simCImean | R Documentation |
Show a sequence of confidence intervals, all calculated from repeated samples of simulated data from the same normal population, and show which intervals contain the true population mean.
simCImean(ns, n, mu=0, sigma=1, cl=0.95, seed=NULL,
show_data=FALSE, show_title=TRUE,
miss_only=FALSE, color_hit="gray40", color_miss="red",
grid="grey90", ylim_bound=NULL, pause=FALSE,
main=NULL, pdf_file=NULL, width=5, height=5, ...)
ns |
Number of samples, that is, repetitions of the experiment. |
n |
Size of each sample. |
mu |
Population mean. |
sigma |
Population standard deviation. |
cl |
Confidence level. |
seed |
Default seed is the R default. Enter a positive integer value to obtain a reproducible result, the same result for the same seed. |
show_data |
Plot the data for each sample over the confidence interval. |
show_title |
Place a title on the graph that contains the parameter values_ |
miss_only |
For the text output, only display information for samples that missed the mean. |
color_hit |
Color of the confidence intervals that contains the mean. |
color_miss |
Color of the confidence intervals that miss the mean. |
grid |
Color of the grid lines. |
ylim_bound |
Specify the maximum deviation of the mean in either direction for the extent of the vertical axis_ |
pause |
Build the graph and the text output, pausing after each confidence interval. |
main |
Title of graph. |
pdf_file |
Name of optional pdf file to which graphics are redirected. |
width |
Width of the pdf file in inches. |
height |
Height of the pdf file in inches. |
... |
Other parameter values. |
Simulate random normal data and display the resulting confidence intervals, with or without the data overlaid on each confidence interval. Highlight confidence intervals that miss the underlying population mean.
David W. Gerbing (Portland State University; gerbing@pdx.edu)
# 25 confidence intervals with a sample size each of 100
# mu=0, sigma=1, that is, sample from the standard normal
simCImean(25, 100)
# set the seed for a reproducible result with the same seed
simCImean(25, 100, seed=43)
# 25 confidence intervals with a sample size each of 100
# mu=100, sigma=15
# overlay the data over each confidence interval
simCImean(25, 100, mu=100, sigma=15, show_data=TRUE)
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