shade_p_value() plots p-value region(s) (using "area under the curve" approach) on top of the visualize() output. It should be used as \ggplot2\ layer function (see examples). shade_pvalue() is its alias.

Learn more in vignette("infer").

shade_p_value(obs_stat, direction, color = "red2", fill = "pink", ...)

shade_pvalue(obs_stat, direction, color = "red2", fill = "pink", ...)

Arguments

obs_stat

A numeric value or 1x1 data frame corresponding to what the observed statistic is.

direction

A string specifying in which direction the shading should occur. Options are "less", "greater", or "two-sided". Can also give "left", "right", "both", "two_sided", or "two sided". If NULL then no shading is actually done.

color

A character or hex string specifying the color of the observed statistic as a vertical line on the plot.

fill

A character or hex string specifying the color to shade the p-value region. If NULL then no shading is actually done.

...

Other arguments passed along to \ggplot2\ functions.

Value

A list of \ggplot2\ objects to be added to the visualize() output.

See also

shade_confidence_interval() to add information about confidence interval.

Examples

# find the point estimate---mean number of hours worked per week point_estimate <- gss %>% specify(response = hours) %>% calculate(stat = "mean") %>% dplyr::pull() # ...and a null distribution null_dist <- 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") # shade the p-value of the point estimate null_dist %>% visualize() + shade_p_value(obs_stat = point_estimate, direction = "two-sided")
# More in-depth explanation of how to use the infer package if (FALSE) { vignette("infer") }