 175.00
  5. e) 275.00

 

Ans: d

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.
Source df SS MS F p
Regression 700
Error
Total 1000

 

The MSE value is __________.

  1. a) 8.57
  2. b) 8.82
  3. c) 10.00
  4. d) 75.00
  5. e) 20.00

 

Ans: c

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.
Source df SS MS F p
Regression 700
Error
Total 1000

 

The observed F value is __________.

  1. a) 17.50
  2. b) 2.33
  3. c) 0.70
  4. d) 0.43
  5. e) 0.50

 

Ans: a

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.
Source df SS MS F p
Regression 700
Error
Total 1000

 

The value of the standard error of the estimate se is __________.

  1. a) 13.23
  2. b) 3.16
  3. c) 17.32
  4. d) 26.46
  5. e) 10.00

 

Ans: b

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.
Source df SS MS F p
Regression 700
Error
Total 1000

 

The R2 value is __________.

  1. a) 0.80
  2. b) 0.70
  3. c) 0.66
  4. d) 0.76
  5. e) 0.30

 

Ans: b

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis with n = 35 and four independent variables.
Source df SS MS F p
Regression 700
Error
Total 1000

 

The adjusted R2 value is __________.

  1. a) 0.80
  2. b) 0.70
  3. c) 0.66
  4. d) 0.76
  5. e) 0.30

 

Ans: c

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The sample size for the analysis is __________.

  1. a) 30
  2. b) 25
  3. c) 10
  4. d) 5
  5. e) 31

 

Ans: e

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The number of independent variables in the analysis is __________.

  1. a) 30
  2. b) 25
  3. c) 1
  4. d) 5
  5. e) 2

 

Ans: d

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The MSR value is __________.

  1. a) 20
  2. b) 400
  3. c) 2000
  4. d) 500
  5. e) 30

 

Ans: b

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The SSE value is __________.

  1. a) 20
  2. b) 400
  3. c) 2000
  4. d) 500
  5. e) 2500

 

Ans: d

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Easy

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The MSE value is __________.

  1. a) 20
  2. b) 400
  3. c) 2000
  4. d) 500
  5. e) 100

 

Ans: a

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The observed F value is __________.

  1. a) 20
  2. b) 400
  3. c) 2000
  4. d) 500
  5. e) 10

 

Ans: a

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The value of the standard error of the estimate se is __________.

  1. a) 20.00
  2. b) 44.72
  3. c) 4.47
  4. d) 22.36
  5. e) 12.47

 

Ans: c

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The R2 value is __________.

  1. a) 0.80
  2. b) 0.70
  3. c) 0.66
  4. d) 0.76
  5. e) 1.00

 

Ans: a

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. The following ANOVA table is from a multiple regression analysis.

 

Source df SS MS F p
Regression 5 2000
Error 25
Total 2500

 

The adjusted R2 value is __________.

  1. a) 0.80
  2. b) 0.70
  3. c) 0.66
  4. d) 0.86
  5. e) 0.76

 

Ans: e

Response: See section 13.3 Residuals, Standard Error of the Estimate, and R2

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 624.5369 78.49712 7.956176 6.88E-06
x1 8.569122 1.652255 5.186319 0.000301
x2 4.736515 0.699194 6.774248 3.06E-05

 

Source df SS MS F p-value
Regression 2 1660914 830457.1 58.31956 1.4E-06
Residual 11 156637.5 14239.77
Total 13 1817552

 

These results indicate that ____________.

  1. a) none of the predictor variables are significant at the 5% level
  2. b) each predictor variable is significant at the 5% level
  3. c) x1is the only predictor variable significant at the 5% level
  4. d) x2is the only predictor variable significant at the 5% level
  5. e) the intercept is not significant at 5% level

 

Ans: b

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 624.5369 78.49712 7.956176 6.88E-06
x1 8.569122 1.652255 5.186319 0.000301
x2 4.736515 0.699194 6.774248 3.06E-05

 

Source df SS MS F p-value
Regression 2 1660914 830457.1 58.31956 1.4E-06
Residual 11 156637.5 14239.77
Total 13 1817552

 

For x1= 30 and x2 = 100, the predicted value of y is ____________.

  1. a) 77
  2. b) 1,173.00
  3. c) 1,355.26
  4. d) 615.13
  5. e) 6153.13

 

Ans: c

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 624.5369 78.49712 7.956176 6.88E-06
x1 8.569122 1.652255 5.186319 0.000301
x2 4.736515 0.699194 6.774248 3.06E-05

 

Source df SS MS F p-value
Regression 2 1660914 830457.1 58.31956 1.4E-06
Residual 11 156637.5 14239.77
Total 13 1817552

 

The coefficient of multiple determination is ____________.

