t_test: 2 Sample t-Test

In rsap: Basic Statistics and Data Analysis

Description

Calculates and displays two sample t-test with intermediate calculations

Usage

t_test(xbar,sd,n,var.equal=F,alpha=0.05,alternative = c("two.sided", 
    "less", "greater"), method = c("p.value", "conf.int", "crit.val"))

S3 method for formula

t_test(formula,data,subset,var.equal=F,alpha=0.05,alternative = c("two.sided", 
    "less", "greater"), method = c("p.value", "conf.int", "crit.val"))

Arguments

xbar	vector containing the two sample means
sd	vector of two sample standard deviations
n	vector of sample size for both samples
formula	standard formula argument of the form response~group
data	data set to use for analysis
subset	vector specifying the observations to be used
var.equal	logical specifying whether to assume equality of variances
alpha	specification of the Type I error rate
alternative	string indicating whether to conduct a two-sided or a single sided alternative
method	string indicating whether to use the p-value, critical value, or confidence interval approach to carry out the test

Details

This function performs the standard two sample t-test but includes in the output all of the intermediate details including the critical values, the degrees of freedom, and the pooled standard deviation. The output is displayed using the Hypothesis testing logic/framework.

Value

t_test writes out the standard notation for the hypotheses for the population mean. Next it displays the appropriate decision rule for each of the different methods. Then the function returns the summary statistics and all the nescicary calculations. Finally, it states the statistical conclusion in terms of the hypotheses.

Author(s)

Timothy Hess [e-mail]

Examples

data(sleep)
t_test(extra~group,data=sleep)  # 2-sided p-value approach

t_test(extra~group,data=sleep,method="crit.val")  # 2-sided critical value approach

rsap documentation built on May 2, 2019, 4:53 p.m.