Busy. Please wait.
Log in with Clever
or

show password
Forgot Password?

Don't have an account?  Sign up 
Sign up using Clever
or

Username is available taken
show password


Make sure to remember your password. If you forget it there is no way for StudyStack to send you a reset link. You would need to create a new account.
Your email address is only used to allow you to reset your password. See our Privacy Policy and Terms of Service.


Already a StudyStack user? Log In

Reset Password
Enter the associated with your account, and we'll email you a link to reset your password.

Babbie Ch 7 Vocab

Quiz yourself by thinking what should be in each of the black spaces below before clicking on it to display the answer.
        Help!  

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.  
🗑


   

Review the information in the table. When you are ready to quiz yourself you can hide individual columns or the entire table. Then you can click on the empty cells to reveal the answer. Try to recall what will be displayed before clicking the empty cell.
 
To hide a column, click on the column name.
 
To hide the entire table, click on the "Hide All" button.
 
You may also shuffle the rows of the table by clicking on the "Shuffle" button.
 
Or sort by any of the columns using the down arrow next to any column heading.
If you know all the data on any row, you can temporarily remove it by tapping the trash can to the right of the row.

 
Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.

  Normal Size     Small Size show me how
Created by: adis
Popular Science sets