Please Note:

Course Detail

RD-QMA-021 - Introduction to Statistics and R (6 DAYS COURSE)

AUDIENCE:
All researchers (including staff and PhD students)

PREPARATION:
Before attending this course, it would be advisable that students get familiar with the R environment. Here is a list of some free online resources, from short tutorials to more comprehensive materials: https://education.rstudio.com/learn/beginner/
https://r4ds.had.co.nz/introduction.html
http://www.r-tutor.com/r-introduction
http://www.r-tutor.com/elementary-statistics
https://moderndive.netlify.app/1-getting-started.html
https://quantixed.org/2020/02/18/get-better-r-for-absolute-beginners/
http://www.biostat.jhsph.edu/~ajaffe/docs/undergradguidetoR.pdf
https://www.statmethods.net/r-tutorial/index.html

Other resources not necessarily free, but with a free trial period/option in some cases:
https://www.coursera.org/learn/r-programming
https://www.edx.org/course/data-science-r-basics
https://www.datacamp.com/courses/free-introduction-to-r


JOINING INSTRUCTIONS:
This workshop will be hosted online.
You will receive joining instructions via email 2 weeks in advance of the session and again 2 days in advance.

FORMAT:
This course takes place over multiple days and you are required to attend all sessions.

DESCRIPTION:
0. Introduction to R
1. Introduction to the course
2. Probability theory
3. Inferential statistics
4. Non-parametric and nominal tests
5. Linear regression and correlation
6. Recap

0. Introduction to R
In this session we will cover some basic R concepts for those students with no previous experience with R

1. Introduction
1.1. Interactive lecture session covering the following topics:
- Introduction to the course
- 'Doing science': hypotheses, experiments and disproof
- Collecting and displaying data
- Introductory concepts of experimental design
1.2. Real data exercises in R
- Basic commands
- Objects
- Functions
- Vectors
- Data types
- Summarising and displaying data
- Describing the variation
- Calculating the range
- Histograms
- Boxplots

2. Probability theory
2.1. Interactive lecture session covering the following topics:
- What is probability?
- Main probability axioms and calculations
- Probability distributions
- Introduction to inferential statistics
- Hypothesis testing and P-values
2.2. Real data exercises in R
- Binomial distribution
- Normal distribution
- Comparing proportions
- Comparing continuous variables
- Additional exercises

3. Inferential statistics
3.1. Interactive lecture session covering the following topics:
- Previous session recap
- Statistical power, P-value, effect size
- Mean, standard deviation, standard error, confidence intervals
- Types of statistical tests. Assumptions
- T-test
- ANOVA
3.2. Real data exercises in R
- Normality
- Power
- One sample t-test
- Two sample t-test
- One-way ANOVA
- Additional exercises

4. Non-parametric and nominal tests
4.1. Interactive lecture session covering the following topics:
- Recap: T-test, ANOVA and regression
- Non-parametric tests for nominal data
- Non-parametric tests for ratio, interval or ordinal scale data
4.2. Real data exercises in R
- Introduction
- Generating new data
- Chi-square/goodness of fit test
- Fisher's exact test
- Paired data
- Mann-Whitney U-test
- One sample and paired sample Wilcoxon test

5. Linear regression and correlation
5.1. Interactive lecture session covering the following topics:
- Relationship between variables: correlation and regression
- Correlation
- Regression
5.2. Real data exercises in R
- Introduction
- Recap of basic commands
- Correlation
- Understanding linear regression
- Controlling linear regression
- Multiple linear regression

6. Recap
In this practical session we will allow some time for questions and problems brought by the students and general Q&As about the content of the course.

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DEPARTMENT POLICIES
Late arrival:
If you anticipate arriving late, please advise us as soon as possible. Please note that the instructor reserves the right to not admit any latecomers.

Assistance:
If you require any type of assistance, whether it is with mobility, visual and/or hearing, please let us know at resdev@qmul.ac.uk so we can do our best to accommodate you.

Objectives

Provided by: Researcher Development

Details

Day 1

Date: Monday 9 November 2020

Venue: Webinar, Online, Internet

Time: 09:00 - 12:30


Day 2

Date: Tuesday 10 November 2020

Venue: Webinar, Online, Internet

Time: 10:00 - 13:30


Day 3

Date: Wednesday 11 November 2020

Venue: Webinar, Online, Internet

Time: 09:00 - 12:30


Day 4

Date: Thursday 12 November 2020

Venue: Webinar, Online, Internet

Time: 09:00 - 12:30


Day 5

Date: Friday 13 November 2020

Venue: Webinar, Online, Internet

Time: 09:00 - 12:30


Day 6

Date: Monday 16 November 2020

Venue: Webinar, Online, Internet

Time: 09:00 - 12:30


Tutors

  • Dr J Ramirez
  • Dr P Cacheiro