Question

Which statement about sampling error is inaccurate?
Sampling error is a measure of degree to which a sample accurately estimates what the population is thinking.
Sampling error decreases as the size of the sample increases.
Sampling error is largely a function of the size of the population being sampled—for example, a much larger sample is required to obtain the same sampling error for a state than for a city within that state.
Sampling error results from the fact that a sample is being used to estimate what the entire population is thinking.

Answer 1

Answer:

First statement

Explanation:

Sampling error is not an accurate estimate of what a population is thinking. Sampling error is a statistical error about a group of people. For example, if you only asked a certain sex about something, and assumed everyone else thought the same way, that would be a statistical sampling error, meaning the data is wrong and biased.

Answer 2

The statement that is inaccurate about the sampling error is that sampling error is a measure of the degree to which a sample accurately estimates what the population is thinking.

What is sampling error?

A sampling error is defined as an analyst that fails to select a sample and accurately represents the full population of data.

Sampling error isn't a reliable indicator of what a group of people is thinking. A statistical inaccuracy about a group of people is known as sampling error. This type of error also decreases the size of sample that increases.

Therefore, option A is correct.

Learn more about the sampling error, refer to:

https://brainly.com/question/13286220

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