Intro to Null Hypothesis Significance Testing with z-test
About this course
This is primarily aimed at first- and second-year undergraduates interested in psychology, data analysis, and quantitative research methods along with high school students and professionals with similar interests. This course delves into the foundational concepts of probability and statistics, emphasizing the importance of random sampling and the normal distribution. Students will learn to apply statistical methods, including z-scores, effect size, and confidence intervals in the context of null hypothesis significance testing. The course also covers the implications of the central limit theorem and the relationship between statistical power and error types. Table of Contents: Probability and Distributions The Normal Distribution Sampling Distributions and the Central Limit Theorem The Logic of Null Hypothesis Significance Testing Null Hypothesis Significance Testing With the z-test Errors in Null Hypothesis Significance Testing Evaluating Statistical Significance Effect Size, Confidence Intervals, and Power
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What you'll learn
- understanding of probability and distributions
- application of the z-test in hypothesis testing
- knowledge of effect size and confidence intervals
- insight into the central limit theorem
- recognition of statistical power and error types
Course objectives
- to teach the fundamentals of probability and statistics as they relate to hypothesis testing
- to equip students with the skills to evaluate statistical significance
- to foster an understanding of sampling distributions and their importance in research
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