`R/BSDA-package.R`

`Remedial.Rd`

Data for Exercise 7.43

`Remedial`

A data frame/tibble with 84 observations on two variables

- gender
a character variable with values

`female`

and`male`

- score
math placement score

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

```
boxplot(score ~ gender, data = Remedial,
col = c("purple", "blue"))
t.test(score ~ gender, data = Remedial, conf.level = 0.98)
#>
#> Welch Two Sample t-test
#>
#> data: score by gender
#> t = 0.20997, df = 68.546, p-value = 0.8343
#> alternative hypothesis: true difference in means is not equal to 0
#> 98 percent confidence interval:
#> -4.285617 5.114189
#> sample estimates:
#> mean in group female mean in group male
#> 19.34286 18.92857
#>
t.test(score ~ gender, data = Remedial, conf.level = 0.98)$conf
#> [1] -4.285617 5.114189
#> attr(,"conf.level")
#> [1] 0.98
wilcox.test(score ~ gender, data = Remedial,
conf.int = TRUE, conf.level = 0.98)
#> Warning: cannot compute exact p-value with ties
#> Warning: cannot compute exact confidence intervals with ties
#>
#> Wilcoxon rank sum test with continuity correction
#>
#> data: score by gender
#> W = 855.5, p-value = 0.218
#> alternative hypothesis: true location shift is not equal to 0
#> 98 percent confidence interval:
#> -1.000053 3.000039
#> sample estimates:
#> difference in location
#> 1.000093
#>
```