Does it pay off to study hard at university and graduate with a high grade point average (GPA)? Aresearcher has collected data on the GPA (2.0-5.0) and the starting annual salary (in euros) of arepresentative sample of 46 graduates from a Business and Management programme. Theresearcher used SPSS to fit a simple linear regression model on the data. The SPSS output is shownbelow.Model1R Square122a. Predictors: (Constant), GPAModel1Model SummaryR.350Adjusted RSquareSum ofSquares666314698.947829902375449304935RegressionResidualTotala. Dependent Variable: Salaryb. Predictors: (Constant), GPA.102ANOVAdf14445Std. Error ofthe Estimate10426.137Mean Square666314698.9108704323.6F6.130Sig..017b Model1CoefficientsUnstandardized CoefficientsBStd. Error(Constant)37737.496GPA5971.460a. Dependent Variable: Salary10287.5442411.927StandardizedCoefficientsBeta.350t3.6682.476Sig..001.017Test the null hypothesis that the population slope is equal to zero against the alternative hypothesisthat the population slope is not zero. Conduct the test at the .01 level of significance. State yourconclusion and explain how you arrived at that conclusion.

Given: The output of simple linear regression is provided in the table. We need to test the null…

Answered: Model 1 Coefficients Unstandardized…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Statistic question. Please help. Part a,b,c is already answered. Need help with the remaining. Thank you
Proposed regression line: y ̂=5.4+(2.6)x n=4 Sum of squared deviations: ∑(??−?ℎ???)2∑(yi−yhati)2 = 25.2 Sums of squares: ∑(??−????????)2∑(yi−averagey)2 = 59 ∑?2?−?(????????)2∑xi2−n(averagex)2 = 5 Questions: (Enter answers rounded to one decimal place. If appropriate, include a zero before the decimal point) 1. What is ???Syx? 2. What is ??1Sb1? 3. What is SST? 4. What is SSE? 5. What is ?2R2?
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-06
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7:41 A myopenmath.com Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = - 42.42x + 49.75 and the r = 0.758. What proportion of the variation in y can be explained by the variation in the values of x? r2 = Report answer as a percentage accurate to one decimal place. Submit Question
Statistic problem. Please help
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