CJUS 3101 Final Flashcards
Sampling Frame
Probability Sample
Equal chance of selection
Probability Sample
Random Chance or selection
Probability Sample
Generalizability
Probability Sample
Unknown chance of selection
Non-Probability Sample
No sampling frame
Non-Probability Sample
Non-random selection - selected for a reason
Non-Probability Sample
Non-generalizable
Non-Probability Sample
All of the individuals or cases we are interested in studying
Population
A subset or smaller group selected from our population
Sample
The process of applying the results we get from our sample to the population
Generalization
This is what sampling sets out to achieve
Representative Sample
Boundaries of the population being sampled
Parameters
All of the people or elements of the population have an equal chance of being selected for the sample
Probability Sampling
Gold standard of sampling, everyone in the population has an equal and independent chance of being selected for the sample
Simple random sampling
a list of everyone or object in the population
Sampling Frame
A modified form of SRS. Instead of the selection being random there is a patter
Systematic Sampling
- Define target population
- Determine the desired sample size
Sampling Interval
How do you find sampling interval?
Divide your sample size into the number of persons by the number of persons in your sampling frame
- If you had 100 persons in your sampling frame and wanted to sample 20 persons
100
—– = 5
20
Use this type of sampling when the variable is rare and would be hard to obtain through SRS
Stratified Sampling
The population is divided into subgroups and you select from each of the subgroups
Stratified Sampling
This type of sampling is utilized in situations when you cannot construct a sampling frame because it is to difficult.
Cluster Sampling
Use this type of sampling when you have more than one sampling frame of clusters
Multistage cluster sampling
as our sample size increases the sampling distribution will equal the mean of the population distribution
Central Limit Theorem
The standard deviation of the sampling distribution
Standard Error
The range of values that probably include the real value
Confidence Interval
a * denotes or means that our estimate is probably correct and not due to chance or sampling error.
Statistical Significance
This is when we conclude that our statistic represents the population when in fact it does not.
Type 1 Error
The elements do not have an equal chance of being selected
Non-Probability Sampling