The proper estimate of variance explained in multiple regression is Question 13 options: R2 >50% significant predictors Adjusted R2 All of these
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The proper estimate of variance explained in multiple regression is
Question 13 options:
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R2 |
>50% significant predictors |
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Adjusted R2 |
All of these |
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- The following result was reported in the text for a regression of winning percentage on market size in the NBA. Coefficient on Market Size = 20 t-statistic for the coefficient on market size = 0.6667 What is the standard error for the coefficient on Market size?One measure of goodness of fit (or the quality) of the estimated regression equation is the… … mean square due to regression … mean square due to error … high correlation between the ‘x’ variables … multiple coefficient of determination ‘R-Squared’I need help with these questions 1. do the covariates and factors interact? 2. can you conclude a homogeneity of regression slopes? 3. can you conclude homogeneity of variance?
- For an ANOVA test of significance of a regression model with 10 regressor variables and 50 observations, what is the degree of freedom of the SSr? choices 11 10 39 4941You may need to use the appropriate technology to answer this question. Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage (hours per week) of a particular brand of computer terminal. Analysis of Variance SOURCE DF Adj SS Adj MS Regression 1 1575.76 1575.76 Error 8 349.14 43.64 Total 9 1924.90 Predictor Coef SE Coef Constant 6.1092 0.9361 X 0.8951 0.1490 Regression Equation Y = 6.1092 + 0.8951 X #1) Write the estimated regression equation. ŷ = #2) Find the value of the test statistic. (Round your answer to two decimal places.)Find the p-value. (Round your answer to three decimal places.) #3)Use the estimated regression equation to predict monthly maintenance expense (in dollars per month) for any terminal that is used 15 hoursper week. (Round your answer to the nearest cent.) $ _____per month
- 10In an ANOVA table for a multiple regression analysis, the global test of significance is based on the _________. Select one: a. Regression mean square divided by the mean square error b. Treatment mean square and block mean square c. Treatment mean square divided by the error variation d. Block and error variationConsider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Intercept Car Accidents (In last 3 years) Credit Score Safety Rating Answer Coefficients 933 167.94 - 102.63 -199.18 Does the sign of the coefficient for the variable credit score make sense? Coefficients Standard Error 95.65 17.99 10.89 19.98 t Stat P-value 9.754 0.0000 9.335 0.0000 -9.424 0.0000 -9.969 0.0000 O Yes, because it is expected that as the credit score increases then the cost should decrease. O No, because it is expected that as the credit score increases then the cost should decrease. O Yes, because it is expected that as the credit score increases then the cost should also increase. O No, because it is expected that as the credit score increases then the cost should also increase. Tables Keypad Keyboard Shortcuts
- Let's study the relationship between brand, camera resolution, and internal storage capacity on the price of smartphones. Use α = .05 to perform a regression analysis of the Smartphones01CS dataset, and then answer the following questions. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Did you find any evidence of multicollinearity and variance inflation among the predictors. Explain your answer using a VIF analysis. b. Copy and paste the normal probability plot for your analysis. Is there any evidence that the errors are not normally distributed? Explain. c. Copy and paste the Residuals vs. Predicted Y-values. Does the pattern support the null hypothesis of constant variance for the errors? Explain. d. Study the residuals analysis. Which observations, if any, have unusual residuals? e. Study the residuals analysis. Calculate the leverage statistic. Which observations, if any, are high leverage…d. Present major regression summary outputs for both regression lines showing: regression statistics, coefficients, standard error, t stats, p-values and 95% confidence interval.Table 1. Critical Values from N(0,1) Distribution One-sided 1.29 1.645 2.33 1. 10% 5% 1% Two-sided 1.645 1.96 2.575 Question 1 Are the following statements true or false? Circle A or B to indicate whether each statement is true or false. Low R² in an estimated regression model indicates that changes in independent variables do not have an important effect on the dependent variable. A. True B. False
