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VII. Sampling Distributions
Prerequisites
none
- Introduction
- Basic Demo
- Sample Size Demo
- Central Limit Theorem
Demo
- Sampling Distribution
of the Mean
- Sampling
Distribution of Difference Between Means
- Sampling Distribution
of Pearson's r
- Sampling Distribution
of a Proportion
- Exercises
- PDF Files (in
.zip archive)
The concept of a sampling distribution is perhaps
the most basic concept in inferential statistics. It is also
a difficult concept to teach because a sampling distribution
is a theoretical distribution rather than an empirical distribution.
The
introductory section defines the concept and gives an
example for both a discrete and a continuous distribution.
It also discusses how sampling distributions are used in inferential
statistics.
The Basic Demo is an interactive demonstration
of sampling distributions. It is designed to make the abstact
concept of sampling distributions more concrete. The Sample Size
Demo allows you to investigate the effect of sample size on the
sampling distribution of the mean. The Central Limit Theorem
(CLT) Demo is an interactive illustration of a very important
and counter-intuitive characteristic of the sampling distribution
of the mean.
The remaining sections of the chapter concern the
sampling distributions of important statistics: the Sampling
Distribution of the Mean, the Sampling Distribution of the Difference
Between Means, the Sampling Distribution of r, and the Sampling
Distribution of a Proportion.
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