Abstract: Critical to any experimentation is the formulation of a research hypothesis that accurately states what the experimental design is going to test. Statistical tests are actually designed to test whether or not the opposite of this research hypothesis, called the null hypothesis, is to be supported or not supported. The level of support for the null hypothesis is defined by what is called a p value or alpha level. This p value is directly related to two different types of statistical error called a Type I or Type II error. This chapter discusses these points in detail along with the concept of statistical power. There is also a brief discussion of experimental bias.
Publication Year: 2016
Publication Date: 2016-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
Access and Citation
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot