Larger values of $ r^2 $ imply that the observations are more closely grouped about the ____.- ○ average value of the independent variables- ○ average value of the dependent variable- ○ least squares line- ○ origin

Answered: Larger values of ²2 imply that the…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter4: Polynomial And Rational Functions

Section4.6: Variation

Problem 37E

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If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
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call: Researchers measured the percent 1m(formula = Symptoms - wear_mask, data - some_states) of people in 25 states who ʻknew someone with COVID symptoms' (ŷ) and regressed this on the percent of the population frequently wearing a mask in public (x). Residuals: Min -7.9167 -2.3306 -0.2469 2.5020 7. 3345 10 Median 30 Маx coefficients: (Intercept) 111.0981 wear_mask Estimate std. Error t value Pr (>|t|) 10. 5423 10. 538 2.82e-10 *** -8. 375 1. 94 e-08 *** -1.0419 0.1244 signif. codes: 0 ****' 0.001 ***' 0.01 **' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3.859 on 23 degrees of freedom Multiple R-squared: 0.7531, F-statistic: 70.15 on 1 and 23 DF, p-value: 1.936e-08 Adjusted R-squared: 0.7423 If 75 percent of people in a state wear masks regularly, what % of people does this model predict will know someone with COVID symptons? 1) 32 2) 33 3) 34 4) 35
On minitab or excel Calculating the coefficient of determination of a set of data, it was obtained that r^2 = 0.845 . Based on this value, it can be concluded that: Options: The least squares line provided a good fit as a large proportion of the variability in "y" has been explained by the least squares line. The least squares line provided a good fit as a small proportion of the variability in "y" has been explained by the least squares line. The least squares line did not provide a good fit since a small proportion of the variability in "y" has been explained by the least squares line. The least squares line did not provide a good fit since a large proportion of the variability in "y" has been explained by the least squares line.
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A multiple regression model has the form y^=b0+b1x1+b2x2 The coefficient b1 is interpreted as the:A. change in y per unit change in x1, holding x2 constantB. change in the average value of y per unit change in x1, holding x2 constantC. change in y per unit change in x1, when x1 and x2 values are correlatedD. change in y per unit change in x1 If multicollinearity exists among the independent variables included in a multiple regression model, the:A. multiple coefficient of determination will assume a value close to zeroB. standard errors of the regression coefficients for the correlated independent variables will increaseC. regression coefficients will be difficult to interpretD. regression coefficients will be difficult to interpret and the standard errors of the regression coefficients for the correlated independent variables will increase please explain which answer is correct and why
**Complete the table** 1) A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEO’s, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for year 1999, and ASSETS is the natural logarithm of the total assets of the company. a) Complete the table below

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Larger values of ²2 imply that the observations are more closely grouped about the average value of the independent variables average value of the dependent variable least squares line origin