Statistics

Course summary

Paper 1 (Data and Probability): Numerical measures, graphs and diagrams Probability Population and samples Probability distributions (including Binomial, Normal, Exponential and Poisson) Correlation and linear regression Bayes’ theorem Experimental design Statistical Enquiry Cycle Paper 2 (Statistical Inference): Correlation and linear regression Contingency tables Experimental design Sampling, estimates and resampling Hypothesis testing (for 1 and 2 samples, including non-parametric and paired tests), significance testing, confidence intervals and power Goodness of fit Analysis of variance Effect size Statistical Enquiry Cycle Paper 3 (Statistics in Practice): All topics