Hypothesis Testing

Partner: Udemy
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Description: This course provides a comprehensive introduction to the fundamental concept of hypothesis testing in statistics. Hypothesis testing is a critical tool for making informed decisions and drawing meaningful conclusions from data. Through a combination of theoretical concepts and practical applications, students will learn how to formulate hypotheses, perform hypothesis tests, interpret results, and make valid inferences about populations based on sample data.Course Objectives:By the end of this course, students should be able to:Understand the purpose and importance of hypothesis testing in various fields.Differentiate between null and alternative hypotheses and select appropriate test criteria.Apply various hypothesis testing methods for means, proportions, and variances.Interpret p-values, confidence intervals, and effect sizes to make informed conclusions.Determine sample sizes for hypothesis tests and assess the power of tests.Identify and mitigate common errors and misconceptions in hypothesis testing.Course Outline:Introduction to Hypothesis TestingRole of hypothesis testing in data analysisFormulating null and alternative hypothesesSignificance level and p-valuesProbability and Distributions ReviewProbability distributions and their propertiesSampling distributions and central limit theoremHypothesis Testing ProcessSteps in hypothesis testingOne-tailed vs. two-tailed testsOne-Sample Hypothesis TestsZ-tests and t-tests for means and proportionsInterpreting results and drawing conclusionsTwo-Sample Hypothesis TestsIndependent sample tests and paired sample testsComparing means and proportions
Category: IT & Software > IT Certifications > Data Science
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Price: 29.99
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Source: Impact
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