Overview

That lecture presented the statistical procedures that permit
researchers to use a sample mean to test hypotheses about
a population. These statistical procedures were based on a
few basic notions, which are summarized as follows:
 A sample mean is expected to more or less approximate
its population mean. This permits us to use the sample
mean to test a hypothesis about the population mean.
 The standard error provides a measure of how well a
sample mean approximates the population mean. The standard
error formula is:
 To quantify our inferences about the population, we
compare the obtained sample mean with the hypothesized
population mean by computing a zscore test statistic.
The ZTest statistic's formula is:
There is one major problem with this:
We don't usually know the population's standard
deviation, which is required to compute the zscore's
standard error.

This lecture presents the statistical procedures that permit
researchers to use a sample mean to test hypotheses about
a population, when the population standard deviation is
NOT known.
These procedures use the TTest, rather than the
ZTest. They are based on TScores,
which we first met in the lecture notes for Topic
5 .
