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This problem uses one of the datasets in the R base distribution, called “attitude”. It contains aggregated results of a survey of employees in a ?nancial organization. ?attitude The variable called “rating” is the employees’ overall rating of the company, and the other variables are responses to individual questions. We want to ?t linear models with “rating” as the outcome variable and one or more of the other responses as covariates.

(a) Fit a linear model for “rating” with “learning” as the only covariate. Report the two coe?cients for the intercept and slope and their standard errors as calculated using normal least-squares theory.

 (b) By bootstrapping cases, calculate the standard error of the coe?cient for “learning” in the model ?tted in part 1a, and also a 95% BCa con?dence interval for this coe?cient.

 (c) Repeat part 1b but this time bootstrap residuals instead of cases.


(d) Fit four linear models with the following sets of covariates, each with “rating” as the outcome: • “learning”

• “learning”, “complaints”

• “learning”, “complaints”, “advance”

• “learning”, “complaints”, “advance”, “raises”

Product code:Statistics-QA438

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require(stats); require(graphics) pairs(attitude, main = "attitude data") summary(attitude)

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