A CEO of a large pharmaceutical company would like to determine if he should be placing more money allotted in the budget next year for television advertising of a new drug marketed for controlling asthma. He wonders whether there is a strong relationship between the amount of money spent on television advertising for this new d
Discussion of multiple regression with the topics from Dielman Terry 'Applied Regression Analysis' - A 2nd course in Bus. and Economic Statistics. Topics (title of chapters) to cover: - Multiple regression analysis - Fitting curves to data - Assessing the assumptions of the regression model - Using indicator and interact
The owner of Maumee Motors wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at Maumee Motors during the last year. A). If we want to estimate selling price based on the age of the car, which variable is the dependant variable and which is th
The following data represent 15 quarters of manufacturing capacity utilization (in percentages) QTR/YR Utilization 1/2000 82.5 2/2000 81.3 3/2000 81.3 4/2000 79.0 1/2001 76.6 2/2001 78.0 3/2001 78.4 4/2001 78.0 1/2002 78.8 2/2002 78.7
1. Variables x and y each have standard deviations of 20. Their correlation is 0.6. The best fit line passes through the Y axis at Y = 40. Write the regression line. If a subject is 10 on x, what do you predict for Y? 2. You are looking through a book of new car ratings, and you decide to see how car weight influences EPA
Sales and Advertising expenses are used for the simple regression data attached. Sales is the dependent variable and Advertising Expense is the independent variable. The results are on the spreadsheet, with the relevant items in boldface. In practical terms, - How do I convert the above information to an equation I can
#1) Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged values she came up with the following: 3) Multiple R = 0.755 4) R-square =
Please define correlation and regression. Describe a management or business-related scenario where a researcher might be interested in whether a number of variables are correlated (without any assumptions about causation). Identify five or more variables that might be tested using a correlation matrix (and perhaps one of the tes
This posting has 5 examples of how to calculate a coefficient of correlation (r), coefficient of determination (r^2), regression equation, and weighted moving average. 1. The following sample observations were randomly selected. [table of data] - SEE ATTACHMENT Determine the coefficient of correlation and the coefficien
(See attached file for full problem description) --- Exercises 2. The following sample observations were randomly selected. Determine the coefficient of correlation and the coefficient of determination. Interpret. 3. Bi-lo Appliance Stores has outlets in several large metropolitan areas. The general sales manager
A group of management trainees was hired ten years ago at the same entry salary. A manager wants to determine why some of the former trainees are now making much higher salaries than others. How might a manager use multiple regression to answer this question? Assuming that salary is the dependent variable, suggest some independe
Please complete the following 5 questions in a Microsoft Word file: 1. When is it appropriate to use a time series approach to a business setting? When can it be applied to project management? 2. What are examples where control charts are used in your workplace to monitor quality control? What are the goals and objectives
A. Laura wanted to build a multiple regression model based on advertising expenditures and the company's price index. Based on the selection of all normal values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged values she came up with the following: 3) Multiple R =
(See attached file for full problem description with diagrams) --- 2. The following sample observations were randomly selected. Determine the coefficient of correlation and the coefficient of determination. Interpret. 3. Bi-lo Appliance Stores has outlets in several large metropolitan areas. The general sales manager
Need guidance on how to approach a statistics paper. Problem: utilize statistics to solve a business related problem. The synopsis should include a discussion of the specific problem, the research methodology used, the quantitative and qualitative tools employed in the study, and the benefit and limitations of the research stud
1. Can you think of an example where analysis of simple-linear and multiple regression analysis can be used? How is regression analysis being used in the financial industry, or how should it be used to formulate strategies? 2. What are examples in which regression analysis is used for forecasting? 3. What is correlation analys
We expect that students who do well on the midterm exam in a course will usually also do well on the final exam. Gary Smith of Pomona College looked at the exam scores of all 346 students who took his statistics class over a 10-year period. *The least-squares line for predicting final exam score from midterm exam score was y
Explain how Charter Communications, a broadband company, uses one or more forecasting methods (e.g., seasonal, Delphi, technological, time series), to forecast demand under conditions of uncertainty.
On multiple choice, check any appropriate answers. For any hypothesis tests, use a .05 level of significance. Barrel temp. (in oF) Mold temp. (in oF) Injection pres. (in psi) Strength (psi) 320 100 7000 3877 320 100 5000 3901 320 100 3000 4010 320 125 7000 3706 320 125 5000 3708 320 125 3000 4140 320 150 7000
A. Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal (i.e., concurrent) values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged (time lapse between independent and dependent) values she cam
A. What is linear regression? b. What can linear regression do for you - both in a general business sense and specifically to your place of employment, or circle of influence? c. What are some of the limitations of regression analysis? a. What is correlation analysis and why is it important to us when we are using regres
The director of an investing group believes that the sales generated by a broker is related to the number of new clients a broker brings to the firm. The director believes that a linear regression model would help in the forecasting of expected sales from the brokers. To build the model the director takes a random sample of 12
14. Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and th
A recent article in Buisness Week listed the best small companies. We are interested in the current results of the companies sales and earnings. A random sample of 12 companies was selected and the sales and earnings, in millions of dollars, are reported below. Company Sales Earnings
Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following: 1) Multiple R = 0.738 2) R-square = 0.546 By using lagged values she came up with the following: 3) Multiple R = 0.755 4) R-square
1. Laura wanted to build a multiple regression model based on advertising expenditures and price index. Based on the selection of all normal values she obtained the following: Multiple R=0.738, r2(r to the second power)=0.546 By using lagged values she came up with the following : Multiple R=0.755, r2=0.570 Explain the differ
Find a bivariate data set relating to your work with a sample size of 10 or more. a) Determine which is the dependent variable Y and which is the independent variable X. Explain your reasoning. b) Draw a scatterplot and indicate the relationship if any. Explain. c) Compute the least-squares regression equation. Show majo
Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and the Y
The owner of Maumee Ford-Mercury wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year. Car Age (years) Selling Price ($000) 1 9 8.1 2 7 6 3 11 3.6 4 12 4 5 8 5 6 7 10 7 8 7.6 8 11 8 9 10 8 10 12 6
Cellulon, a manufacturer of a home insulation, wants to develop guidelines for builders and consumers regarding the effects (1) of the thickness of the insulation in the attic of a home and (2) of the outdoor temperature on natural gas consumption. In the laboratory they varied the insulation thickness and temperature. A few of