R for Statistical Significance Tests, Short Course | Part time online | University of Oxford | United Kingdom
Short Online

# R for Statistical Significance Tests

1 days
Duration
115 GBP/full
115 GBP/full
Unknown
Tuition fee
Unknown
Unknown
Apply date
Unknown
Start date

In the R for Statistical Significance Tests course offered by University of Oxford you will learn how to perform several widely-used hypotheses and statistical significance tests and correctly interpret the results.

## 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

• Part-time
• 1 days

English

### Delivered

Online

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

To always see correct tuition fees
• ### International

115 GBP/full
Tuition Fee
Based on the tuition of 115 GBP for the full programme during 1 days.
• ### National

115 GBP/full
Tuition Fee
Based on the tuition of 115 GBP for the full programme during 1 days.

## Our partners

R for Statistical Significance Tests
University of Oxford
R for Statistical Significance Tests
-
University of Oxford

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