Data for Exercise 9.20

Shuttle

## Format

A data frame/tibble with 15 observations on two variables

users

number of shuttle riders

autos

number of automobiles in the downtown area

## References

Kitchens, L. J. (2003) Basic Statistics and Data Analysis. Pacific Grove, CA: Brooks/Cole, a division of Thomson Learning.

## Examples


plot(autos ~ users, data = Shuttle)

model <- lm(autos ~ users, data = Shuttle)
summary(model)
#>
#> Call:
#> lm(formula = autos ~ users, data = Shuttle)
#>
#> Residuals:
#>      Min       1Q   Median       3Q      Max
#> -195.035  -41.056   -0.979   82.357  149.287
#>
#> Coefficients:
#>               Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 2837.23046   55.59622   51.03 2.30e-16 ***
#> users         -1.15105    0.06872  -16.75 3.52e-10 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 109.5 on 13 degrees of freedom
#> Multiple R-squared:  0.9557,	Adjusted R-squared:  0.9523
#> F-statistic: 280.5 on 1 and 13 DF,  p-value: 3.515e-10
#>
rm(model)