1. BigShots, Inc. Is A Specialty ETailer That Operates 87 Catalog Web Sites On The Internet..
1.
BigShots, Inc. is a specialty etailer that operates 87 catalog Web sites on the Internet. Kevin Conn, Sales Director, feels that the style (color scheme, graphics, fonts, etc.) of a Web site may affect its sales. He chooses three levels of design style (neon, old world, and sophisticated) and randomly assigns six catalog Web sites to each design style. Analysis of Kevin’s data yielded the following ANOVA table.
Using = 0.05, the calculated F value is __________.
2.
BigShots, Inc. is a specialty etailer that operates 87 catalog Web sites on the Internet. Kevin Conn, Sales Director, feels that the style (color scheme, graphics, fonts, etc.) of a Web site may affect its sales. He chooses three levels of design style (neon, old world, and sophisticated) and randomly assigns six catalog Web sites to each design style. Analysis of Kevin’s data yielded the following ANOVA table.
Using = 0.05, the critical F value is __________.
3.
For the following ANOVA table, the df Treatment value is __________.
4.
Cindy Ho, VP of Finance at Discrete Components, Inc. (DCI), theorizes that the discount level offered to credit customers affects the average collection period on credit sales. Accordingly, she has designed an experiment to test her theory using four sales discount rates (0%, 2%, 4%, and 6%) by randomly assigning five customers to each sales discount rate. Cindy’s null hypothesis is __________.
5.
Suppose a researcher sets up a completely randomized design in which there are four different treatments and a total of 32 measurements in the study. For alpha = .05, the critical table F value is __________.
6.
A multiple regression analysis produced the following tables.
Predictor  Coefficients  Standard Error  tStatistic  pvalue  
Intercept  752.0833  336.3158  2.236241  0.042132  
x_{1}  11.87375  5.32047  2.231711  0.042493  
x_{2}  1.908183  0.662742  2.879226  0.01213  
Source  df  SS  MS  F  pvalue  
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 ____________.
7.
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 __________.
8.
A multiple regression analysis produced the following tables.
Predictor  Coefficients  Standard Error  tStatistic  pvalue  
Intercept  616.6849  154.5534  3.990108  0.000947  
x_{1}  3.33833  2.333548  1.43058  0.170675  
x_{2}  1.780075  0.335605  5.30407  5.83E05  
Source  df  SS  MS  F  pvalue  
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 H_{0}: _{1} = _{2} = 0, the critical F value is ____.
9.
A multiple regression analysis produced the following tables.
Predictor  Coefficients  Standard Error  tStatistic  pvalue  
Intercept  624.5369  78.49712  7.956176  6.88E06  
x_{1}  8.569122  1.652255  5.186319  0.000301  
x_{2}  4.736515  0.699194  6.774248  3.06E05  
Source  df  SS  MS  F  pvalue  
Regression  2  1660914  830457.1  58.31956  1.4E06  
Residual  11  156637.5  14239.77  
Total  13  1817552  
The adjusted R^{2} is ____________.
10.
Yvonne Yang, VP of Finance at Discrete Components, Inc. (DCI), wants a regression model which predicts the average collection period on credit sales. Her data set includes two qualitative variables: sales discount rates (0%, 2%, 4%, and 6%), and total assets of credit customers (small, medium, and large). The number of dummy variables needed for “sales discount rate” in Yvonne’s regression model is ________.
11.
Abby Kratz, a market specialist at the market research firm of Saez, Sikes, and Spitz, is analyzing household budget data collected by her firm. Abby’s dependent variable is monthly household expenditures on groceries (in $’s), and her independent variables are annual household income (in $1,000’s) and household neighborhood (0 = suburban, 1 = rural). Regression analysis of the data yielded the following table.
Coefficients  Standard Error  tStatistic  pvalue  
Intercept  19.68247  10.01176  1.965934  0.077667 
x_{1} (income)  1.735272  0.174564  9.940612  1.68E06 
x_{2} (neighborhood)  49.12456  7.655776  6.416667  7.67E05 
For a suburban household with $70,000 annual income, Abby’s model predicts monthly grocery expenditure of ________________.
12.
A multiple regression analysis produced the following tables.
Coefficients  Standard Error  tStatistic  pvalue  
Intercept  1411.876  762.1533  1.852483  0.074919 
x_{1}  35.18215  96.8433  0.363289  0.719218 
x_{1}^{2}  7.721648  3.007943  2.567086  0.016115 
df  SS  MS  F  
Regression  2  58567032  29283516  57.34861 
Residual  25  12765573  510622.9  
Total  27  71332605 
The regression equation for this analysis is ____________.
13.
Abby Kratz, a market specialist at the market research firm of Saez, Sikes, and Spitz, is analyzing household budget data collected by her firm. Abby’s dependent variable is monthly household expenditures on groceries (in $’s), and her independent variables are annual household income (in $1,000’s) and household neighborhood (0 = suburban, 1 = rural). Regression analysis of the data yielded the following table.
Coefficients  Standard Error  t Statistic  pvalue  
Intercept  19.68247  10.01176  1.965934  0.077667 
X_{1} (income)  1.735272  0.174564  9.940612  1.68E06 
X_{2} (neighborhood)  49.12456  7.655776  6.416667  7.67E05 
Abby’s model is ________________.
14.
An “all possible regressions” search of a data set containing 9 independent variables will produce ______ regressions.

question.docx
1. BigShots, Inc. Is A Specialty ETailer That Operates 87 Catalog Web Sites On The Internet.