Compute a p-value from a null distribution and observed statistic. 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)

x | Data frame of calculated statistics as returned by |
---|---|

obs_stat | A numeric value or a 1x1 data frame (as extreme or more extreme than this). |

direction | A character string. Options are |

A 1x1 tibble with value between 0 and 1.

`get_pvalue()`

is an alias of `get_p_value()`

.
`p_value`

is a deprecated alias of `get_p_value()`

.

Though a true p-value of 0 is impossible, `get_p_value()`

may return 0 in
some cases. This is due to the simulation-based nature of the {infer}
package; the output of this function is an approximation based on
the number of `reps`

chosen in the `generate()`

step. When the observed
statistic is very unlikely given the null hypothesis, and only a small
number of `reps`

have been generated to form a null distribution,
it is possible that the observed statistic will be more extreme than
every test statistic generated to form the null distribution, resulting
in an approximate p-value of 0. In this case, the true p-value is a small
value likely less than `3/reps`

(based on a poisson approximation).

In the case that a p-value of zero is reported, a warning message will be raised to caution the user against reporting a p-value exactly equal to 0.

# find the point estimate---mean number of hours worked per week point_estimate <- gss %>% specify(response = hours) %>% calculate(stat = "mean") %>% dplyr::pull() # 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 = 1000, type = "bootstrap") %>% # finding the null distribution calculate(stat = "mean") %>% get_p_value(obs_stat = point_estimate, direction = "two-sided")#> # A tibble: 1 x 1 #> p_value #> <dbl> #> 1 0.042