Data for Exercise 7.59

Music

Format

A data frame/tibble with 12 observations on three variables

method1

a numeric vector measuring the improvement scores on a music recognition test

method2

a numeric vector measuring the improvement scores on a music recognition test

differ

method1 - method2

References

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

Examples


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$method1, Music$method2, paired = TRUE)
#>
#> 	Paired t-test
#>
#> data:  Music$method1 and Music$method2
#> t = 1.5947, df = 11, p-value = 0.1391
#> alternative hypothesis: true difference in means is not equal to 0
#> 95 percent confidence interval:
#>  -0.411863  2.578530
#> sample estimates:
#> mean of the differences
#>                1.083333
#>
# Or
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()
}