Consider the following data on the number of minutes (x) that 10 persons spent on social mediaduring office hours and their productivity level (y):Xi102954 63707688 91108118Yi92 72 59 50 4948 38 25149A linear model was fitted using the statistical software R, producing the following output:Coefficients:(Intercept) 98.81082-0.75263Estimate Std. Error t value Pr(>|t|)29.8 1.74e-09 ***-17.6 1.1le-07 ***3.315740.04277Signif. codes:0 ***'0.001 ****0.010.05 .' 0.11Residual standard error: 4.304 on 8 degrees of freedomMultiple R-squared: 0.9748,F-statistic: 309.7 on 1 and 8 DF,Adjusted R-squared:p-value: 1.11e-070.9717(a) Obtain the equation of the estimated regression line.(b) Interpret the slope coefficient.(c) Discuss whether the simple linear regression model obtained does a good job of explainingobserved variation in productivity level.(d) Perform a model utility test using a = 0.01. Use an appropriate P-value from the outputgiven. (Note: R uses the E notation to display very large or very small numbers. Forexample, 3.2e-4 = 3.25 x 10-4 = 0.000325.)(e) The R output provides a residual standard error of 4.304, and an estimated standard errorvalue of 0.04277 for the slope coefficient. Provide the formulas used to obtain these twovalues, and describe what these standard errors are.

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Answered: (a) Obtain the equation of the…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter7: Analytic Trigonometry

Section7.6: The Inverse Trigonometric Functions

Problem 94E

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(a) Obtain the equation of the estimated regression line. (b) Interpret the slope coefficient. (c) Discuss whether the simple linear regression model obtained does a good job of explaining observed variation in productivity level.