The course provides the necessary background for further studies in statistics, management, or any other area requiring some proficiency in data analysis. It provides an overview of techniques and applications of data analysis, with emphasis on the analysis of experiments. It teaches the principles of good experimental design, and focuses on a project where you design and analyse your own experiment. The course uses a simple statistical package for data exploration and presentation, and the analysis of data from simple experimental and observational studies.

summarise and present data clearly in numerical and graphical forms
relate population distributions (such as the Normal and Binomial distributions), and sampling distributions to real-life problems
design a simple experiment (allowing for and controlling variability)
calculate confidence intervals and perform hypothesis tests for population means and proportions for one or two populations via z and t-tests
carry out one- and two-way analyses of variance
determine the relationships between two or more variables, via correlation and regression analysis)
draw conclusions from statistical analyses and present these conclusions in clear non-technical language

Distance

Describing Data
Population Distributions
Random variables, expectations, assessing normality
Sampling, experimental design
Sampling Distributions
Confidence intervals
Hypothesis tests
Comparing two populations
Comparing several populations: one-way ANOVA
Comparing several populations: two-way ANOVA
Correlation and regression
Inference for regression
Project work