The statistical method currently used to combine the results of multiple studies is? a. Meta-analysis b. Power analysis c. Regression analysis d. Retrospective analysis
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- See the attached image for the introduction. Question: Fill in a blank ANOVA table.A researcher wants to forecast the annual sales of Walmart, based on store size. To examine the relationship between the store size in square feet and its annual sales in million dollars, a sample of 14 stores was selected shown below in the image: Answer the following: i) Null hypothesis of correlation ii) Coefficient of Correlation and its interpretation iii) Interpret the sig value of ANOVA. iv) Coefficient of Determination and its interpretation v) Write down the Regression Model. vi) Interpret the value of ‘a’ vii) Interpret the value of ‘slope’What mean physical health score would you expect in a group of 28-year-old women with a graduate degree?
- In doing regression analysis in MS Excel, what are the three sets of data you see from Regression result? Select all that apply. A. Probability Output B. Residual Output C. ANOVA D. Summary Output E. OVERALL FitAs part of a study designed to compare hybrid and similarly equipped conventional vehicles, Consumer Reports tested a variety of classes of hybrid and all-gas model cars and sport utility vehicles (SUV’s). You are given the required information in the Excel data-file named HybridTest. Test for any significant effect due to Class, Type using multiple regressions. Create dummy variables for Class and Type. Use alpha=0.05 Make/Model Class Type MPG Honda Civic Small Car Hybrid 37 Honda Civic Small Car Conventional 28 Toyota Prius Small Car Hybrid 44 Toyota Corolla Small Car Conventional 32 Chevrolet Malibu Midsize Car Hybrid 27 Chevrolet Malibu Midsize Car Conventional 23 Nissan Altima Midsize Car Hybrid 32 Nissan Altima Midsize Car Conventional 25 Ford Escape Small SUV Hybrid 27 Ford Escape Small SUV Conventional 21 Saturn Vue Small SUV Hybrid 28 Saturn Vue Small SUV Conventional 22 Lexus RX Midsize SUV Hybrid 23 Lexus RX Midsize SUV Conventional 19…Hi there Q5
- Last year, TimeWise conducted a study that aimed at predicting the waiting time (in minutes) at the checkout line of the Ranch 99 Supermarket in South Jakarta based on the number of customers in one particular month. Using the simple regression method on a dataset with a sample size of 30, the regression output tables are given below: SUMMARY OUTPUT Regression Statistics Multiple R 0.88728417 R Square 0.7872732 Adjusted R Square 0.77967582 Standard Error 0.59521532 Observations 30 ANOVA MS Significance F Regression 36.7121241 36.7121241 103.6242271 6.48782E-11 Residual 28 9.91987592 0.35428128 Total 29 46.632 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept -0.4479791 0.2782914 -1.6097484 0.118670876 -1.018033233 0.12207495 Customers 0.12847188 0.01262053 10.1795986 6.48782E-11 0.102619905 0.15432385 a. Determine the simple regression model to predict the waiting time b. Interpret the meaning of the regression coefficient of the independent variable c. What is…Using a sample of 46 college students, we want to determine if there is a significant correlation between weight (in lbs.) and weekly exercise (in minutes). The results of a correlation and regression analysis are indicated in the Excel output below. The mean weight (the independent variable) was 166.80 lbs., and the mean weekly exercise time (the dependent variable) was 158.83 minutes. SUMMARY OUTPUT Regression Statistics Multiple R 0.027082077 R Square 0.000733439 Adjusted R Square -0.021977165 Standard Error 79.41761298 Observations 46 ANOVA df SS MS F Significance F Regression 1 203.6896 203.6896 0.032295 0.858207 Residual 44 277514.9 6307.157 Total 45 277718.6 Coefficients Standard Error t Stat P-value Lower 95%…A nonprofit analyst considered two independent variables as a predictor for the dependent variable Commitment, the percent of total expenses that are allocated to charitable services. The independent variables are Revenue, total revenue in billions of dollars, andEfficiency, the percent of private donations remaining after fundraising expenses. The regression analysis resulted in this ANOVA table. Determine whether there is a significant relationship between commitment and the two independent variables at the 0.01 level of significance. Source Degrees of Freedom Sum of Squares Mean Square F p-value Regression 2 3640.0416 1820.02 51.0429 <.0001 Error 87 3102.1301 35.66 Total 89 6742.1717 Determine the p-value. The p-value is ________ (Round to three decimal places as needed.)
- 7) Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total df 2 39 41 0.745495 0.555762 0.532981 7211.848 42 SS 2537650171 2028419591 4566069762 Coefficients Standard Error MS 1.27E+09 52010759 F 24.39544 Significance F 1.3443E-07 Upper 95% t Stat P-value Lower 95% Intercept 47331.38 13884.34664 3.408974 0.001528 19247.6673 House Age -825.161 607.3128421 -1.35871 0.182046 -2053.5662 Square Feet 40.91107 6.696523994 6.109299 3.65E-07 27.3660835 7A. What is the estimated regression equation for determining the market value of houses? 7B. Discuss tests of significance of the regression 7C. What percentage of the variation in the dependent variable, Market Value, is explained by the regression…In a production process, the time (in minutes) taken (run time) for a production run and the number of items produced (run size) for 15 randomly selected orders are analyzed using Minitab statistical software. The Minitab output is as follows: Regression Analysis: Run time versus Run size Analysis of Variance Source DF Adj SS Adj MS F-Value Critical value Regression 1 8737.1 8737.1 29.35 ……… Error 13 3870.5 297.7 Total 14 12607.6 Model Summary S R-sq R-sq(adj) R-sq(pred) 17.2549 ……. 66.94% 61.32% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 148.4 11.3 13.13 0.000 Run size 0.2627 0.0485 ……. ……. 1.00 1- Write down the least square regression equation to predict the run time for run size. 2- Interpret the coefficients of the fitted model. 3- At 5% significance level, test if run size is a good…What does the correlation matrix for a multiple regression analysis contain?A. Multiple correlation coefficientsB. Simple correlation coefficientsC. Multiple coefficients of determinationD. Multiple standard errors of estimate
