R/BSDA-package.R
Music.Rd
Data for Exercise 7.59
Music
A data frame/tibble with 12 observations on three variables
a numeric vector measuring the improvement scores on a music recognition test
a numeric vector measuring the improvement scores on a music recognition test
method1
- method2
Kitchens, L. J. (2003) Basic Statistics and Data Analysis. Pacific Grove, CA: Brooks/Cole, a division of Thomson Learning.
qqnorm(Music$differ)
qqline(Music$differ)
shapiro.test(Music$differ)
#>
#> Shapiro-Wilk normality test
#>
#> data: Music$differ
#> W = 0.96631, p-value = 0.8685
#>
t.test(Music$differ)
#>
#> One Sample t-test
#>
#> data: Music$differ
#> t = 1.5947, df = 11, p-value = 0.1391
#> alternative hypothesis: true mean is not equal to 0
#> 95 percent confidence interval:
#> -0.411863 2.578530
#> sample estimates:
#> mean of x
#> 1.083333
#>
if (FALSE) {
library(ggplot2)
ggplot2::ggplot(data = Music, aes(x = differ)) +
geom_dotplot() +
theme_bw()
}