Research methods chapter 8 Sampling

Representativeness and probability of selection

Although the term "representativeness" has no precise, scientific definition, it carries a commonsense meaning that makes it useful in the discussion of sampling. As we'll use the term here, a sample is representative of the population from which it is selected if the aggregate characteristics of the sample closely approximate those some aggregate characteristics in the population.

Conscious and unconscious sampling bias

In connection with sampling bias simply means that those selected are not "typical" or "representative" of the larger populations from which they have been chosen. This kind of bias is virtually inevitable when a researcher picks subjects casually

Probability theory and sampling distribution summed up

Random selection permits the researcher to use probability theory to estimate the accuracy of findings drawn from a sample. All statements of accuracy in sampling must specify both a confidence level and a confidence interval. The researcher must report that he or she is x percent confident that the population parameter is between two specific values.

Probability sampling

a special type of sampling that enables us to make statical generalizations to a larger population, a method of selection in which each member of a population has a known chance or probability of being selected. Knowing the probability that any individual member of a population could be selected makes it possible for us to make predictions that our sample accurately represents the larger population.

Standard error

a valuable piece of information in probability theory because it indicates how closely the sample estimates will be distributed around the population parameter. The standard error tells us how sample statistics will be dispersed or clustered around a population parameter

Sampling frame

is a list of elements in a population that is used to select a sample

The use of sampling

is ordinarily used to select observations for one of two related reasons. 1) it is often not possible to collect information from all persons or other units we wish to study 2) it is often not necessary to collect data from all persons or other units

The sampling distribution of 10 cases

is the defined as the range of sample statistics one obtains when many samples are selected

Sample statistic

summary description of a given variable in the sample

Sampling

the process of selecting observations.

Confidence levels and confidence intervals

the result of these inferences and estimations is that we are able to estimate a population parameter and also the expected degree of error on the basis of one sample drawn from a population

Population

the theoretically specified grouping of study elements, a population parameter is the value for a given variable in a population

Sample element

unit about which information is collected and that provides the basis of analysis