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Babbie Ch 7 Vocab
| Question | Answer |
|---|---|
| Sampling | the process of selecting observations |
| Nonprobablility sampling (a.k.a. convenience/haphazard sampling) | Any technique in which samples are selected in some way not suggested by probability theory. Examples include reliance on available subjects as well as purposive (judgmental), quota, and snowball sampling. |
| Purposive (judgmental) sampling | A type of nonprobability sampling in which the unites to be observed are selected on the basis of the researcher’s judgment about which ones will be the most useful or representative. |
| Snowball sampling | a nonprobability sampling method, often employed in field research, whereby each person interviewed may be asked to suggest additional people for interviewing. |
| Quota Sampling | A type of nonprobability sampling in which units are selected into a sample on the basis of prespecified characteristics, so that the total sample will have the same distribution of characteristics assumed to exist in the populations being studied. |
| Informant | Someone who is well versed in the social phenomenon that you wish to study and who is wiling to tell you what he or she knows about it. Not to be confused with a respondent (a person who provides data for analysis by responding to a survey questionnaire) |
| Probability Sampling | the general term for samples selected in accord with probability theory, typically involving some random-selection mechanism. Specific types of ____ include EPSEM, PPS, simple random sampling, and systematic sampling. |
| Bias | those selected are not typical or representative of the larger populations they have been chosen from. |
| Representativeness | the quality of a sample of having the same distribution of characteristics as the population from which it was selected. ____ is enhanced by probability sampling and provides for generalizability and the use of inferential statistics. |
| EPSEM (equal probability of selection method) | A sample design in which each member of a population has the same chance of being selected into the sample. |
| Element | that unit of a population is composed and which is selected in a sample. Distinguished from units of analysis, which are used in data analysis. |
| Population | the theoretically specified aggregation of the elements in a study. |
| Study Population | that aggregation of elements from which a sample is actually selected. |
| Random Selection | A sampling method in which each element has an equal chance of selection independent of any other event in the selection process. |
| Sampling Unit | That element or set of elements considered for selection in some stage of sampling |
| Random Digit Dialing | computers are used to select random telephone numbers for interviewing. |
| Probability Theory | a branch of mathematics that provides the tools researchers need to devise sampling techniques that produce representative samples and to analyze the results of their sampling statistically. |
| Parameter | the summary description of a given variable in a population. |
| Sampling Distribution | the distribution of that statistic, considered as a random variable, when derived from a random sample of size n. |
| Statistic | the summary description of a variable in a sample, used to estimate a population parameter. |
| Sampling Error | degree of error to be expected by virtue of studying a sample instead of every1 (how close sample stats clustered ard T value). For probab sampling, the max error depends on sample size, the diversity of the population, and the confidence level. |
| Confidence Level | The estimated probability that a population parameter lie within a given confidence interval. Thus, we might be 95 percent confident that between 35 and 45 percent of all voters favor candidate A. |
| Confidence Interval | The range of values within which a population parameter is estimate to lie. |
| Sampling Frame | that list or quasi list of units composing a population from which a sample is selected. If the sample is to be representative of the population, it is essential that the sampling frame include all (or nearly all) members of the population. |
| Simple Random Sampling (SRS) | a type of probability sampling in which the units composing a population are assigned numbers. A set of random numbers is tehn generated, and the units having those numbers are included in the sample. |
| Systematic Sampling | a type of probability sampling in which every kth unit in a list is selected for inclusion in the sample. You compute k by dividing the size of the population by the desired sample size; k =sampling interval. |
| Sampling Interval | the standard distance between elements selected from a population for a sample. (population size/sample size) |
| Sampling Ratio | the proportion of elements in the population that are selected to be in a sample. ( sample size/population size) |
| Stratification | the grouping of the units composing a population into homogenous groups b4 sampling. This procedure (can b used w/ any sampling method &) improves the representativeness of a sample, at least in terms of the stratification of variables. |
| Cluster Sampling | multistage sampling in which natural groups (clusters) are sampled initially, with the members of each selected group being sub-sampled afterward. |
| PPS (probability proportionate to size) | this refers to a type of multistage cluster sample in which clusters are selected, not with equal probabilities (see EPSEM) but with probabilities proportionate to their size—as measured by the number of units to be subsampled. |
| Weighting | assigning different weights to cases that were selected into a sample with different probabilities of selection. In the simplest scenario, each case is given a weight equal to the inverse of its probability of selection. If all same chance, don't need. |
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