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Star, Inc. used Excel to run a least-squares regression analysis, which resulted in the following output:...
7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
REGRESSION STATISTICS Multiple R .142620229 R Square .02034053 Standard Error 20.25979924 Observations 22 Coefficients Standard Error...
REGRESSION STATISTICS Multiple R .142620229 R Square .02034053 Standard Error 20.25979924 Observations 22 Coefficients Standard Error T Stat P-Value Intercept 39.39.027309 37.24347659 1.057642216 .302826622 Attendance .340583573 .52852452 .644404489 .526635689 _______ In the table above, the proportion of the variation in "Score received on the exam" that can be explained by the variation in attendance is given by -standard error -R Square -The P-value -Intercept
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression Statistics Multiple R 0 .9697622171 R Square 0.940438758 Adjusted R Square 0.92058501 Standard Error 360.0073099 Observations 5 IIIIIIII ANOVAT di SS M S F Sanificance Regression 11 6 139184 2116139184 2111 47 368327870 000 Residual 3 3 88.815.78951129605,26321 Total 146528000T IUSTI Intercept X Variable 1 Coefficients 2056. 58 1.50 Standard Error 4 54.25 0.1816 Stat 6.728812231 .882465029 P-value 0006701290 0.006283174 Refer to the Regression...
18 QueSLIVIT TO Based on the following regression output, what is the equation of the regression...
18
QueSLIVIT TO Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.99313 0.98630 R Square Adjusted R Square Standard Error 0.98238 2.94802 10 Observations ANOVA df SS MS Significance F Regression 4379.182 2189.591 251.943 0.0000 Residual 7 60.836 8.691 9 Total 4440.017 Coefficients Standard Error t Stat P-value Lower 95% 14.169 3.856 3.674 Intercept 0.008 5.050 X Variable 1 0.985 0.114 8.607 0.000 0.714 X Variable 0.995 0.057 17.498 0.000...
QUESTION 20 From the Regression output below, what is the impact on the quantity demand of...
QUESTION 20 From the Regression output below, what is the impact on the quantity demand of water when incomes increase by 3% Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.925 0.856 0.846 0.059 45 ANOVA 81.46 Regression Residual Total SMS 0.85 0.28 0.14 0.00 0.99 t Intercept PRICE INCOME WEATHER Coefficients 13.040 -0.200 1.500 0.124 Standard Error 0.758 0.063 0.079 0.065 Stat 17.194 -7.904 13.162 1.909 P-value 0.000 0.000 0.000 0.063 A. Increase by 3%...
HW # 5 Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to...
HW # 5 Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to reproduce the excel out put below (Note: First enter the data in the next page in an Excel spreadsheet) Home Sale Price: The table below provides the Excel output of a regression analysis of the relationship between Home sale price(Y) measured in thousand dollars and Square feet area (x): SUMMARY OUTPUT Dependent: Home Price ($1000) Regression Statistics Multiple R 0.691 R Square 0.478 Adjusted...
Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor)...
Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor) variables. Provide some important arguments about the fitted multiple regression model. (Give one argument about each of the three main outputs.) [4 marks] SUMMARY OUTPUT Regression Statistics Multiple R 0.9870 R Square Adjusted R Square 0.9741 0.9721 Standard Error 116.2766 Observations 43 ANOVA Significance F df SS MS F Regression 19817036.22 6605678.74 488.58 5.82876E-31 Residual 527289.46 39 13520.24 Total 42 20344325.68 P-value Coefficients Standard...
Following a regression analysis output : SUMMARY OUTPUT Regression Statistics Multiple R 0.719422 R Square Adjusted...