  1. a) 0592
  2. b) 0.9138
  3. c) 0.1149
  4. d) 0.9559
  5. e) 1.0000

 

Ans: b

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept 624.5369 78.49712 7.956176 6.88E-06
x1 8.569122 1.652255 5.186319 0.000301
x2 4.736515 0.699194 6.774248 3.06E-05

 

Source df SS MS F p-value
Regression 2 1660914 830457.1 58.31956 1.4E-06
Residual 11 156637.5 14239.77
Total 13 1817552

 

The adjusted R2 is ____________.

  1. a) 0.9138
  2. b) 0.9408
  3. c) 0.8981
  4. d) 0.8851
  5. e) 0.8891

 

Ans: c

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

The regression equation for this analysis is ____________.

  1. a) y = 302689 + 1153309 x1+ 1455998 x2
  2. b) y = -139.609 + 24.24619 x1+ 32.10171 x2
  3. c) y = 2548.989 + 22.25267 x1+ 17.44559 x2
  4. d) y = -0.05477 + 1.089586 x1 + 1.840105 x2
  5. e) y = 0.05477 + 1.089586 x1+ 1.840105 x2

 

Ans: b

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

The sample size for this analysis is ____________.

  1. a) 17
  2. b) 13
  3. c) 16
  4. d) 11
  5. e) 15

 

Ans: c

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Easy

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

Using a = 0.01 to test the null hypothesis H0: b 1 = b 2 = 0, the critical F value is ____.

  1. a) 99
  2. b) 5.70
  3. c) 1.96
  4. d) 4.84
  5. e) 6.70

 

Ans: e

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

Using a = 0.01 to test the null hypothesis H0: b2 = 0, the critical t value is ____.

  1. a) ± 1.174
  2. b) ± 2.093
  3. c) ± 2.131
  4. d) ± 4.012
  5. e) ± 3.012

 

Ans: e

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

These results indicate that ____________.

  1. a) none of the predictor variables are significant at the 5% level
  2. b) each predictor variable is significant at the 5% level
  3. c) x1is the only predictor variable significant at the 5% level
  4. d) x2is the only predictor variable significant at the 5% level
  5. e) all variables are significant at 5% level

 

Ans: a

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

For x1= 40 and x2 = 90, the predicted value of y is ____________.

  1. a) 77
  2. b) 1,173.00
  3. c) 1,355.26
  4. d) 3,719.39
  5. e) 1,565.75

 

Ans: d

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

The coefficient of multiple determination is ____________.

  1. a) 2079
  2. b) 0. 0860
  3. c) 0.5440
  4. d) 0.7921
  5. e) 0.5000

 

Ans: a

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

  1. A multiple regression analysis produced the following tables.

 

Predictor Coefficients Standard Error t Statistic p-value
Intercept -139.609 2548.989 -0.05477 0.957154
x1 24.24619 22.25267 1.089586 0.295682
x2 32.10171 17.44559 1.840105 0.08869

 

Source df SS MS F p-value
Regression 2 302689 151344.5 1.705942 0.219838
Residual 13 1153309 88716.07
Total 15 1455998

 

The adjusted R2 is ____________.

  1. a) 0.2079
  2. b) 0.0860
  3. c) 0.5440
  4. d) 0.7921
  5. e) 1.0000

 

Ans: b

Response: See section 13.4 Interpreting Multiple Regression Computer Output

Difficulty: Medium

 

 

 

Find factors that could be affecting how nurses listen to their patients

/in /by

Explore review of literature about the “perception” that a person believes another is listening.

Nationally for the question “listen carefully on the HCAPHS,” 20% of the people do not believe their nurses are listening to them. At Emory midtown, 25-30% of patients consider their nurses do not listen to them both on the Med-Surg and mother-baby units.

1.     what do patients perceive as being listened to or what is the “perception” that a person believes another is listening?

2.     Find factors that could be affecting how nurses listen to their patients.

 

What copyrights are, how to obtain them, and how they differ from trademarks

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Name:                                                                         PMU ID:                                            

 

 

 

 

Course: Legal Environment of Business

Final Exam – Spring 2021

 

Number of Exam Pages                                 Time Allowed                           

 

 

 

 

 

 

 

 

 

 

Mapping Exam Question to CLOs Max Grade Weight Student Grade
CLO1
CLO2
CLO3
CLO4
CLO5
CLO7
 

 

  

Total

 100%

 

 

 

Note: All exam questions are corrected in accordance with the attached rubrics. Same rubrics are followed across all section of the course.

