![]() with 20 more variables: popamerindian, popasian, # popother, percwhite, percblack, percamerindan, # percasian, percother, popadults, perchsd, # percollege, percprof, poppovertyknown, # percpovertyknown, percbelowpoverty, # percchildbelowpovert, percadultpoverty, # percelderlypoverty, inmetro, category I also use the dplyr, tidyr, magrittr, and gridExtra packages. For the paired t-test I willustrate with the built in sleep data set. This tutorial leverages the midwest data that is provided by the ggplot2 package for the one and two-sample independent t-tests. Paired t-tests: Compare the means of two sets of paired samples, taken from two populations with unknown variance.Two-sample t-tests: Compare the means of two groups under the assumption that both samples are random, independent, and normally distributed with unknown but equal variances.One-sample t-tests: Compare the sample mean with a known value, when the variance of the population is unknown.t.test() & wilcox.test(): The basic functions you’ll leverage for the various t-tests. ![]() Replication requirements: What you’ll need to reproduce the analysis in this tutorial.First, I provide the data and packages required to replicate the analysis and then I walk through the basic operations to perform t-tests. ![]() This tutorial serves as an introduction to performing t-tests to compare two groups. This tutorial covers the basics of performing t-tests in R. There is also a widely used modification of the t-test, known as Welch’s t-test that adjusts the number of degrees of freedom when the variances are thought not to be equal to each other. It is known that under the null hypothesis, we can calculate a t-statistic that will follow a t-distribution with degrees of freedom. The null hypothesis is that the two means are equal, and the alternative is that they are not. The assumption for the test is that both groups are sampled from normal distributions with equal variances. One of the most common tests in statistics, the t-test, is used to determine whether the means of two groups are equal to each other.
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