SyllabusThe subject will cover the following topics: Descriptive statistics: Graphs and statistics as summaries, frequency tables, concept of population and sample, random variation, measurement levels (categorical, ordinal, interval, ratio), measures of location and dispersion, mean and median, standard deviation, range and coefficient of variation;
Basic probability: Probability estimate from relative frequency and percentiles;
Random Variables: Representing the outcome of experiments in terms of random variables, distinguishing between discrete and continuous random variables and calculating probabilities;
Sampling Distributions: The application of various sampling strategies and the distribution of sample means and proportions;
Inference based on a single sample: Using a sample to gain information about a population, controlled experimentation, randomisation and causality, distribution of sample means and proportions, confidence intervals, hypothesis tests;
Inference based on two independent samples: Using a sample to gain information about a population, controlled experimentation, randomisation and causality, distribution of sample means and proportions, confidence intervals, hypothesis tests;
Analysis of Variance: Oneway ANOVA for testing differences in two or more means, graphical displays, checks on assumptions and post hoc tests;
Chisquare tests: Fitting distributions to data, checking distributions graphically and by chisquare, testing 2way tables of counts;
Regression: Intercept and slope, error sum of squares, correlation, relation to slope, F and t tests of slope, R squared;
Experimental Design: Difference between experimental and observational data, issues of cost, sample size, efficiency, layout of simple orthogonal designs  single factor, randomised blocks, latin square, balanced incomplete block, factorial designs. 
