QUESTION 14 What does AR mean? O the change in R squared the total of R square O impossible to tell the variance of R squared QUESTION 15 in multiple regression, is testing each b for significance
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A: Solution Answer is The change in R sqaured
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- Regression: Determine what percentage of variation in College GPA is NOT explained by High School GPA. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square ANOVA Standard Error 0.25 Observations 20 Residual 0.3895 Total 0.1517 Regression 1 Intercept 0.1398 High School GPA 18 19 Coefficients 0.79 0.002 Significance F 2.502556445 2.502556 37.77623 8.36481E-06 $5 MS 1.192443555 0.066247 3.695 Standard Error t Stat P-value 0.348877197 2.393669 0.027785 0.000344183 6.146237 8.36E-06Please no written by hand solutionUsing the regression model from the previous problem, what is the interpretation of the slope coefficient associated with Age? Assume Salary is measured in $1,000's.
- 1) Interpret the multiple coefficient of determination R-square. 2) Compare the R-square of the simple linear regression and the R-square of the multiple regression, what does the differences in R-squares tell us? 3) What does F-test for significance tell us?egression line? About the unexplained variation? r= -0 422 Calculate the coefficient of determination. Round to three decimal places as needed.) What does this tell you about the explained variation of the data about the regression line? % of the variation can be explained by the regression line. (Round to one decimal place as needed.) About the unexplained variation? % of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)21. Least-squares OK? Following is a residual plot produced by MINITAB. Was it appropriate to compute the least-squares regression line? Explain. Residuals Versus x -2 -3 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Residual
- The total expenses of a hospital (dependent variable) are related to many factors. One of these factors is the number of admissions to the hospital (independent variable). Using the summary output below to answer, what is the meaning (analysis) of the X variable B1? SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Regression Statistics Intercept Admissions df 0.98706 0.974288 0.972145 8.106794 14 Coefficients 1 12 13 1.518053 0.668591 SS 29883.07 788.6412 30671.71 Standard Error 3.248929 0.031354 MS 29883.07 65.7201 t Stat 0.467247 21 32375 F 454.7022 P-value 0.648693 6.59E-11 Significance F 6.59E-11 Lower 95% -5.56075 0.600276 Upper 95% 8.59686 0736907Tests of Between-Subjects Effects df Mean Square F Dependent Variable Game Score Type II Sum Source: of Squares Sex 117.042 473 029 Handedness 605 6004 000 000 Sex Handedness 210.333 624 051 Error 3913 250 18 Total 232005.000 a. R Squared = 618 (Adjusted R Squared=512) Using the the value of "Mean Square", or variance, you calculated for the interaction between sex and handedness and error, calculate F- obt for the interaction. Use the rounded numbers from your calculations. Round your answer to 2 decimal places. Sig Partial Eta SquaredWhat is the least-squares regression line with the point (9,13) included in the data set? Data Set x y 3 6 4 5 5 7 7 6 8 9 8 8 10 8 11 9 11 7 12 10 13 12 13 10 14 11 This is a reading assessment question. ..... y hat = ______x + ______ Type integers or decimals rounded to 4 decimal places as needed
- Data for 50 U.S. “states" was used to examine the relationship between violent crime rate (violent crimes per 100,000 persons per year) and the independent variables of urbanization (percentage of the population living in urban areas) and poverty rate. 50 observations were examined. The Excel sheet output for the analysis of this data is shown in the Figure (with some information intentionally left blank). SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.69 Standard Error 8.54 Observations 50 ANOVA df SS MS Significance F Regression 2060 54.9 0.000 Residual 47 18.77 Total 2942 Coefficients Standard Error t Stat P-value B0 B1 B2 31.9 148.2 -2.17 0.035 -4.6 1.654 2.83 0.007 39.3 13.52 2.91 0.006X Y 14 25 26 28 19 27 13 21 28 31 23 24 30 31 26 27 19 29 Mean. 22 27 Std. Dev 6.08 3.28 Correlation 0.76 What is the t value using the direct difference approach? (report positive t-value)hi need the answer for this question tq