descr(iris)
Variables
Total
p
(N=150)
Sepal.Length
N 150 <0.001tt1
mean 5.8
sd 0.83
median 5.8
Q1 - Q3 5.1 – 6.4
min - max 4.3 – 7.9
Sepal.Width
N 150 <0.001tt1
mean 3.1
sd 0.44
median 3
Q1 - Q3 2.8 – 3.3
min - max 2 – 4.4
Petal.Length
N 150 <0.001tt1
mean 3.8
sd 1.8
median 4.3
Q1 - Q3 1.6 – 5.1
min - max 1 – 6.9
Petal.Width
N 150 <0.001tt1
mean 1.2
sd 0.76
median 1.3
Q1 - Q3 0.3 – 1.8
min - max 0.1 – 2.5
Species
setosa 50 (33%) >0.999chi1
versicolor 50 (33%)
virginica 50 (33%)
tt1 Student’s one-sample t-test
chi1 Chi-squared goodness-of-fit test
descr(
  iris,
  "Species",
  group_labels = list(setosa = "My custom group label"),
  var_options = list(Sepal.Length = list(label = "My custom variable label"))
)
Variables
My custom group label
versicolor
virginica
Total
p
(N=50) (N=50) (N=50) (N=150)
My custom variable label
N 50 50 50 150 <0.001F
mean 5 5.9 6.6 5.8
sd 0.35 0.52 0.64 0.83
median 5 5.9 6.5 5.8
Q1 - Q3 4.8 – 5.2 5.6 – 6.3 6.2 – 6.9 5.1 – 6.4
min - max 4.3 – 5.8 4.9 – 7 4.9 – 7.9 4.3 – 7.9
Sepal.Width
N 50 50 50 150 <0.001F
mean 3.4 2.8 3 3.1
sd 0.38 0.31 0.32 0.44
median 3.4 2.8 3 3
Q1 - Q3 3.2 – 3.7 2.5 – 3 2.8 – 3.2 2.8 – 3.3
min - max 2.3 – 4.4 2 – 3.4 2.2 – 3.8 2 – 4.4
Petal.Length
N 50 50 50 150 <0.001F
mean 1.5 4.3 5.6 3.8
sd 0.17 0.47 0.55 1.8
median 1.5 4.3 5.5 4.3
Q1 - Q3 1.4 – 1.6 4 – 4.6 5.1 – 5.9 1.6 – 5.1
min - max 1 – 1.9 3 – 5.1 4.5 – 6.9 1 – 6.9
Petal.Width
N 50 50 50 150 <0.001F
mean 0.25 1.3 2 1.2
sd 0.11 0.2 0.27 0.76
median 0.2 1.3 2 1.3
Q1 - Q3 0.2 – 0.3 1.2 – 1.5 1.8 – 2.3 0.3 – 1.8
min - max 0.1 – 0.6 1 – 1.8 1.4 – 2.5 0.1 – 2.5
F F-test (ANOVA)
descr(
  iris,
  "Species",
  group_labels = list(setosa = "My custom group label"),
  var_options = list(Sepal.Length = list(label = "My custom variable label")),
  format_options=list(caption="Test Caption")
)
Test Caption
Variables
My custom group label
versicolor
virginica
Total
p
(N=50) (N=50) (N=50) (N=150)
My custom variable label
N 50 50 50 150 <0.001F
mean 5 5.9 6.6 5.8
sd 0.35 0.52 0.64 0.83
median 5 5.9 6.5 5.8
Q1 - Q3 4.8 – 5.2 5.6 – 6.3 6.2 – 6.9 5.1 – 6.4
min - max 4.3 – 5.8 4.9 – 7 4.9 – 7.9 4.3 – 7.9
Sepal.Width
N 50 50 50 150 <0.001F
mean 3.4 2.8 3 3.1
sd 0.38 0.31 0.32 0.44
median 3.4 2.8 3 3
Q1 - Q3 3.2 – 3.7 2.5 – 3 2.8 – 3.2 2.8 – 3.3
min - max 2.3 – 4.4 2 – 3.4 2.2 – 3.8 2 – 4.4
Petal.Length
N 50 50 50 150 <0.001F
mean 1.5 4.3 5.6 3.8
sd 0.17 0.47 0.55 1.8
median 1.5 4.3 5.5 4.3
Q1 - Q3 1.4 – 1.6 4 – 4.6 5.1 – 5.9 1.6 – 5.1
min - max 1 – 1.9 3 – 5.1 4.5 – 6.9 1 – 6.9
Petal.Width
N 50 50 50 150 <0.001F
mean 0.25 1.3 2 1.2
sd 0.11 0.2 0.27 0.76
median 0.2 1.3 2 1.3
Q1 - Q3 0.2 – 0.3 1.2 – 1.5 1.8 – 2.3 0.3 – 1.8
min - max 0.1 – 0.6 1 – 1.8 1.4 – 2.5 0.1 – 2.5
F F-test (ANOVA)
Tooth2 <- ToothGrowth
Tooth2$categorical <- factor(sample(c("a", "b"), nrow(Tooth2), TRUE))
descr(Tooth2, "supp")
Variables
OJ
VC
Total
p
CI
(N=30) (N=30) (N=60)
len
N 30 30 60 0.061tt2 [-0.17, 7.6]t
mean 21 17 19
sd 6.6 8.3 7.6
median 23 16 19
Q1 - Q3 15 – 26 11 – 23 13 – 25
min - max 8.2 – 31 4.2 – 34 4.2 – 34
dose
N 30 30 60 >0.999tt2 [-0.33, 0.33]t
mean 1.2 1.2 1.2
sd 0.63 0.63 0.63
median 1 1 1
Q1 - Q3 0.5 – 2 0.5 – 2 0.5 – 2
min - max 0.5 – 2 0.5 – 2 0.5 – 2
categorical
a 11 (37%) 15 (50%) 26 (43%) 0.297chi2 [-0.39, 0.12]PWa
b 19 (63%) 15 (50%) 34 (57%)
tt2 Welch’s two-sample t-test
chi2 Pearson’s chi-squared test
t CI for difference in means derived from the t-distribution
PWa CI for difference in proportions derived from a normal (“Wald”) approximation