Overview
What you will study
The R for Statistical Significance Tests course offered by University of Oxford assumes prior knowledge of how to use R and RStudio. It contains explanation and implementation of several tests such as:
- t-test to determine if there is a significant difference between the means of two groups, which may be related in certain features, or to answer the question: is the mean of a vector different from a given value? This includes variations of the t-test.
- Kolmogorov-Smirnov test to statistically test the distribution of a variable.
- A/B test to establish which of two treatments, products, procedures, or the like is superior.
- Permutation test to compare an observed statistic to a resampled distribution and determine whether an observed difference between samples might occur by chance.
- ANOVA to test whether groupings in the data can be meaningful ways to understand the structure of the data.
- Chi-Squared test to test differences across a contingency table.
- This training covers various theoretical and practical aspects of several hypothesis and statistical significance tests. You will learn what a test does, when to use it, how to use it and how to interpret its results.
By the end of the day you will have access to all course material (e.g. slides, code examples and so on).
Programme Structure
The program focuses on:
- What are hypothesis and statistical significance tests? Why do we need them?
- What is a p-value? How do we interpret it?
- The two types of error (type I and type II errors)
- Paired sample vs independent sample
- Data types and distributions
- Kolmogorov-Smirnov test
- Shapiro-Wilk test
- T-test, A/B and permutation tests
- Why have a control group?
- Resampling and resampling techniques
- Permutation test
- More on the p-value and how to interpret it
- ANOVA, Chi-squared and Fisher’s Exact Tests
- Kruskal-Wallis and Mann-Whitney tests and how to select a test
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
- StartingApplication deadline not specified.
Language
Delivered
Disciplines
Statistics View 21 other Short Courses in Statistics in United KingdomWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- The day assumes prior knowledge of how to use R and RStudio.
Tuition Fee
-
International
115 GBP/fullTuition FeeBased on the tuition of 115 GBP for the full programme during 1 days. -
National
115 GBP/fullTuition FeeBased on the tuition of 115 GBP for the full programme during 1 days.