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Introduction to Statistics II - Lecture 9

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Lecture 9 - Hypothesis Testing - Single Mean and Single Proportion

The job of a statistician is to make statistical inferences about populations based on samples taken from the population. Confidence intervals are one way to estimate a population parameter. Another way to make a statistical inference is to make a decision about a parameter. For instance, a car dealer advertises that its new small truck gets 35 miles per gallon, on the average. A tutoring service claims that its method of tutoring helps 90% of its students get an A or a B. A company says that women managers in their company earn an average of $60,000 per year.

A statistician will make a decision about these claims. This process is called "hypothesis testing." A hypothesis test involves collecting data from a sample and evaluating the data. Then, the statistician makes a decision as to whether or not the data supports the claim that is made about the population.

This lecture covers hypothesis tests on single means and single proportions. You will also learn about the errors associated with these tests.

Dr. Barbara Illowsky, Susan Dean
Collaborative Statistics
(Connexions)
http://cnx.org
Date accessed: 2009-01-17
License: Creative Commons Attribution 2.0

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