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This MSD Skills training course consists of four half-day sessions, and is suitable for all MSD postgraduate research students and postdoctoral early career researchers using and interpreting statistical data.

Which course is for me?

MSD Skills runs several courses in statistics that have similar titles to this course. Here is a short description of this course vs other available courses to help you decide if you should sign up:

Fundamentals of Statistical Software and Analysis FoSSA): Runs ONLINE, at your own pace. Gives a brief overview of statistical theory and how to carry out a wide variety of statistical tests in R, Stata, or SPSS. 

Introduction to Statistics (this course): Runs IN PERSON over 4 days. Gives an in-depth understanding of fundamental statistical theory. Does not use any software. Students may want to take this course prior to signing up for FoSSA.

Intro to R for Biologists: Runs ONLINE over 2 days. Gives a more in-depth understanding to use the software R and make basic plots. Covers some basic statistical tests. You could take this course before or after taking FoSSA; FoSSA will show you how to run a wider variety of statistical tests in R.

Data Analysis & Visualisation in R: Runs ONLINE over 3 days. This is a more advanced course covering programming, data wrangling and visualisation in R. It does not cover statistical tests but shows how statistical information can be visualised in plots.

COURSE AIM

This course provides a basic introduction to statistics, covering the key concepts that form the basis of computer statistical software. It assumes no prior knowledge of statistics. With the help of real data from published medical studies, and by generating your own data from pre- and in-class experiments, you will explore the core concept of the sampling distribution, which in turn leads to hypothesis testing and confidence intervals, ideas which form the basis of many statistical tests.

Obtaining a deep understanding of these “basic” concepts not only satisfies scientific curiosity and de-mystifies statistics, but more importantly is crucial to aid decision-making with regard to which techniques and tests to perform, and also in how to interpret statistical results in scientific literature and in your own research. No statistical software will be used, but a scientific calculator is required.

You are required to attend 4 sessions on:

  • Monday 31 March, 09:30 - 13:00
  • Tuesday 1 April, 09:30 - 13:00
  • Wednesday 9 April, 09:30 - 13:00
  • Tuesday 15 April, 09:30 - 13:00

COURSE DESCRIPTION

The course will cover: data distributions; averages; sampling distribution; standard deviation and standard error; sampling variation; statistical inference; the null hypothesis and hypothesis testing; statistical significance and confidence intervals; relative risk and odds ratios; chi-squared tests; anova tests, and power calculations, of particular importance for researchers writing grant applications.

Other topics not covered in the workshops are covered as supplementary material in the workbooks, including correlations, confounding, and an introduction to linear regression.

 

COURSE OBJECTIVES 

This course will enable you to:

  • To get a grounding in the theory and core concepts of statistics
  • How to perform some key of the statistical tests on both continuous and binary data
  • When you might need to use non-parametric tests, and how to do them
  • How to interpret the statistical results that you have produced
  • How to do sample size calculations on both continuous and binary data

ATENDANCE SURVEY ON COMPLETION

It is now a requirement that you complete the three short questions in the survey you receive after attending the course. Once you have submitted the survey, you will be sent an email with a link to your attendance certificate. This is to ensure we receive the feedback we need to evaluate and improve our courses. Survey results are downloaded and stored anonymously. 

feedback from previous sessions

 

It was the perfect balance between theory and practice
Very good teacher - clear, concise and happy to answer any questions. The workbook and course were well-structured. Overall, I learnt a lot from this course and got to practice what I learnt so I would recommend this course to others.
Basic and important concepts of statistics were widely covered & easy to understand
After COVID19 it was nice to have the face-to-face teaching and the social aspect of being in a room with classmates. Not an intimidating environment so was easy to ask questions.