Section 1.2 - Random Samples Flashcards
Explain the importance of random samples. Construct a simple random sample using random numbers. Simulate a random process. Describe stratified sampling, cluster sampling, systematic sampling, multistage sampling, and convenience sampling.
A ________ of n measurements from a population is a subset of the population selected in such a manner that every sample of size from the population has an equal chance of being selected.
simple random sample
What are three important features of a Simple Random Sample?
- Every sample of specified size n from the population has an equal chance of being selected.
- No researcher bias occurs in the items selected for the sample.
- A random sample may not always reflect the diversity of the population. For instance, from a population of 10 cats and 10 dogs, a random sample of size could consist of all cats.
An easy way to select random numbers is to use a:
random number tell
The term ____ should not be confused with haphazard
random
How to draw a random sample:
- Number all members of the population sequentially.
- Use a table, calculator, or computer to select random numbers from the numbers assigned to the population members.
- Create the sample by using population members with numbers corresponding to those randomly selected.
Another important use of random-numbers is in _____.
Simulation
The word simulation refers to:
The process of providing numerical imitations of “real” phenomena
Sampling with replacement means:
although an item is selected for the sample, it is not removed from the population.
What is Stratified Sampling?
Divide the entire population into subgroups (strata). Draw random samples from each stratum.
What is Systematic Sampling?
Number all members of the population sequentially. Then from a random starting point, include every Kth member of the population in the sample.
The advantage of systematic sample is that it is easy to get. However, one danger in using systematic sampling is:
When the population is repetitive or cyclic in nature.
What is Cluster Sampling?
Divide the entire population into pre-existing segments or clusters, make a random selection of clusters. Include every member of selected cluster in the sample.
Cluster sampling is primarily used by:
government agencies and certain private research organizations.
What is Convenience Sampling?
Create a sample by using data from population members that are readily available.
Convenience Sampling runs the risk of ______
being severely biased.
Sampling Frame?
A list of individuals from which a sample is actually selected.
Undercoverage?
Results from omitting population members from the Sample Frame.
Sampling Error?
the difference between measurements from a sample and corresponding measurements from the respective population. It is caused by the fact that the sample does not perfectly represent the population.
A nonsampling error is:
the result of poor sample design, sloppy data collection, faulty measuring instruments, bias in questionnaires, and so on.
Explain the difference between a stratified sample and a cluster sample.
In a stratified sample, random samples from each stratum are included. In a cluster sample, the clusters to be included are selected at random, and then all members of each selected cluster are included.
Explain the difference between a simple random sample and a systematic sample
In a systematic sample, the only samples possible are those including every kth item from the random starting position, while in a simple random sample, every sample of size n has an equal chance of being included
Marcie conducted a study of the cost of breakfast cereal. She recorded the costs of several boxes of cereal. However, she neglected to take into account the number of servings in each box. Someone told her not to worry because she just had some sampling error. Comment on that advice
The advice is wrong. A sampling error accounts only for the difference in results based on the use of a sample rather than of the entire population.
In a random sample of 50 students from a large university, all the students were between 18 and 20 years old. Can we conclude that the entire population of students at the university is between 18 and 20 years old? Explain.
No, even though the sample is random, some students younger than 18 or older than 20 may not have been included in the sample.
Greg took a random sample of size 100 from the population of current season ticket holders to State College men’s basketball games. Then he took a random sample of size 100 from the population of current season ticket holders to State College women’s basketball games.
What sampling technique did Greg use to sample from the population of current season ticket holders to all State College basketball games played by either men or women?
Stratified.