Population

Chapter 7

Populations and Sampling

7

Populations and Sampling

The Rationale of Sampling Steps in Sampling Types of Sampling Inferential Statistics: A Look Ahead The Case Study Approach The Rationale of Sampling

In Chapter One, we established the fact that inductive reasoning is an essential part of the scientific process. Recall that inductive reasoning moves from individual observations to general principles. If a researcher can observe a characteristic of interest in all members of a population, he can with confidence base conclusions about the population on these observations. This is perfect induction. If he, on the other hand, observes the characteristic of interest in some members of the population, he can do no more than infer that these observations will be true of the whole. This is imperfect induction, and is the basis for sampling.1 The population of interest is usually too large or too scattered geographically to study directly. By correctly drawing a sample from a specific population, a researcher can analyze the sample and make inferences about population characteristics.

Population Sampling Biased Samples Randomization

The Population

A “population” consists of all the subjects you want to study. “Southern Baptist missionaries” is a population. So is “ministers of youth in SBC churches in Texas.” So is “Christian school children in grades 3 and 4.” A population comprises all the possible cases (persons, objects, events) that constitute a known whole.2

Sampling

Sampling is the process of selecting a group of subjects for a study in such a way that the individuals represent the larger group from which they were selected.3 This representative portion of a population is called a sample.4

Donald Ary, Lucy Cheser Jacobs, and Asghar Razavieh, Introduction to Research in Education, (New York: Holt, Rinehart and Winston, Inc., 1972), 160 2 Ibid., p. 125 3 L. R. Gay, Educational Research: Competencies for Analysis and Application, 3rd ed.,...