Which of the Following Are Not True Concerning Sampling Error

question 50

Multiple Choice

Which of the following are not true concerning sampling error?

• A) if many independent random samples are drawn from a population, then the sample statistics from those samples are distributed in a predictable way around the population parameter
• B) probability theory allows us to use a formula to estimate how closely the sample statistics are clustered
• C) the standard error identifies how spread out or clustered the sample statistics are around the population parameter
• D) sampling error allows us to know if we selected the wrong subjects for our sample

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Definitions:

μ

It signifies the mean or average of a population in statistics, representing the central location of a data set.

σ

The symbol representing the standard deviation of a population, indicating the dispersion of data points from the mean in a population.

Normally Distributed

Characterizes a probability distribution with symmetry around its mean, illustrating that occurrences close to the mean are more common than those distant from the mean.

Standard Deviation

A measure of the dispersion or variability of a set of values, indicating how much the values deviate from the mean.