Introduction to Statistical Analysis

Course Data

Please download and unzip this zip file that contains all the data files required for the course CourseData.zip

Software Requirements

You will need an internet connection in order to run the practicals and examples

• One sample test app
• Two sample test app
• Contingency table app

N.B If the above links are not working, please try the following instead

• One sample test app
• Two sample test app
• Contingency table app

Timetable and Materials

• 11:00 - 11:45 Introductory Lecture
• 11:45 - 12:00 Online quiz
• 12:00 - 12:30 Lecture on Parametric Tests (1- and 2- sample t-tests for continuous variables)
• 12:30 - 13:30 Lunch (not provided)
• 13:30 - 14:00 Practical Session 1
• 14:00 - 14:30 Lecture on Non-Parametric tests (1- and 2-sample tests)
• 14:30 - 15:00 Practical Session 2
• 15:00 - 15:15 Lecture on test for categorical variables
• 15:15 - 15:30 Practical Session 3
• 15:30 - 16:15 Group based exercise; choosing appropriate tests. Please record your observations about the data on this interactive document
• 16:15 - Wrap-up and summary

Overview

This course provides a refresher on the foundations of statistical analysis. The course is aimed at scientists at all levels – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since. The focus of the course is on understanding the principles behind statistical testing, how to choose an appropriate test for your data and how to interpret the result.

Note that this is not a course for learning the R statistical language itself. If you wish to learn more about R, please see other courses at the Sheffield Bioinformatics Core.

Who should attend this course?

The course is aimed primarily at scientists at all levels – especially those whose formal education likely included statistics, but who have not perhaps put this into practice since.

Objectives:- After this course you should be able to:

• State the assumptions required for a one-sample and two-sample t-test and be able to interpret the results of such a test
• Know when to apply a paired or independent two-sample t-test
• To perform simple statistical calculations using the online app
• Understand the limitations of the tests taught within the course
• Know when more complex statistical methods are required

Aims:- During this course you will learn about:

• Different types of data, distributions and structure within data
• Summary statistics for continuous and discrete data
• Formulating a null hypothesis
• Assumptions of one-sample and two-sample t-tests
• Interpreting the result of a statistical test
• Statistical tests of categorical variables (Chi-squared and Fisher’s exact tests)
• Non-parametric versions of one- and two-sample tests (Wilcoxon tests)

Prerequisites

• None

Instructors

• Mark Dunning, Bioinformatics Core Director

• Alison Parton, Animal and Plant Sciences

• Sheffield - 24th October 2018
• 11:00am - 5pm
• Pam Liversidge Design Studio 2 - E06