11COMPARING MEANS USING T-TESTS
Experiments whose outcome measures are quantitative variables are often analyzed by comparing means. The Student's t-test is the most commonly used statistical test for comparing two means or for comparing an observed mean with a known value. If more than two groups are observed, an analysis of variance (ANOVA) is used to compare means across groups (discussed in Chapter 13).
11.1 PERFORMING A ONE-SAMPLE T-TEST
A one-sample t-test is often used to compare an observed mean with a known or “gold standard” value. For example, in a quality control setting, you may be interested in comparing a sample of data to an expected outcome, such as the observed calories of liquid in cans of baby formula against the claim on the label. The purpose of the one-sample t-test, in this case, is to determine if there is enough evidence to dispute the claim. In general, for a one-sample t-test you obtain a random sample from some population and then compare the observed sample mean to some fixed value. The typical hypotheses for a one-sample t-test are as follows:
- : The population mean is equal to a hypothesized value, ...
Get SAS Essentials: Mastering SAS for Data Analytics, 2nd Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.