Deck 5: Introduction to Sampling

Question 1

A study of the population yields results referred to as ______________________ __________________, while a study of sample yields results referred to as _________________________________.

Answer 1

POPULATION PARAMETERS, STATISTICS

Question 2

Sampling instead of studying the entire population

A) Creates sampling error
B) May be due to physical reasons
C) May be due to economic reasons
D) May not accurately reflect the population
E) All of the above
F) None of the above

Answer 2

E

Question 3

Unbiased sampling gives each member of a population an _________________________ chance of being selected, while biased sampling gives each member an ______________________ chance of being selected.

Answer 3

EQUAL, UNEQUAL

Question 4

A professor wishes to study the attitudes of all sophomores at a college. This is referred to as ___________________, but asks only those enrolled in her introductory psychology class. This is referred to as _____________________.

Question 5

In the above scenario, what type of sampling was used?

A) A sample of convenience
B) A simple random sampling
C) An unbiased sampling
D) A sample of inconvenience

Question 6

Is the sample bias or unbiased?
a. A professor studying the attitudes of all sophomores at a college asks those who are enrolled in her psychology class. ________
b. A researcher doing a citywide survey on monthly spending at local grocery stores. ________
c. A magazine editor studying the opinion on a gun-control measure from all rifle owners, mails a questionnaire to only those who subscribe to her magazine. ________

Question 7

Random errors created by random sampling still exists in an unbiased sample. ________

Question 8

One cannot be certain that the results from the sample accurately reflect those results that would have been obtained by studying the entire population. ________

Question 9

In predicting the results of a city-side election, the researcher persistently spends weeks at the shopping mall asking shoppers how they intend to vote. Discuss how even a large sample may differ from the population of voters thereby creating bias.