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Suppose X, is a numerical variable and X, is a dummy variable with two categories and...
A researcher would like to predict the dependent variable YY from the two independent variables X1X1...
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2 for a sample of N=12N=12 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.01α=0.01. X1X1 X2X2 YY 51.1 40.5 48 53.5 41 51.5 53.2 62.8 42.8 52.3 52.7 51.3 64.1 60 48.8 56.8 62.1 50 61.6 88.1 39.2 60.4 62.5...
1. A variable that takes on the values of 0 or 1 and is used to...
1. A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical variables in a regression model is called a. an interaction b. a constant variable c. a dummy variable d. None of these alternatives is correct. 2. adjusted multiple coefficient of determination is adjusted for a. the number of dependent variables b. the number of independent variables c. the number of equations d. detrimental situations 3. A variable such as...
Box office Example with 2 Dummy variables: Let us define two dummy variables First yr box...
Box office Example with 2 Dummy variables: Let us define two dummy variables First yr box Total Prod Dummy Dummy Cost Promational Total Book Costs million dollan tion dailand (miltlion dollar li dolland Horro 85.10 106.30 50.20 130.60 5480 0.30 7940 91.00 5.10 5.80 2.10 8.50 12.90 5.20 10.70 3.10 3.50 9.20 9.00 15.10 0.20 7.00 14.00 4.70 8.80 15.10 12.20 0.60 3.50 9.70 5.90 20.80 7.90 10.40 3.00 Horror Drama 2.90 1.20 3.70 7.60 Drama 89.30 95.00 4.50 4.00...
2) Suppose the regression model y = B0 + B1x1 + B2x2 + B3x3 + B4x1x2...
2) Suppose the regression model y = B0 + B1x1 + B2x2 + B3x3 + B4x1x2 + B5x1x3 + B6x2x3 was fit to n = 27 data points with SSE = 2000.0. a) Set up the null and alternative hypotheses for testing whether the interaction terms are significant. b) Give the reduced model necessary to test the significance of the interaction terms. c) The reduced model resulted in SSE = 2800. Calculate the value of the test statistic appropriate for...
INDEPENDENT OR DEPENDENT ARE IN THE DROP DOWN BOXES. Degrees of Sum of The ANOVA summary...
INDEPENDENT OR DEPENDENT ARE IN THE DROP DOWN BOXES.
Degrees of Sum of The ANOVA summary table to the right is for a multiple regression model with two independent variables. Complete parts (a) through (e) Source Freedom Squares Regression Eror Total 15 17 70 160 230 Draw a conclusion. Choose the correct answer below o A. There is insufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is less than...
A regression analysis is performed using data for 36 single-family homes to predict appraised value (in...
A regression analysis is performed using data for 36
single-family homes to predict appraised value (in thousands of
dollars) based on land area of the property (in acres), X1i, and
age (in years), X2i, in month i. Use the results below to
complete parts (a) and (b) below.
Variable
Coefficient
Standard Error
t Statistic
p-value
Intercept
392.60372
51.68272
7.60
0.0000
Area, X1
451.43475
100.48497
4.49
0.0001
Age,X2
−2.17162
0.79077
−2.75
0.0097
a. Construct a 95% confidence interval estimate...
Drop down options are durability, impact properties, shock absorbing capabilities, the two independent variables. A regression...
Drop down options are durability, impact properties, shock
absorbing capabilities, the two independent variables.
A regression analysis is performed to predict the durability of a brand of running shoe, based on the shock-absorbing capability and the change in impact properties over time. The resulting ANOVA table is below. Complete parts (a) through (d). Degrees of Sum of Freedom Squares Regression Error Total 10.45577 6.46314 16.91891 Mean Square 5.22789 0.28101 p-value 0.00002 18.60 2 23 25 a. Determine whether there is...
Consider a linear regression model where y represents the response variable, x is a quantitative explanatory...
