Hi I was wondering if i could have some help with some
distribution questions.
1. show where zero and one fall on a normal distribution based on
thedata.
2.is the coefficient sufficiently different than zero?
explain
3. is the coefficient sufficiently different than one? explain.
Homework Answers
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Hi I was wondering if i could have some help with some
distribution questions.
1. show...
What is the coefficient? What is the standard error? What is the z-statistic? Is the coefficient...
What is the coefficient?
What is the standard error?
What is the z-statistic?
Is the coefficient sufficiently different from zero? How about
one? Explain.
SUMMARY OUTPUT Regression Statistics Multiple R 0.58175248 R Square 0.33843594 Adjusted R S 0.31393357 Standard Err 1.1991813 Observations 29 ANOVA df SS MS Significance F 0.000932269 Regression 1 19.86268888 19.86268888 13.8123745 Residual 38.82696629 27 1.438035789 Total 58.68965517 28 Coefficients Standard Error P-value t Stat Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.0202247 0.223805467 -0.090367404...
We are doing regression analysis for business analytics class and I am having a hard time reading...
We are doing regression analysis for business analytics class and I am having a hard time reading this data. Please help. SUMMARY OUTPUT Regression Statistics Multiple R 0.999964 R Square 0.999928 Adjusted R Square 0.9999248 Standard Error 267.074107 Observations 48 ANOVA df SS MS F Significance F Regression 2 44576676715 2.23E+10 312474.2 6.1672E-94 Residual 45 3209786.045 71328.58 Total 47 44579886501 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -42159057 121894.4727 -345.865 1.04E-78 -42404564.6...
Calculate the 95% prediction interval of y when x=5 using the 2000 pairs Mean of x...
Calculate the 95% prediction interval of y when x=5 using the 2000 pairs Mean of x = 4.51 Regression Statistics Multiple R 0.012848 R Square 0.000165 Adjusted R Square -0.00034 Standard Error 2.869737 Observations 2000 ANOVA df SS MS F Significance F Regression 1 2.716416 2.716416 0.329847 0.565814 Residual 1998 16454.31 8.235388 Total 1999 16457.02 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.509054 0.119572 37.70997 1.7E-235 4.274555 4.743552574 4.274555 4.743553 X 0.012884...
Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R...
Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Significance df SS MS F F Regression 102.1488 148.9539 Residual Total 12.0000 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept % MGT 0.4543 SE CI CI PI PI Predicted Predicted Lower Upper Lower Upper x0 Value Value 95% 95% 95% 95% 67.0000 67.8474 65.8779 69.8169 72.0000 70.1189 68.2003 72.0375 76.0000 71.9361 69.7884 74.0838 Dep.= % MGT...
What percent of the variance in well production is explained by knowing well depth and well...
What percent of the variance in well production is explained by knowing well depth and well age? SUMMARY OUTPUT Regression Statistics Multiple R 0.98711 R Square 0.974387 Adjusted R Square 0.965849 Standard Error 47.4523 Observations 9 ANOVA df SS MS F Significance F Regression 2 513960.7 256980.4 114.1262 1.68E-05 Residual 6 13510.32 2251.72 Total 8 527471.1 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -100.805 48.43281 -2.08133 0.082583 -219.316 17.70612 -219.316 17.70612 Well...
1.Based on the table above, how to intepret this regression analysis? 2. When we need to...
1.Based on the table above, how to intepret this regression
analysis?
2. When we need to look at the adjusted r2 and why?
3. How to conduct the hypothesis test?
0 Regression Statistics 1 Multiple R 2 R Square 3 Adjusted RS 0.853658537 0,97530483 0.951219512 4 Standard Err 0.191273014 5 Observation 6 7 ANOVA Significance F 0.220863052 df SS MS 0.713414634 0.356707 9 Regression 0 Residual 1 Total 2. 9.75 1 0.036585366 0.036585 0.75 2 Lower 95 % 3 Coefficients...
Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations...
Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance 285.2516 MS 916816.787 3214.0637 Regression Residual Total 0.000 2750450.3598 800301.8665 3550752.226 252 Intercept Income Coefficients Standard Error 70.2382 15.8338 5.45850 .2485 t Stat P-value 4.4360 0.000014 21.96960 .000 Lower 3 9.053 4.969 "pper 95% 1.4234 479 HULLU LIIS TILIR. SUMMARY OUTPUT Regression Statistics Multiple R 0.8778 R Square Adjusted R Square 0.6558 Standard Error Observations ANOVA ANOVA Significance Regression 45.3528 de...
Calculate the following statistics given the existing information (1 point per calculation): Regression Statistics Multiple R...
