Statistical Inference and Hypothesis Testing in Data Science Applications
Completed by Michael Curley
July 6, 2024
36 hours (approximately)
Michael Curley's account is verified. Coursera certifies their successful completion of Statistical Inference and Hypothesis Testing in Data Science Applications
What you will learn
Define a composite hypothesis and the level of significance for a test with a composite null hypothesis.
Define a test statistic, level of significance, and the rejection region for a hypothesis test. Give the form of a rejection region.
Perform tests concerning a true population variance.
Compute the sampling distributions for the sample mean and sample minimum of the exponential distribution.
Skills you will gain
- Category: Sampling (Statistics)
- Category: Statistical Hypothesis Testing
- Category: Statistics
- Category: Statistical Methods
- Category: Sample Size Determination
- Category: Data Ethics
- Category: Probability & Statistics
- Category: Probability Distribution
- Category: Statistical Inference
- Category: Statistical Analysis

