Compute p-value

Compute a p-value from a null distribution and observed statistc. Simulation-based methods are (currently only) supported.

Learn more in vignette("infer").

get_p_value(x, obs_stat, direction)

get_pvalue(x, obs_stat, direction)

Arguments

x	Data frame of calculated statistics as returned by generate()
obs_stat	A numeric value or a 1x1 data frame (as extreme or more extreme than this).
direction	A character string. Options are "less", "greater", or "two_sided". Can also use "left", "right", or "both".

Value

A 1x1 tibble with value between 0 and 1.

Aliases

get_pvalue() is an alias of get_p_value(). p_value is a deprecated alias of get_p_value().

Examples

# find the point estimate---mean number of hours worked per week
point_estimate <- gss %>%
  specify(response = hours) %>%
  calculate(stat = "mean") %>%
  dplyr::pull()
#> Warning: Removed 1244 rows containing missing values.

# starting with the gss dataset
gss %>%
  # ...we're interested in the number of hours worked per week
  specify(response = hours) %>%
  # hypothesizing that the mean is 40
  hypothesize(null = "point", mu = 40) %>%
  # generating data points for a null distribution
  generate(reps = 10000, type = "bootstrap") %>%
  # finding the null distribution
  calculate(stat = "mean") %>%
  get_p_value(obs_stat = point_estimate, direction = "two_sided")
#> Warning: Removed 1244 rows containing missing values.
#> # A tibble: 1 x 1
#>   p_value
#>     <dbl>
#> 1  0.0182

# More in-depth explanation of how to use the infer package
vignette("infer")
#> Warning: vignette ‘infer’ not found