One 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 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.
- 9.1: Introduction
- A statistician will make a decision about claims via a process 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 there is sufficient evidence, based upon analysis of the data, to reject the null hypothesis.
- 9.2: Hypothesis Testing
- The actual test begins by considering two hypotheses. They are called the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints. Since the null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough evidence to reject the null hypothesis or not.
- 9.3: A Single Population Mean using the Normal Distribution
- The hypothesis test itself has an established process. This section focuses on tests of a mean when the population standard deviation is given or can be determined.
- 9.4: A Single Population Mean using the Student t-Distribution
- The hypothesis test itself has an established process. This section focuses on tests of a mean when the population standard deviation is is not given or cannot be determined.
- 9.5: A Population Proportion
- The hypothesis test itself has an established process. This section focuses on tests of a proportion.
- 9.E: Hypothesis Testing with One Sample (Exercises)
- These are homework exercises to accompany the Textmap created for "Introductory Statistics" by OpenStax.
Contributors and Attributions
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