 

  1. Describe how the common law – legal model/system differs from the civil law – legal model/system. Identify some of the better-known nations with both systems. (15%)

 

_________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

 

  1. Define ethics and explain the importance of good ethics for business people and

business organizations. Explain how both individuals and institutions can be viewed as ethical or unethical. (20%)

 

_________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

 

  1. Explain the basic ways to carry on business: what are the legal forms of business?

(15%)

 

_________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

 

  1. Define contract and explain what constitutes a valid legal agreement? (20%)

 

_________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

 

 

  1. What copyrights are, how to obtain them, and how they differ from trademarks? (20%)

 

__________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________

6.ZYCOO, known as a perfume manufacturer made fantastic floral-scented fragrance that quickly became very popular product. Consumers associated the floral scent with ZYCOO and repeatedly asked for spin-off products, such as home air fresheners and bath products. ZYCOO consulted its in-house counsel about whether it could register a trademark in the scent.(10%)

How should in-house counsel advise the manufacturer?

  1. The manufacturer may register the scent because consumers’ opinions about the scent are positive.
  2. The manufacturer may not register the scent because the scent is essential to the use of the perfume.
  3. The manufacturer may not register the scent because scents cannot be protected with a trademark.
  4. The manufacturer may register the scent because it is source-identifying.

 

WK4 -Popular Culture vs. High Culture?

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What are the main arguments made in the course materials assigned for this week about the relationship between social class and cultural consumption? Do you think there are value differences today between popular culture and high culture? Why/why not? Include specific examples to support your argument.

Propose a viable model for approaching the problem in your jurisdiction

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This assignment is the major decision point for your integrative project. In this component, you will:

  • Synthesize the research from your literature review to complete a demographic analysis of the study groups or populations affected by the problem. You must evaluate valid, reliable, and relevant criminal justice research to critically examine the groups or populations. It is important to consider multicultural perspectives in your examination and in the selection of sources you use to support your analysis.
  • Describe alternative solutions to the problem and the impact of each solution on criminal justice policy, based on your demographic analysis.
  • Propose a viable model for approaching the problem in your jurisdiction or community that promotes the evolution of criminal justice policy and advances the discipline.
  • Describe any personal biases and social and professional ethical dilemmas that might arise as you take action.
  • Determine how you would evaluate and measure the success of your model if it were implemented as a solution to the problem.

In discussing the implementation of your model, synthesize the historical and contemporary criminal justice policies related to your problem, given your demographic analysis, and propose how your model can influence social change and promote community improvements. Keep in mind, social change necessitates policy change and affects community improvements. Conversely, criminal justice policy must recognize the dynamics of social change in order to influence it and promote community improvements.

  • Describe how you would communicate the proposed model itself, and the plan for evaluating its efficacy, to the various audiences affected by the problem (such as political, community, institutional, or funding sources).
  • Analyze how the model relates to the existing, multiple professional standards that may impact its implementation, efficacy, and influence on policy.
  • Describe your plan to communicate how the model relates to the professional standards for each audience affected by the problem.

Assignment Requirements

  • Written communication: Written communication is free of errors that detract from the overall message.
  • Style and formatting: Be sure to use proper APA style for your in-text citations and references. Also, use proper APA formatting to layout your paper (for example, running headers, double-spaced and indented paragraphs, Times Roman 12-point font, and 1-inch margins). Refer to APA Style and Format for more information.
  • Number of pages: Your assignment must be a minimum of five pages. This page requirement does not include the list of references or any appendices you may include.
  • Resources: Your ideas must be supported with recent, scholarly sources that are properly cited and referenced in APA Style.
  • Writing assistance is available through the Capella Writing Center or Smarthinking, the free, online writing tutorial and review service.

Refer to the Demographic Analysis and Proposed Model Scoring Guide to ensure you understand the grading criteria for this assignment.

Synthesizes research from the literature review to complete a demographic analysis of the study groups or populations affected by a problem in a jurisdiction or community. Identifies knowledge gaps, unknowns, missing information, unanswered questions, or areas of uncertainty (where further information could improve the analysis).

Describes alternative solutions to a problem in a jurisdiction or community and the impact of each solution on criminal justice policy. Evaluates the relevance, currency, sufficiency, and trustworthiness of the evidence.

Proposes a viable model for approaching a problem in a jurisdiction or community that promotes the evolution of criminal justice policy and advances the discipline. Identifies criteria that could be used to evaluate effectiveness of the model.

Determines how to best evaluate and measure the success of a proposed model if it were implemented as a solution to a problem affecting a jurisdiction or community and impartially considers conflicting data and other perspectives.

Describes personal biases and social and professional ethical dilemmas that might arise as action is taken and identifies assumptions on which the biases are based.

Writes clearly and logically, with correct use of spelling, grammar, punctuation, and mechanics; No notable errors in spelling, punctuation, or grammar. Uses relevant evidence to support a central idea.

Correctly formats paper, citations, and references using APA style. Citations are free from all errors.