library(tidylsr)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, unionA minimal example for the two sample test:
iris %>%
filter(Species != "versicolor") %>%
ttest_twosample(Sepal.Length ~ Species)
#>
#> Welch's two sample t-test
#>
#> Variables:
#> outcome: Sepal.Length
#> group: Species
#>
#> Descriptives:
#> sample mean sd
#> setosa 5.006 0.352
#> virginica 6.588 0.636
#>
#> Hypotheses:
#> null: population means are equal
#> alternative: population means are different
#>
#> Test results:
#> t-statistic: -15.386
#> degrees of freedom: 76.516
#> p-value: <.001
#>
#> 95% confidence interval:
#> lower bound: -1.787
#> upper bound: -1.377A minimal example for the one sample test:
iris %>%
filter(Species == "virginica") %>%
ttest_onesample(outcome = Sepal.Length, null_mean = 6)
#>
#> One sample t-test
#>
#> Variables:
#> outcome: Sepal.Length
#>
#> Descriptives:
#> sample mean sd
#> Sepal.Length 6.588 0.636
#>
#> Hypotheses:
#> null: population mean equals 6
#> alternative: population mean not equal to 6
#>
#> Test results:
#> t-statistic: 6.539
#> degrees of freedom: 49
#> p-value: <.001
#>
#> 95% confidence interval:
#> lower bound: 6.407
#> upper bound: 6.769