Statistical & Hypothesis Tests: Using the One-sample T-test
Statistics | Intermediate
- 11 videos | 1h 37m 52s
- Includes Assessment
- Earns a Badge
One-sample T-tests are probably the single most commonly used type of hypothesis test. Through this course, learn to manually implement the one-sample T-test to know exactly how the p-value and test statistic are calculated. You'll examine various library implementations of the one-sample T-test and apply the test on data drawn from several different distributions. This course will also help you explore the non-parametric Wilcoxon signed-rank test, which is conceptually very similar to the one-sample T-test and helps estimate the median rather than the mean of that population without making assumptions about the population distribution. Upon completion of this course, you will be able to use the one-sample T-test as well as its non-parametric equivalent to evaluate both one-sided and two-sided hypotheses about the population mean or median.
WHAT YOU WILL LEARN
discover the key concepts covered in this courseinstall various modules in pythoncreate a function to manually perform a T-testcompare a manual one-sample T-test to a built-in testexplore Laplace and Wald distributions with T-teststest data to see if it is normally distributed using Shapiro-Wilk and Anderson-Darling tests
perform T-tests on real-world dataexplore one-sided and two-sided T-testsperform the Wilcoxon signed-rank test to compare medianstest medians using the Wilcoxon signed-rank testsummarize the key concepts covered in this course
IN THIS COURSE
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.Digital badges are yours to keep, forever.
YOU MIGHT ALSO LIKE
Course Basic Analytical Methods