Hypothesis Testing: Concepts, Application and Interpretation

Hypothesis testing is a statistical procedure that uses a set of numbers to test a researcher's claims and beliefs. It's a broad topic that includes a variety of tests. This statistical tool is studied and used extensively by college students from all disciplines, as well as all researchers, regardless of the topic of their research. This course has made an effort to explain each step of the process in detail. Because visual learning has a higher retention rate, the goal is to aid the learner in following the process smoothly with the use of tables, graphs, and other pictorial tools. To give a better understanding of the different types of tests, various examples and scenarios have been discussed.

In the first video, the significance of null and alternate hypotheses is discussed in depth. A summary table is provided as a quick reference to assist the learner in selecting the appropriate set of hypotheses. In addition, the steps of inference and conclusion are thoroughly discussed. This section covers both the traditional method and the P-value method. The following section goes over the various types of hypothesis tests that are commonly used by scientists. This section uses a variety of illustrative examples to help students understand the various types of hypothesis tests. By the end of this course, you will definitely master the topic of Hypothesis testing.

Who this course is for:

• Statistics students ( High school and university students) and majorly people involved in research ( clinical research, Biostatistics)
  

Requirements

• NA

Course ratings: 4.2/5

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