Training: Statistics and Visualisation with R

COURSE SCHEDULE

Session            Date

1                       Mon 1st

2                       Tues 2nd

3                       Mon 8th

4                       Tues 9th

5                       Mon 15th

6                       *Thurs 18th

7                       Mon 22nd

8                       Tues 23rd

9                       Mon 29th

10                     Tues 30th

 

Time: 13:00 - 14:30 on each of the above dates.

Sessions 10 is planned for a recap of course materials and a chance to bring your own dataset for discussion. In order to receive a certificate of participation, please take part in all sessions.

Sessions will be held remotely, with participants joining a remote Blackboard Collaborate session.

-

Description:

This course will give you an introductory overview to basic techniques for visualising your data with R, as well as statistical techniques for analysing your dataset.

Participants will learn how to enter and modify data in R, how to create visualisations (charts, scatter plots, and histograms, etc.), and how to conduct the main statistical tests and corrections required in order to analyse your data.

No previous knowledge of programming or statistics is needed.

Topics covered: Installing R; Using built-in datasets; Importing data; Creating bar/ pie charts for categorical variables; Creating histograms/ box plots for quantitative variables; Calculating frequencies & descriptives; Transforming variables; Coding missing data; Analysing by subgroup; Charts for associations; Calculating correlations; Charts & statistics for 3 or more variables; Crosstabs for categorical variables.

Send an email to cdcs@ed.ac.uk if you have questions about this course.

You might be interested in

Interactive Analysis Reports with R Markdown

Interactive Analysis Reports with R Markdown

text analysis

Digital Method of the Month: Text Analysis

Beyond Social Networks with Gephi

Beyond Social Networks: Advanced Uses of Gephi in Humanities Research

Sentiment Analysis

Silent Disco: Introduction to Sentiment Analysis

Regression and Mixed Effect Modelling mashup

Regression and Mixed Effects Modelling

Introduction to Topic Modelling with Bert

Introduction to Topic Modelling with Bert

Digital Method of the Month. Machine learning

Digital Method of the Month: Machine Learning

A Gentle Introduction to Causal Inference

A Gentle Introduction to Causal Inference

Introduction to Bayesian Statistics

Introduction to Bayesian Statistics