Introductory Course on Statistics: Data Visualization and Analysis (Using R software)

This course is targeted to individuals who are not familiar with basic statistical concepts or individuals who have attended some basic course in Statistics but would like a refresher course and perhaps even learn more than was covered in their previous education and/or training.

The aim is to provide a painless introduction to statistical analysis to users with a non-mathematical background. The software that will be used in this course is R. R is a very widely used software in the statistical community due to it being very powerful and available for free download. Apart from standard tasks, the open source platform also allows one to freely download, install and use additional packages.

Session 1
✓ The Importance of Statistics and Data Analysis in Today’s World.
✓ Getting Acquainted with R and the RStudio Interface.
✓ Importing, Creating and Sorting data in R.

Session 2
✓ An Introduction to Different Types of Variables.
✓ Descriptive Statistics - Mean, trimmed mean, median, standard deviation, variance, skewness and
kurtosis.
✓ Data Exploration and Visualisation - looking at the most common statistical and visual techniques for
preliminary data analysis. These include: Pie Charts, Bar Graphs, Histograms, Box-plots and Scatter plots.

Sessions 3-5
Basics of Sampling
✓ Introducing notions such as population, sample, sample space and sample estimates
✓ Introducing important probability distributions
✓ Investigating the relationship between population and sample
✓ Calculating the margin of error
✓ Sample size calculation.
Tests for comparison of means:
✓ one-sample, independent and paired samples t-test
✓ one-sample and paired Wilcoxon tests, Mann Whitney test
✓ ANOVA and repeated measures ANOVA
✓ Kruskal-Wallis and Friedman test
✓ Post-hoc tests.

Session 6
✓ Tests for comparison of proportions.
✓ Tests for the association: Chi-squared test.
✓ Tests for correlation: Pearson, Spearman and Kendall tests.
✓ Introduction to modelling.

Session 7
✓ Hands-on supervised experience with real data - visualisation and analysis.