The population parameter for firefighters on Long Island is 79% male. The sample statistic for three fire stations is 73% male. Why wasn't the sample statistic the same as the population parameter?
a. Sampling error was present.
b. Random variation might have occurred.
c. Systematic variation might have occurred.
d. The sample was fairly small.
e. The sample was not perfectly representative.
f. The population parameter is inaccurate.
ANS: A, B, C, D, E
The difference between a sample statistic and a population parameter is called the sampling error. A large sampling error means that the sample is not providing a precise picture of the population; it is not representative. Sampling error is usually larger with small samples and decreases as the sample size increases. Sampling error reduces the power of a study, or the ability of the statistical analyses conducted to detect differences between groups or to describe the relationships among variables. Sampling error occurs as a result of random variation and systematic variation.
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