This course on Hypothesis Testing Statistics aims to teach learners the fundamentals of hypothesis testing, including designing hypotheses, conducting tests, and validating results. The course covers the connection between hypothesis testing and probability, type 1 and type 2 errors, and various hypothesis tests such as t-test, z-test, chi-square test, and ANOVA. By the end of the course, students will be able to understand basic concepts of six sigma, different types of hypothesis tests, confidence levels, and intervals, as well as how to apply hypothesis testing in real-world scenarios. The course is suitable for individuals interested in statistics, research, data analysis, and decision-making processes.
Hypothesis Testing Statistics - Examples and T-Test Hypothesis Testing
Overview
Syllabus
- Introduction to Hypothesis Testing.
- What is a hypothesis test and its types.
- Type I and type II errors.
- Types of hypothesis testing.
- Confidence level and confidence interval.
- One-tailed and two-tailed hypothesis.
- Hypothesis testing examples.
- Chi square distribution.
- ANOVA.
- one-way ANOVA test and two-way ANOVA test.
- f statistic test.
- Z statistic test.
- Summary.
Taught by
Great Learning