Consider a linear regression model where y represents the response variable, x is a quantitative explanatory variable, and d is a dummy variable. The model is estimated as yˆy^ = 14.6 + 4.5x − 3.4d. a. Interpret the dummy variable coefficient. Intercept shifts down by 3.4 units as d changes from 0 to 1. Slope shifts down by 3.4 units as d changes from 0 to 1. Intercept shifts up by 3.4 units as d changes from 0 to 1. Slope shifts...
Consider a linear regression model where y represents the response variable, x is a quantitative explanatory...
Consider a linear regression model where y represents the response variable, x is a quantitative explanatory variable, and d is a dummy variable. The model is estimated as yˆy^ = 14.4 + 4.6x − 3.1d. a. Interpret the dummy variable coefficient. Intercept shifts down by 3.1 units as d changes from 0 to 1. Slope shifts down by 3.1 units as d changes from 0 to 1. Intercept shifts up by 3.1 units as d changes from 0 to 1. Slope shifts...
2) Suppose the regression model y = B0 + B1x1 + B2x2 + B3x3 + B4x1x2 + B5x1x3 + B6x2x3 was fit to n = 27 data points with SSE = 2000.0. a) Set up the null and alternative hypotheses for testing whethe...
2) Suppose the regression model y = B0 + B1x1 + B2x2 + B3x3 + B4x1x2 + B5x1x3 + B6x2x3 was fit to n = 27 data points with SSE = 2000.0. a) Set up the null and alternative hypotheses for testing whether the interaction terms are significant. b) Give the reduced model necessary to test the significance of the interaction terms. c) The reduced model resulted in SSE = 2800. Calculate the value of the test statistic appropriate for...
1. A variable that takes on the values of 0 or 1 and is used to incorporate the effect of categorical variables in a regression model is called a. an interaction b. a constant variable c. a dummy variable d. None of these alternatives is correct. 2. adjusted multiple coefficient of determination is adjusted for a. the number of dependent variables b. the number of independent variables c. the number of equations d. detrimental situations 3. A variable such as...
Box office Example with 2 Dummy variables: Let us define two dummy variables First yr box Total Prod Dummy Dummy Cost Promational Total Book Costs million dollan tion dailand (miltlion dollar li dolland Horro 85.10 106.30 50.20 130.60 5480 0.30 7940 91.00 5.10 5.80 2.10 8.50 12.90 5.20 10.70 3.10 3.50 9.20 9.00 15.10 0.20 7.00 14.00 4.70 8.80 15.10 12.20 0.60 3.50 9.70 5.90 20.80 7.90 10.40 3.00 Horror Drama 2.90 1.20 3.70 7.60 Drama 89.30 95.00 4.50 4.00...
INDEPENDENT OR DEPENDENT ARE IN THE DROP DOWN BOXES.
Degrees of Sum of The ANOVA summary table to the right is for a multiple regression model with two independent variables. Complete parts (a) through (e) Source Freedom Squares Regression Eror Total 15 17 70 160 230 Draw a conclusion. Choose the correct answer below o A. There is insufficient evidence of a significant linear relationship with at least one of the independent variables because the test statistic is less than...
A regression analysis is performed using data for 36
single-family homes to predict appraised value (in thousands of
dollars) based on land area of the property (in acres), X1i, and
age (in years), X2i, in month i. Use the results below to
complete parts (a) and (b) below.
Variable
Coefficient
Standard Error
t Statistic
p-value
Intercept
392.60372
51.68272
7.60
0.0000
Area, X1
451.43475
100.48497
4.49
0.0001
Age,X2
−2.17162
0.79077
−2.75
0.0097
a. Construct a 95% confidence interval estimate...
Drop down options are durability, impact properties, shock
absorbing capabilities, the two independent variables.
A regression analysis is performed to predict the durability of a brand of running shoe, based on the shock-absorbing capability and the change in impact properties over time. The resulting ANOVA table is below. Complete parts (a) through (d). Degrees of Sum of Freedom Squares Regression Error Total 10.45577 6.46314 16.91891 Mean Square 5.22789 0.28101 p-value 0.00002 18.60 2 23 25 a. Determine whether there is...
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