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babunello [35]
4 years ago
7

Why do we prefer the t procedures to the z procedures for inference about a population mean? Group of answer choices z requires

that you know the population standard deviation σ which may be unrealistic. z can be used only for large samples. t does not require your data to be a random sample from the population. z requires that you know the population mean
Mathematics
1 answer:
denis-greek [22]4 years ago
5 0

Answer:

Correct option:

"z requires that you know the population standard deviation σ which may be unrealistic."

Step-by-step explanation:

The hypothesis test for significant population mean <em>μ</em> can be done either using the <em>z</em>-distribution of <em>t</em>-distribution.

Both the distribution require certain conditions to be fulfilled to use.

For using a <em>z</em>-distribution to perform a hypothesis test for <em>μ</em> the conditions to fulfilled are:

  • Population is Normally distributed.
  • The population standard deviation is known.
  • The sample selected is large.

For using a <em>t</em>-distribution to perform a hypothesis test for <em>μ</em> the conditions to fulfilled are:

  • Population is Normally distributed.
  • The sample selected is randomly selected.

If the population standard deviation is not known and we have to compute the sample standard deviation then use the <em>t</em>-distribution to perform the test for population mean.

Thus, the correct option is:

"z requires that you know the population standard deviation σ which may be unrealistic."

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