Infer: a grammar for statistical inference
The objective of this package is to perform statistical inference using a grammar that illustrates the underlying concepts and a format that coheres with the tidyverse.
These examples assume that mtcars has been overwritten so that the variables cyl, vs, am, gear, and carb are factors:
mtcars <- as.data.frame(mtcars) %>%
mutate(cyl = factor(cyl),
vs = factor(vs),
am = factor(am),
gear = factor(gear),
carb = factor(carb))
One categorical (2 level) variable (implemented up to calculate())
mtcars %>%
specify(response = am) %>% # alt: am ~ 1
hypothesize(null = "point", p = c("1" = .25)) %>%
generate(reps = 100, type = "simulate") %>%
calculate(stat = "prop")
Two categorical (2 level) variables
mtcars %>%
specify(am ~ vs) %>% # alt: response = am, explanatory = vs
hypothesize(null = "independence") %>%
generate(reps = 100, type = "permute") %>%
calculate(stat = "diff in props")
One categorical (>2 level) - GoF
mtcars %>%
specify(cyl ~ NULL) %>% # alt: response = cyl
hypothesize(null = "point", p = c("4" = .5, "6" = .25, "8" = .25)) %>%
generate(reps = 100, type = "simulate") %>%
calculate(stat = "Chisq")
Two categorical (>2 level) variables
mtcars %>%
specify(cyl ~ am) %>% # alt: response = cyl, explanatory = am
hypothesize(null = "independence") %>%
generate(reps = 100, type = "permute") %>%
calculate(stat = "Chisq")
One numerical variable one categorical (2 levels) (diff in means)
mtcars %>%
specify(mpg ~ am) %>% # alt: response = mpg, explanatory = am
hypothesize(null = "independence") %>%
generate(reps = 100, type = "permute") %>%
calculate(stat = "diff in means")
One numerical one categorical (>2 levels) - ANOVA
mtcars %>%
specify(mpg ~ cyl) %>% # alt: response = mpg, explanatory = cyl
hypothesize(null = "independence") %>%
generate(reps = 100, type = "permute") %>%
calculate(stat = "F")
Two numerical vars - SLR
mtcars %>%
specify(mpg ~ hp) %>% # alt: response = mpg, explanatory = cyl
hypothesize(null = "independence") %>% # or "slope = 0"
generate(reps = 100, type = "permute") %>%
calculate(stat = "slope")
One numerical (one mean)
mtcars %>%
specify(response = mpg) %>%
generate(reps = 100, type = "bootstrap") %>%
calculate(stat = "mean")
One categorical (one proportion) (not yet implemented)
mtcars %>%
specify(response = am) %>%
generate(reps = 100, type = "bootstrap") %>%
calculate(stat = "prop")
One numerical variable one categorical (2 levels) (diff in means)
mtcars %>%
specify(mpg ~ am) %>%
generate(reps = 100, type = "bootstrap") %>%
calculate(stat = "diff in means")
Two categorical variables (diff in proportions) (not yet implemented)
mtcars %>%
specify(am ~ vs) %>%
generate(reps = 100, type = "bootstrap") %>%
calculate(stat = "diff in prop")
Two numerical vars - SLR (not yet implemented)
mtcars %>%
specify(mpg ~ hp) %>%
generate(reps = 100, type = "bootstrap") %>%
calculate(stat = "slope")