The significance level is a measure of reliability that measures how frequently the conclusion about a population will be wrong in the long run.

The confidence level is a measure of reliability that measures the proportion of times that an estimating procedure will be correct.

PLEASE NOTE: The definitions above are what you need to know for test 1. Later in the course though, these definitions will not be sufficient. A better set of definitions for the chapters AFTER Test #1 are given below. You can ignore them for now, but I thought I should include them here to be thorough:

The significance level of an event (such as a hypothesis test in later chapters) is the probability that the event could have occurred by chance. If the level is quite low, that is, the probability of occurring by chance is quite small, we say the event is significant.

A confidence level is the probability that the true value you’re trying to estimate, falls within a given range (the confidence interval). Effectively, it measures how confident you are that the value you’ve obtained from your sample (the sample statistic) is the same as the value you’re trying to estimate in the total population from which your sample was taken (the population parameter).

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1. Question

You take a random sample to estimate a population mean and your results have a confidence level of 90%. That means the process you used will give you correct results 90% of the time.

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Question 2 of 2

2. Question

The significance level of a statistical inference measures: