Intro to Null Hypothesis Significance Testing with z-test
By External Provider
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
What you will learn
- Calculate and interpret t-tests, effect sizes, and confidence intervals from raw data and summary statistics.
- Compare and contrast z- and t-distributions, and determine the appropriate test for various research situations.
- Develop and generate hypotheses for differences between means and conduct the corresponding tests.