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Chapter 22: Sample Size - Coggle Diagram
Chapter 22: Sample Size
A Review of Hypothesis Testing Errors
The concept of hypothesis testing errors is key to selecting sample sizes for various hypothesis testing.
Type I error occurs when you reject the null hypothesis during a hypothesis test when, in fact, the null
hypothesis is true. Y
Type II error occurs when you accept the null hypothesis when it is, in fact, not true.
What Information is Required for Choosing Sample Size?
Sample Size Calculations: Choosing the Right Method
Just as there were numerous hypothesis tests to cover a range of data types and questions, there are
numerous sample size calculations – all of which can be performed in Minitab.
Running and Analyzing Sample Size Tests in Minitab
Sample Calculations for a 1-Sample T Test
Sample Calculations for a 1-Sample Proportion Test
Proportion tests are a bit different for two major reasons:
Proportion tests are run using attribute data. Attribute data almost always requires a larger sample size for accurate results than continuous data does.
Because you are dealing with attributes – and rates – you don’t need to provide any information about population parameters such as sigma levels or standard deviation.
Sample Size Calculations for a 2-Sample T Test
