Discussion – Testing Hypotheses
- Hypothesis testing is a set of core analysis tools used to answer questions about the characteristics of a population. The process involves several steps, varying from five to ten depending upon the author of the text being used. What are these steps and why is it so important to follow and explicitly state each step in the process? In your responses discuss the properties of hypotheses, the importance and meaning of the level of significance and the various kinds of tests we might choose from and why.
- One and Two sample hypothesis tests are either comparing a sample to a standard value or comparing to samples to each other. Thanks to the Central Limit Theorem and the empirical rule we can usually trust the results. But there are exceptions. These are called Type I and Type II errors. So:
- What are Type I and Type II errors?
- Is there anything we can do to measure the likelihood of these errors and thereby reduce the chance of these errors occurring?
- In addition to the one and two sample tests of hypothesis we have Analysis of Variance (ANOVA). ANOVA is one of the most widely used tests in statistics.There are many varieties, but the biggest varieties are the one factor and two factor ANOVA tests.What are these tests and what are the differences between one factor and two factor ANOVA?Can you think of any examples where these tests might be used in your workplace?
