About This Chapter
Cambridge Pre-U Math Short Course: Non-Parametric Tests - Chapter Summary
Prior to thaking the end-of-course exam for the Cambridge Pre-U Math Short Course, improve your comprehension of statistics. In particular, this chapter reviews non-parametric significance tests and helps you determine when they should be used. The lessons also help you to understand and demonstrate the use of the Wilcoxon tests when formulating a hypothesis. Once you finish studying this chapter's text and video lessons, you could be able to:
- Compare and provide examples of parametric and non-parametric statistics
- Explain the Wilcoxon Mann-Whitney statistical test
- Apply the Wilcoxon signed-rank test to form a hypothesis
- Use the Wilcoxon rank-sum test to determine the identity of populations
Review the fundamentals of non-parametric tests as they're presented by knowledgeable instructors throughout this chapter's text and video lessons. Study these concepts at your convenience on your mobile device and look over the transcripts to clarify any points you may have missed during a video presentation. You can take a short multiple-choice quiz once you've completed each lesson.
Cambridge Pre-U Math Short Course: Non-Parametric Tests Chapter Objectives
During your work on Paper 1, also called Pure Mathematics of the Cambridge Pre-U Math Short Course examination, you'll provide answers to 65 questions. The test lasts about one hour and 45 minutes and makes up 45% of the entire score.
The Statistics section, or Paper 2, of the examination is where you will be tested on the concepts in this chapter. It may assess your understanding of the use of and procedures involved in a Wilcoxon single-sample sign test, single-rank test and a rank-sum test. You should also be capable of interpreting these test results. The Statistics component consists of 80 questions, and it's worth 55% of the test. You'll have approximately two hours for completion.
1. Non-Parametric Inferential Statistics: Definition & Examples
In this lesson, you're going to learn about the major differences between parametric and non-parametric methods for dealing with inferential statistics, as well as see an example of the non-parametric method.
2. Wilcoxon Rank-Sum Test: Definition & Application
Given two random variables, we would like to know which one is more likely to exceed the other one. Without knowing the underlying distribution of either of these random variables, we can test the hypothesis that they are equally likely to exceed the other. This can be accomplished using the Wilcoxon Rank-Sum Test.
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Other chapters within the Cambridge Pre-U Mathematics - Short Course: Practice & Study Guide course
- Cambridge Pre-U Math Short Course: Quadratic Equations
- Cambridge Pre-U Math Short Course: Coordinate Geometry
- Cambridge Pre-U Math Short Course: Sequences & Series
- Cambridge Pre-U Math Short Course: Exponentials & Logarithms
- Cambridge Pre-U Math Short Course: Differentiation
- Cambridge Pre-U Math Short Course: Integration
- Cambridge Pre-U Math Short Course: Data Summarization
- Cambridge Pre-U Math Short Course: Correlation & Regression
- Cambridge Pre-U Math Short Course: Binomial Distribution
- Cambridge Pre-U Math Short Course: Normal Distribution
- Cambridge Pre-U Math Short Course: Sampling
- Cambridge Pre-U Math Short Course: Statistical Estimation
- Cambridge Pre-U Math Short Course: Hypothesis Testing
- Cambridge Pre-U Math Short Course: Chi-Square Test
- Cambridge Pre-U Mathematics - Short Course Flashcards