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1) Which of the following statements about the regression standard error hold TRUE? I. The regression standard error reflects the variation of the y-values about

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1) Which of the following statements about the regression standard error hold TRUE? I. The regression standard error reflects the variation of the y-values about the regression line. II. The regression standard error is an estimate of the model standard deviation . III. The smaller the regression standard error is, the better the model fits the data and the more precise inference about the regression model.

Group of answer choices

I

I and II

II and III

I, II, and III

2) In the regression equation, the intercept term represents ____

Group of answer choices

the slope of the line.

any value of the independent variable that is selected.

the value of the dependent variable when the independent variable equals zero.

the standard error of the regression.

3) Consider the following generalized regression equation,= a +bX. Suppose we estimate b =-0.3. What does that mean?

Group of answer choices

b is the slope; it implies that for every one-unit change in the X variable, the y variable increases by 0.3

b is the slope; it implies that for every one-unit change in the X variable, the y variable decreases by 0.3

b is the intercept, and it implies that when X=0,= 0.3

b is the standard error of the regression and indicates how close the parameter estimates are to zero.

4)

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Question 4 Assume the below least squares equation. What does the value of 30 in the equation indicate? y = 30 + 5 X O When X = 1, = 20. O X increases by 30 for each unit increase in Y. O Y increases by 30, for each unit increase in X. O When X = 0, $ = 30.Question 5 Assume the below least squares equation. What is the predicted value of y? 9 = 2,000 100 x 0 5,734 O 750 0 1,500 0 1,750 Set up 1: Figure 1 shows the box office revenue (Box Office) and the production budget (Budget) for the top grossing films in 2021. (Both are measured in millions of USD.) We hypothesize that the box office revenues are a function of the production budget of the movie. Table 1 provides some useful summary statistics. Figure 1: Scatter Plot for Box Office v. Budget Top Grossing Movies 51.600 $1,400 $1.200 $1,000 Box Office ('000,000$) .. 2 . .. . i 100 150 200 Budget ('000,000s) Table 1 n= Mean Budget 82.88 Standard Deviation Budget 64.64 Mean Box Office 201.98 Standard Deviation Box Office 289.38 What is the independent variable in this analysis? O Budget Box Office O Budget minus Box Office O There is no defendant variable.Question 11 Below is the ANOVA from the data in Set up_1. TABLE 2: ANOVA FOR BOX OFFICE AND BUDGET DATA df 55 MS F Significance F Regression 1 1269098499 1269098 22.06674 2.82469E-05 Residual 42 2415496873 57511.83 Total 43 3684595.373 What is the standard error of the regression (estimate)? (Assume this is a sample.) 0 -239.82 0 237.01 0 239.82 0 3.71 Question 16 Table 3 is the (rounded) data from the Excel output for Set up 1. TABLE 3 Coefficients Standard Error Intercept -15.76 58.79 X Variable 1 2.63 0.56 What is "X Variable 1"? O The dependent variable, in this case Box Office O The independent variable, in this case Budget O The dependent variable, in this case Budget The independent variable, in this case Box Office

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