Add information about p-value region(s)
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", ...)
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 |
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 |
... |
Other arguments passed along to \ggplot2\ functions. |
A list of \ggplot2\ objects to be added to the visualize()
output.
shade_confidence_interval() to add information about confidence
interval.
# 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
## Not run:
vignette("infer")
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.