Use Excel to develop a regression model for the Hospital Database (using the “Excel Databases.xls” file on Blackboard) to predict the number of Personnel by the number of Births. What can you conclude from the study?
| SUMMARY OUTPUT | ||||||||
| Regression Statistics | ||||||||
| Multiple R | 0.697463374 | |||||||
| R Square | 0.486455158 | |||||||
| Adjusted R Square | 0.483861497 | |||||||
| Standard Error | 590.2581194 | |||||||
| Observations | 200 | |||||||
| ANOVA | ||||||||
| df | SS | MS | F | Significance F | ||||
| Regression | 1 | 65345181.8 | 65345181.8 | 187.5554252 | 1.79694E-30 | |||
| Residual | 198 | 68984120.2 | 348404.6475 | |||||
| Total | 199 | 134329302 | ||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
| Intercept | 390.6214398 | 54.07601821 | 7.223561437 | 1.06764E-11 | 283.9825868 | 497.2602928 | 283.9825868 | 497.2602928 |
| Births | 0.538734917 | 0.039337822 | 13.69508763 | 1.79694E-30 | 0.461160045 | 0.616309789 | 0.461160045 | 0.616309789 |
Homework Answers
Solution-
We have to predict the number of Personnel by the number of Births.
From the Summary Output provided -
Intercept = 390.6214398
Slope = 0.538734917
The regression equation is
Number of personals = 390.6214398 + ( 0.538734917 × Number of births )
Also, From ANOVA F value is very large and also p- value is less than significance level.
So, we can conclude
The number of births is adding significant predictability to the number of personals in a hospitals.
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Use Excel to develop a regression model for the Hospital
Database (using the “Excel Databases.xls” file...
Locate Hospital Tab on Excel Data. View Data:https://drive.google.com/file/d/1HMgLG7BVcvpoQ6iUxjk...
Locate Hospital Tab on Excel Data. View
Data:https://drive.google.com/file/d/1HMgLG7BVcvpoQ6iUxjkL_xCBzvpgHhHp/view?usp=sharing
Problem 1 What is a better predictor of the number of Personnel in a hospital? Using the "Excel Databases.xls" file, locate the tab for the Hospital Database. Use Excel to develop two simple regression models for the Hospital Database at a 5% significance level Model 1: Predict the number of Personnel by the number of Births Model 2: Predict number of Personnel by number of Beds Must complete all the parts to...
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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...
Locate Hospital Tab on Excel Data. View
Data:https://drive.google.com/file/d/1HMgLG7BVcvpoQ6iUxjkL_xCBzvpgHhHp/view?usp=sharing
Problem 1 What is a better predictor of the number of Personnel in a hospital? Using the "Excel Databases.xls" file, locate the tab for the Hospital Database. Use Excel to develop two simple regression models for the Hospital Database at a 5% significance level Model 1: Predict the number of Personnel by the number of Births Model 2: Predict number of Personnel by number of Beds Must complete all the parts to...
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...
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...
Step 1
For each of the independent variables contained in the
regression model in Step 1, test their statistical significance.
In testing statistical significance of a regression
coefficient, you have to justify your choice of one or two tail
test. (PLEASE SHOW ALL WORKING)
SUMMARY OUTPUT Regression Statistics Multiple R 0.31179522 0.097216259 R Square Adjusted R Square0.08877902 Standard Error 15.42093465 Observations 649 ANOVA df MS Significance F Regression 6 16440.370442740.0617411.52229408 2.87685E-12 Residual 642 152670.9547 237.8052254 Total 648 169111.3251 P-value Coefficients...
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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.
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