Following a regression analysis output : SUMMARY OUTPUT Regression Statistics Multiple R 0.719422 R Square Adjusted R Square 0.477366 Standard Error Observations 14 ANOVA df SS MS F Regression 1 3.028885709 Residual 12 2.823257148 Total 13 5.852142857 Coefficients Standard Error t Stat P-value Intercept 1.157091 0.566482479 0.063699302 Satisfaction with Speed of Execution 0.636798 0.177478218 0.003726861 Group of answer choices R Square is 0.517 Standard error is 0.386 Residuals are 2.823 F-test is 11.87 R Square is 0.517 Standard error is...
show all steps, excel not allowed, thank you and will rate Regression Statistics Multiple R R...
show all steps, excel not allowed, thank you and will rate
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.989778267 0.979661017 0.969491525 0.387298335 4 ANOVA Significance F 14.45 96.33333 0.010221733 MS Regression Residual Total 14.45 0.3 14.75 0.15 Coefficients p-value Lower 95% U per 95% Lower 95.096 Upper 95.0% 7 0.474341649 14.75729575 0.00456 4.959072609 9.040927 4.959072609 9.040927391 1.7 0.173205081-9.814954576 0.010222 -2.445241314 0.95476-2.445241314 -0.954758686 Standard Errort Stat Intercept Case Sales a. Write the regression equation for the...
Q. 9 The following is a partial regression result of a two-variable model (i.e. simple linear...
Q. 9 The following is a partial regression result of a two-variable model (i.e. simple linear regression). In the study, a health care economist seeks to determine if a relationship exists between personal income and expenditures on health care, both measured in billions of dollars. Regression Statistics Multiple R ??? R Square ??? Standard Error Observations 51 ANOVA df SS MS F P-value Regression 1 15,750.32 0.00001 Residual/Error Total ??? 16,068.21 Coefficients Standard Error t Stat P-value Lower 95% Upper...
7,10,11
Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression Statistics Multiple R 0 .9697622171 R Square 0.940438758 Adjusted R Square 0.92058501 Standard Error 360.0073099 Observations 5 IIIIIIII ANOVAT di SS M S F Sanificance Regression 11 6 139184 2116139184 2111 47 368327870 000 Residual 3 3 88.815.78951129605,26321 Total 146528000T IUSTI Intercept X Variable 1 Coefficients 2056. 58 1.50 Standard Error 4 54.25 0.1816 Stat 6.728812231 .882465029 P-value 0006701290 0.006283174 Refer to the Regression...
18
QueSLIVIT TO Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.99313 0.98630 R Square Adjusted R Square Standard Error 0.98238 2.94802 10 Observations ANOVA df SS MS Significance F Regression 4379.182 2189.591 251.943 0.0000 Residual 7 60.836 8.691 9 Total 4440.017 Coefficients Standard Error t Stat P-value Lower 95% 14.169 3.856 3.674 Intercept 0.008 5.050 X Variable 1 0.985 0.114 8.607 0.000 0.714 X Variable 0.995 0.057 17.498 0.000...
QUESTION 20 From the Regression output below, what is the impact on the quantity demand of water when incomes increase by 3% Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.925 0.856 0.846 0.059 45 ANOVA 81.46 Regression Residual Total SMS 0.85 0.28 0.14 0.00 0.99 t Intercept PRICE INCOME WEATHER Coefficients 13.040 -0.200 1.500 0.124 Standard Error 0.758 0.063 0.079 0.065 Stat 17.194 -7.904 13.162 1.909 P-value 0.000 0.000 0.000 0.063 A. Increase by 3%...
Consider the following Excel multiple regression of output of Total Sales on the (c) other (predictor) variables. Provide some important arguments about the fitted multiple regression model. (Give one argument about each of the three main outputs.) [4 marks] SUMMARY OUTPUT Regression Statistics Multiple R 0.9870 R Square Adjusted R Square 0.9741 0.9721 Standard Error 116.2766 Observations 43 ANOVA Significance F df SS MS F Regression 19817036.22 6605678.74 488.58 5.82876E-31 Residual 527289.46 39 13520.24 Total 42 20344325.68 P-value Coefficients Standard...
show all steps, excel not allowed, thank you and will rate
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.989778267 0.979661017 0.969491525 0.387298335 4 ANOVA Significance F 14.45 96.33333 0.010221733 MS Regression Residual Total 14.45 0.3 14.75 0.15 Coefficients p-value Lower 95% U per 95% Lower 95.096 Upper 95.0% 7 0.474341649 14.75729575 0.00456 4.959072609 9.040927 4.959072609 9.040927391 1.7 0.173205081-9.814954576 0.010222 -2.445241314 0.95476-2.445241314 -0.954758686 Standard Errort Stat Intercept Case Sales a. Write the regression equation for the...
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