Calculate the following statistics given the existing information (1 point per calculation): Regression Statistics Multiple R R Square Adjusted R Square 0.559058 Standard Error Observations 30 ANOVA df SS MS F Significance F Regression 2 3609132796 19.38411515 6.02827E-06 Residual 27 2513568062 Total 29 6122700857 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -15800.8 57294.51554 -0.27578 0.784814722 CARAT 12266.83 1999.250369 6.135715 1.48071E-06 DEPTH 156.686 928.9461882 0.168671 0.867312915 Additionally interpret your results. Be sure to comment on Accuracy, significance...
11. (35 pts) An agent for a real estate company wanted to predict the monthly rent...
11. (35 pts) An agent for a real estate company wanted to predict the monthly rent for one- bedroom apartments, based on the size of the apartment (see summary output below). Using the results, identify the coefficient of determination, r2, and interpret its meaning. SUMMARY OUTPUT Regression Statistics Multiple R 0.354314 R Square 0.125539 Adjusted R Square 0.106529 Standard Error 186.0407 Observations 48 ANOVA df Regression Residual Total 1 46 47 Significance SS MS F F 228565.2 228565.2 6.603807 0.013481439...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45 6 Anova df SS MS F Significance F 0.11 1 41497.60 41497.60 4.20 Regression Residual 4 39561.23 9890.31 Total 5 81058.83 t Stat P-value Coefficients Standard Error 1423.60 564.95 2.52 0.07 Intercept X Variable 1 Lower 95% Upper 95% -144.96 2992.16 -0.11 0.72 Lower 95.0% Upper 95.0% -144.96 2992.16 -0.11 0.72 0.31 0.15 2.05 0.11 Assume that Craig's Fresh and Hot Pancake Restaurant does...
What is the coefficient?
What is the standard error?
What is the z-statistic?
Is the coefficient sufficiently different from zero? How about
one? Explain.
SUMMARY OUTPUT Regression Statistics Multiple R 0.58175248 R Square 0.33843594 Adjusted R S 0.31393357 Standard Err 1.1991813 Observations 29 ANOVA df SS MS Significance F 0.000932269 Regression 1 19.86268888 19.86268888 13.8123745 Residual 38.82696629 27 1.438035789 Total 58.68965517 28 Coefficients Standard Error P-value t Stat Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.0202247 0.223805467 -0.090367404...
1.Based on the table above, how to intepret this regression
analysis?
2. When we need to look at the adjusted r2 and why?
3. How to conduct the hypothesis test?
0 Regression Statistics 1 Multiple R 2 R Square 3 Adjusted RS 0.853658537 0,97530483 0.951219512 4 Standard Err 0.191273014 5 Observation 6 7 ANOVA Significance F 0.220863052 df SS MS 0.713414634 0.356707 9 Regression 0 Residual 1 Total 2. 9.75 1 0.036585366 0.036585 0.75 2 Lower 95 % 3 Coefficients...
Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance 285.2516 MS 916816.787 3214.0637 Regression Residual Total 0.000 2750450.3598 800301.8665 3550752.226 252 Intercept Income Coefficients Standard Error 70.2382 15.8338 5.45850 .2485 t Stat P-value 4.4360 0.000014 21.96960 .000 Lower 3 9.053 4.969 "pper 95% 1.4234 479 HULLU LIIS TILIR. SUMMARY OUTPUT Regression Statistics Multiple R 0.8778 R Square Adjusted R Square 0.6558 Standard Error Observations ANOVA ANOVA Significance Regression 45.3528 de...
11. (35 pts) An agent for a real estate company wanted to predict the monthly rent for one- bedroom apartments, based on the size of the apartment (see summary output below). Using the results, identify the coefficient of determination, r2, and interpret its meaning. SUMMARY OUTPUT Regression Statistics Multiple R 0.354314 R Square 0.125539 Adjusted R Square 0.106529 Standard Error 186.0407 Observations 48 ANOVA df Regression Residual Total 1 46 47 Significance SS MS F F 228565.2 228565.2 6.603807 0.013481439...
Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.72 0.51 0.38 99.45 6 Anova df SS MS F Significance F 0.11 1 41497.60 41497.60 4.20 Regression Residual 4 39561.23 9890.31 Total 5 81058.83 t Stat P-value Coefficients Standard Error 1423.60 564.95 2.52 0.07 Intercept X Variable 1 Lower 95% Upper 95% -144.96 2992.16 -0.11 0.72 Lower 95.0% Upper 95.0% -144.96 2992.16 -0.11 0.72 0.31 0.15 2.05 0.11 Assume that Craig's Fresh and Hot Pancake Restaurant does...
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