Solve for the R2. Enter your response as numerical value. Enter your response with 4 decimals. Please show all your work
| R Square | X |
| Adjusted R Square | X |
| Standard Error | 3.201 |
| Observations | 135 |
| df | ss | MS | MS | Signifigance | |
| Regression | 4 | x | x | x | 0.003 |
| Residual | x | X | X | x | |
| Total | X | 10,560 | |||
Solve for the R2. Enter your response as numerical value. Enter your response with 4 decimals....
Based on the below data what will be the value of mse? Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 8 ANOVA df SS MS F Regression 1 23 23.0 11.5 Residual 6 12 2.0 Total 7 Coefficients Standard Error t Stat P-value Intercept 20 31.274666 3.984284 0.007248 Advertising (thousands of $) 41 6.19330674 1.610802 0.158349
You were asked by your manager to evaluate the regression tables below to decide which cost driver would be best to use for the production department. Since your manager is new and does not understand the regression analysis tables, you will need to explain why one set of statistics is better than the other and why you have chosen the better driver. Manufacturing Direct Labor Hours Regression Statistics Multiple R 0.799304258 R Square 0.638887297 Adjusted R Square 0.602776026 Standard Error...
Based on the below data what will be the value of multiple R? Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 8 ANOVA df SS MS F Regression 1 29 29 7 Residual 6 26 4 Total 7 Coefficients Standard Error t Stat P-value Intercept 1 31.274666 3.984284 0.007248 Advertising (thousands of S) 42 6.19330674 1.610802 0.158349 Submit Answer format: Number Round to: 2 decimal places.
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....
4- Indicate if the estimates are statistically significant at 0.1%, 1%, 5% or 10%. Regression summary output using Excel is as follows. SUMMARY OUTPUT Regression Statistics Multiple R 0.8811 R Square 0.7764 Adjusted R Square 0.7205 Standard Error 14.7724 Observations 16 ANOVA df SS MS F Regression 3 9091.7392 3030.5797 13.8874 Residual 12 2618.7008 218.2251 Total 15 11710.44 Coefficients Standard Error t Stat P-value Intercept 29.1385 174.7427 0.1668 0.8703 PFH -2.1236 0.3405 -6.2361 0.0000 PR 1.0345 0.4667 2.2164 0.0467 M...
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.
Regression Statistics Multiple R 0.806174983 0.649918103 R Square Adjusted R Square Standard Error Observations 0.636952107 13.57635621 29 ANOVA Significance F E SS MS df 9238.877183 9238.877 50.12481 1.30123E-07 Regression Residual 4976.571093 184.3174 27 14215.44828 Total...
4. Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?". Summary Output Regression Statistics Multiple R ? R Square ? Adjusted R Square 0.8125 Standard Error 1.3693064 Observations 7 ANOVA df SS MS F Significance F Regression ? 50.625 ? ? ? Residual ? 9.375 ? Total 6 60 Coefficients Standard Error. t Stat P-value Lower 95% Intercept 13.75 1.398341. 9.833082 0.0001853 10.15555 x -1.125...
5- Interpret the coefficient of determination (R-squared) and the F test. SUMMARY OUTPUT Regression Statistics Multiple R 0.8811 R Square 0.7764 Adjusted R Square 0.7205 Standard Error 14.7724 Observations 16 ANOVA df SS MS F Regression 3 9091.7392 3030.5797 13.8874 Residual 12 2618.7008 218.2251 Total 15 11710.44 Coefficients Standard Error t Stat P-value Intercept 29.1385 174.7427 0.1668 0.8703 PFH -2.1236 0.3405 -6.2361 0.0000 PR 1.0345 0.4667 2.2164 0.0467 M 3.0871 0.9993 3.0892 0.0094
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...
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...