QUESTION 10 Which of the following assumptions is not necessary for unbiasedness of a slope coefficient in a multiple regression model? Random sampling MLR 4 Homoskedasticity MLR1
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Q: Which of the following assumptions is not necessary for unbiasedness of a slope coefficient in a…
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- The owner of a new pizzeria in town wants to study the relationship between weekly revenue and advertising expenditures. All measures are recorded in thousands of dollars. The summary output for the regression model is given below.ANOVA dfdf SSSS MSMS F� Significance F� Regression 11 20.2147598620.21475986 20.2147598620.21475986 20.9811354520.98113545 0.0013268390.001326839 Residual 99 8.6712580048.671258004 0.963473110.96347311 Total 1010 28.8860178628.88601786 Step 1 of 3: What is the coefficient of determination for this model, R2�2? Round your answer to four decimal places.11:12 AA www-awn.aleks.com O REGRESSION AND CORRELA Computing the sample. OD O DO An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (denoted by x, in millions of dollars) and the resulting percentage increase in sales (denoted by y) following the campaign, were presented by the firm. A scatter plot of the data is shown in Figure 1. Also given are the products of the values for campaign cost and values for percentage increase in sales for each of the twelve campaigns. (These products, written in the column labelled "xy," may aid in calculations.) Campaign cost, Increase in sales, y (percent) xy (in milions o dollars) 3.71 6.73 24.9683 72 3.84 7.03 26.9952 2.18 6.40 13.952 3.06 6.94 21.2364 3.27 6.55 21.4185 1.50 6.28 9.42 2.25 6.57 14.7825 2.00 6.77 13.54 1.47 6.63 9.7461 3.58 6.91 24.7378 1.31 6.41 8.3971 Figure 1 3.01 6.59…The owner of a new pizzeria in town wants to study the relationship between weekly revenue and advertising expenditures. All measures are recorded in thousands of dollars. The summary output for the regression model is given below.ANOVA dfdf SSSS MSMS F� Significance F� Regression 11 20.2147598620.21475986 20.2147598620.21475986 20.9811354520.98113545 0.0013268390.001326839 Residual 99 8.6712580048.671258004 0.963473110.96347311 Total 1010 28.8860178628.88601786 Step 3 of 3: Which statistic is most appropriate for the pizzeria owner to determine the usefulness of the regression model and why?
- Big Time Corporation wanted to determine the relationship between its monthly operating costs and a potential cost driver, machine hours. The output of a regression analysis showed the following information (note: only a portion of the regression analysis results is presented here) SUMMARY OUTPUT Regression Statistics Multiple R 0.998041188 R Square 0.996086212 Adjusted R Square 0.994781616 Standard Error 917.1714273 Observations 5 ANOVA df SS MS F Significance F Regression 1 642276389.7 642276389.7 763.5208906 0.000104039 Residual 3 2523610.281 841203 427 Total 4 644800000 Coefficients Standard Errort Stat P-value Intercept 6679.617454 931.8558049 7.168080532 0.005592948 3714.03639 X Variable 9.796772265 0.354545968 27.63188178 0.000104039 8.66844876 What is variable cost per machine hour (rounded to the nearest cent)? OA. $6,679.62 OB. $917.17 OC. $9.80 OD. $.99 Lower 95% Upper 95.0% 9645.198517 10.92509577The owner of a new pizzeria in town wants to study the relationship between weekly revenue and advertising expenditures. All measures are recorded in thousands of dollars. The summary output for the regression model is given below.ANOVA dfdf SSSS MSMS F� Significance F� Regression 11 15.1540376815.15403768 15.1540376815.15403768 16.0586340516.05863405 0.0102486910.010248691 Residual 55 4.7183457924.718345792 0.943669160.94366916 Total 66 19.8723834719.87238347 Step 2 of 3 : What is the adjusted coefficient of determination for this model, R2a��2? Round your answer to four decimal placesWhat is the least-squares regression line with the point (9,13) included in the data set? Data Set x y 3 6 4 5 5 7 7 6 8 9 8 8 10 8 11 9 11 7 12 10 13 12 13 10 14 11 This is a reading assessment question. ..... y hat = ______x + ______ Type integers or decimals rounded to 4 decimal places as needed
- 2. Given the partial results from a linear regression model below, a sample size of 504, and a=0.05, a. What is the F-Statistic for the overall model? b. Is it statistically significant? Model Residuals Total Degrees of Freedom 3 Sum of Squares 12000 12288 Mean Square F-StatisticA researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis (Pearson's Correlation)The ANOVA summary table to the right is for a multiple regression model with six independent variables. Complete parts (a) through (e). a. Determine the regression mean square (MSR) and the mean square error (MSE). (Round to four decimal places as needed.) (Round to four decimal places as needed.) MSR= MSE = b. Compute the overall FSTAT test statistic. FSTAT (Round to two decimal places as needed.) C Source Regression Error Total Degrees of Sum of Freedom Squares 240 190 430 6 26 32
- True or False? If False, explain: a) The sample is the group of people on whom we wish to draw statistical interference. b) The Mean Square Error from a regression model is an example of a descriptive statistic. c) Getting enough power (so that we are able to conclude a non-zero slope in a scenario where the true slope is non-zero) is achieved primarily by increasing sample size.What is a residual for a multiple regression model and the data that is used to create it? Select one. Question 3 options: A statistic that explains the relationship between response and predictor variables The predicted value of the response variable using the multiple regression model A statistic that is used to evaluate the significance of the multiple regression model The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression modelQuestion: Consider a random sample of 20 observations of two variables X and Y. The following summary statistics are available: Ey,= 67, null= 135, 2x = %3D 467, and 2x,y,= 342. What is the slope of the fitted simple linear regression line?