Mean.test {LearningStats}

One Sample Mean Test of a Normal Population

Description

Mean.test allows to compute hypothesis tests for a Normal population mean in both scenarios: known and unknown population variance.

Usage

Mean.test(x, mu0, sigma = NULL, sc = NULL, s = NULL, n = NULL,
  alternative = "two.sided", alpha = 0.05, plot = TRUE, lwd = 1)

Arguments

x

a numeric vector of data values or, if single number, estimated mean.

mu0

a single number corresponding with the mean to test.

sigma

population standard deviation. Defaults to NULL, if specified, a t-test with known variance will be performed.

sc

cuasi-standard deviation of sample x. By default computes the cuasi-standard deviation of argument x.

s

sample standard deviation of sample x. Defaults to NULL, if provided, it computes the cuasi-standard deviation.

n

sample size. By default length of argument x.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".

alpha

a single number in (0,1), significance level.

plot

a logical value indicating whether to display a graph including the test statistic value for the sample, its distribution, the rejection region and p-value.

lwd

single number indicating the line width of the plot.

Details

The formula interface is applicable when the user provides the sample and also when the user provides the value of the sample characteristics (sample mean, cuasi-standard deviation or sample standard deviation, jointly with the sample size).

Value

A list with class "lstest" and "htest" containing the following components:

statistic

the value of the test statistic.

parameter

the degrees of freedom of the statistic's distribution. NULL for the Normal distribution.

p.value

the p-value of the test.

estimate

the sample mean.

null.value

the value specified by the null.

alternative

a character string describing the alternative.

method

a character string indicating the method used.

data.name

a character string giving the names of the data.

alpha

the significance level.

dist.name

a character string indicating the distribution of the test statistic.

statformula

a character string with the statistic's formula.

reject.region

a character string with the reject region.

unit

a character string with the units.

Examples

x <- rnorm(50, mean = 4, sd = 2)
#unknown sigma
Mean.test(x, mu0 = 3.5)
Mean.test(mean(x), sc = sd(x),  n = length(x), mu0 = 3.5)
#known sigma
Mean.test(x, mu0 = 3.5, sigma = 2)