2021 - Introductory Statistics for Researchers
10 - 13 May
Important Notes - please read
1. Remote course
The course will be delivered remotely using online teaching tools, with a mix of live video-assisted lectures and computer-based tutorials. A continuous chat session will be available and there will be extra staff to answer questions during the practical periods.
2. Participants must have basic R skills prior to course
This is not an introductory course in using the statistical software package, R. Basic R coding will not be taught. To do this course successfully, you must have basic proficiency in using the R package. All examples and exercises used in this course are done using R. We want to ensure everyone is able to follow the course, and no participant is disappointed.
If you have basic R skills, that's excellent, please complete this quick task HERE. Once you have completed this and emailed your results you will be given a code to allow you to register for Introductory Statistics for Researchers.
If you do not have basic R skills, but want to do the Introductory Statistics for Researchers course, you can enroll in our Introduction to R course that runs twice ahead of this course, on 27-28 April and 6-7 May (register HERE). Please email email@example.com once you have done this, and you will be given a code to allow you to register for Introductory Statistics for Researchers.
In many disciplines, researchers wishing to publish are asked to provide a rigorous statistical analysis. Reviewers are often specific about what statistical measures they want included. "Why wasn't Fisher's Exact Test used?" "Was an appropriate sample size determined a priori?"
How does one decide which statistical procedure is the most appropriate? What do all the sections of the output mean?
This course is designed as an introduction to statistical analysis for researchers. There is emphasis on understanding the concepts of statistical procedures (with a minimum of mathematics, although some will be discussed) and on interpreting computer output. This course is designed to help you, the researcher. It is helpful if you have done an undergraduate statistics subject, although this course can serve as a first introduction or a refresher. The theory behind the statistical procedures outlined in the course will, in general, not be discussed.
Statistical analyses require specialised software to perform calculations. In this course, we use the free statistical program R, although researchers may have another statistical package available to them.
A range of statistical analyses will be discussed in the course, as described in the course outline below. We will talk through examples of all analysis types and will demonstrate how to carry them out in R. Equal emphasis will also be put on interpreting the output of these analyses. There will be plenty of practical work in the course. You will need basic R proficiency to carry out the practical work; we will teach only the additional R commands needed for these analyses.
Do you need to have previous experience using the program R?
It is essential to have basic proficiency in using the R statistical package. Please read "Important Notes" above.
In this course, the statistical software package used is R exclusively. We do not use or demonstrate SPSS.
Summarising and Graphing Data
Ways of presenting data (histograms, boxplots), measures of centre and spread, analysing tables, correlation, and confidence intervals.
Hypothesis testing concepts - power, significance, P-value. Comparing two groups (t and Wilcoxon tests).
Comparing many groups - with one treatment factor (one-way ANOVA or Kruskal-Wallis test; multiple comparison tests).
Correlation, predicting relationships (regression - simple).
Other topics covered
Non-Normal data - transformations and non-parametric tests. If time is available, we will briefly discuss sample size and power.
Course Requirement: You will need to use a computer during the course. You will also need administrator rights to install software needed for the course onto your computer. Basic proficiency in using the R statistical package is essential.
Date: Monday 10 to Thursday 13 May
Duration: 9.00am to 1.00pm each day
You will receive a certificate of completion for the course.
***You will receive emails from us closer to the course date regarding the course materials and remote meeting access links, so please ensure you provide a correct email address.***