Due to the cessation of face-to-face teaching on QMUL campuses, some changes have been made to the current provision. Check the Venue column for information. Sessions will either proceed online at their scheduled times or will be POSTPONED with further notice. Please check your email as you will likely have received notice, or contact your tutor for more information | Introduction of new booking system

Course Detail

RS125 (5-day) - Introduction to Statistics and R (5 sessions)

Audience: All researchers (including staff and PhD students)

IMPORTANT: Different start times for each session! You are required to attend at least 4 sessions, otherwise your place will be given to someone else.

This is a 5-half-day course that runs over 2 weeks. It is designed for all PhD students and researchers with little prior knowledge of statistics who wish to better understand and apply statistical methods. Each 3-hour session will consist of 2 hours of teaching and 1 hour of interactive R tutorial. The topics covered in each session are given below:

1) Introduction
- What are statistics? And what do we use them for?
- Descriptive vs inferential statistics
- What descriptive measures are there?
- Visualising data (bars, box plot, scatter)
- Types of variables (e.g. continuous, dichotomous, ranked, discrete)
- Designing experiments
- How to use R/R Studio

2) Probability theory
- What is probability?
- Main probability axioms and calculations
- Probability distributions (continuous & discrete)
- Introduction to inferential statistics
- Hypothesis testing
- P value

3) Inferential statistics
- Assumptions
- Sample variance
- Confidence intervals
- t-test
- Multiple testing
- Effect sizes
- ANOVA

4) Non-parametric and nominal tests + ANOVA
- Fisher’s exact test
- Chi-square test
- Odds ratios
- McNemar
- Wilcoxon rank sum test
- Mann-Whitney U test

5) Linear and logistic regression
- Statistical model
- Assumptions
- Errors
- Correlation
- Confounding
- Logistic regression

Objectives

Provided by: Researcher Development

Details

Day 1

Date: Wednesday 30 October 2019

Venue: Libr TrainingRm (PCLab 101) ME, Library, 1st Floor, Mile End

Time: 13:00 - 16:00


Day 2

Date: Friday 1 November 2019

Venue: Libr TrainingRm (PCLab 101) ME, Library, 1st Floor, Mile End

Time: 09:00 - 12:00


Day 3

Date: Tuesday 5 November 2019

Venue: Libr TrainingRm (PCLab 101) ME, Library, 1st Floor, Mile End

Time: 09:00 - 12:00


Day 4

Date: Thursday 7 November 2019

Venue: Libr TrainingRm (PCLab 101) ME, Library, 1st Floor, Mile End

Time: 09:00 - 12:00


Day 5

Date: Friday 8 November 2019

Venue: Libr TrainingRm (PCLab 101) ME, Library, 1st Floor, Mile End

Time: 09:00 - 12:00


Tutors

  • Dr J Ramirez
  • Dr P Cacheiro