lec7 - Chapter 7 Sampling(Reminder Dont forget to utilize...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Chapter 7 Sampling (Reminder: Don’t forget to utilize the concept maps and study questions as you study this and the other chapters.) The purpose of Chapter 7 it to help you to learn about sampling in quantitative and qualitative research. In other words, you will learn how participants are selected to be part of empirical research studies. Sampling refers to drawing a sample (a subset) from a population (the full set). The usual goal in sampling is to produce a representative sample (i.e., a sample that is similar to the population on all characteristics, except that it includes fewer people because it is a sample rather than the complete population). Metaphorically, a perfect representative sample would be a "mirror image" of the population from which it was selected (again, except that it would include fewer people). Terminology Used in Sampling Here are some important terms used in sampling: A sample is a set of elements taken from a larger population. The sample is a subset of the population which is the full set of elements or people or whatever you are sampling. A statistic is a numerical characteristic of a sample, but a parameter is a numerical characteristic of population. Sampling error refers to the difference between the value of a sample statistic, such as the sample mean, and the true value of the population parameter, such as the population mean. Note: some error is always present in sampling. With random sampling methods, the error is random rather than systematic. The response rate is the percentage of people in the sample selected for the study who actually participate in the study. A sampling frame is just a list of all the people that are in the population. Here is an example of a sampling frame (a list of all the names in my population, and they are numbered). Note that the following sampling frame also has information on age and gender included in case you want to draw some samples and do some calculations.
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
The two major types of sampling in quantitative research are random sampling and nonrandom sampling. The former produces representative samples. The latter does not produce representative samples. Simple Random Sampling The first type of random sampling is called simple random sampling . It's the most basic type of random sampling. It is an equal probability sampling method (which is abbreviated by EPSEM ). Remember that EPSEM means "everyone in the sampling frame has an equal chance of being in the final sample." You should understand that using an EPSEM is important because that is what produces "representative" samples (i.e., samples that represent the populations from which they were selected)! You will see below that, simple random samples are not
Background image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

Page1 / 7

lec7 - Chapter 7 Sampling(Reminder Dont forget to utilize...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online