BASIC STATISTICS CASE, SLP, AND THREAD DISCUSSION HOMEWORK

Module 4 - Home

Sampling

Modular Learning Outcomes

Upon successful completion of this module, the student will be able to satisfy the following outcomes:

•Case

◦Define sampling methods and terminology.

◦Identify situations when sampling is appropriate.

◦Draw the proper inferences about the population after the sample has been evaluated.

◦Describe the process of selecting and evaluating a sample.

•SLP

◦Explain the effects of a larger samples size in relation to data.

◦Describe the process of selecting and evaluating a sample.

◦Draw conclusions from comparing two data sets.

•Discussion

◦Describe the process of selecting and evaluating a sample.

Module Overview

In many situations, it is desirable to reach a statistical conclusion about a population of data but that set of data is far too large to test completely. Thus, we have long employed the concept of statistical sampling.

The process is very straight forward. First, we select a representative sample of observations from the population. This may be random or some variation of a random sample. Second, we test the sample we have selected. Third, based on the results of this sample testing, we make an inference about the population.

It is essential to understand that we do not know the true facts about the population but we can only make an inference through this sampling technique. Statistical sampling tools take this sampling error into consideration in the manner in which the results are expressed