Question

Table 1: Human Resources Data on 15 Sales Representatives at Company ABC А B с D E F Employee ID Gender Ethnicity PayRate Age 1 2 3 4 5 6 33.5 44.1 42 52 42 55 48.5 7 8 1510081026 Female African American 1108426251 Female African American 1403065874 Male African American 1102024149 Female African American 1409070147 Male Hispanic 1405067298 Female Hispanic 1001944783 Female Hispanic 1107027351 Male Hispanic 1103024679 Female Hispanic 1402065355 Female White 1303054580 Male White 1307060077 Male White 1501072311 Male White 1000974650 Male White 1110029990 Male White 36 45 43 60 40 52 38 54 48 37 39 40 42 Employee Satisfaction 3.2 3.4 3.5 4.7 4 4.2 4 4.5 3.8 4.1 3.7 4.5 3.7 4.2 5 9 10 11 12 13 14 15 16 52 55 38.7 50.5 48 54.5 53 55 55 57

6. Complete a regression analysis using Age (x variable) to predict Payrate (y variable).

A. Paste your regression analysis output below.

B. Using the output in part a, write out the linear equation to predict payrate based on our data set.

C. Use your regression equation in part b to estimate the payrate of a 45-year-old and a 55-year-old employee.

Answer 1

> x=c(36,45,43,60,40,52,38,54,48,37,39,40,42,55,57) > y=c(33.5,44.1,42,52,42,55,48.5,52,55,38.7,50.5,48,54.5,53,55) > m=lm(y^x) summary(m) Call: Im(formula = y ~ x) Residuals: Min 10 Median 30 -9.2365 -4.0387 -0.5057 3.9123 Max 8.3627 Coefficients: Estimate Std. Error t value Prit (Intercept) 22.3317 8.0404 2.777 0.0157 À х 0.5668 0.1734 3.269 0.0061 ** Signif. codes: O **** 0.001 ? 0.01 * 0.05 '.' 0.1'' 1 Residual standard error: 5.18 on 13 degrees of freedom Multiple R-squared: 0.4512, Adjusted R-squared: 0.409 F-statistic: 10.69 on 1 and 13 DF, p-value: 0.006096

Let x = Age. * y = Payrate a) b) 9 22. 3317 + 0.56 68 * x. d) ŷ x=45 2213317 + 0.5668 # (45) 47.84 능 & z = 55 22.3317 + 0.5668 * (55) = 53:51