Block A Unit A1 Exploring data 1. Data and questions 2. Pie charts and bar charts 2.1 Pie charts 2.2 Bar charts 2.3 Problems with graphics 2.4 Introducing MINITAB 3. Histograms and scatterplots 3.1 Histograms 3.2 Scatterplots 3.3 Histograms and scatterplots using MINITAB 4. Numerical summaries 4.1 Measures of location 4.2 Measures of dispersion 4.3 Symmetry and skewness 4.4 Numerical summaries using MINITAB Unit A2 Interpreting data 1. Boxplots 1.1 Simple boxplots 1.2 Comparing data sets using boxplots 1.3 Transforming to reduce skewness 1.4 Boxplots using MINITAB 2. Producing useful tables 2.1 Basic table layout 2.2 Including the results of useful calculations 3. Interpreting data in tables Unit A3 Modelling variation 1. What is probability? 2. Modelling random variables 2.1 Discrete and continuous random variables 2.2 Probability distributions and probability functions 3. Describing probability distributions 3.1 Probability functions 3.2 The cumulative distribution function 4. Bernoulli trials 4.1 The Bernoulli probability model 4.2 The binomial probability model 4.3 Calculations using MINITAB 5. The geometric probability model 5.1 The geometric probability model 5.2 Family patterns 6. The normal distribution Unit A4 Samples and populations 1. Choosing a probability model 2. The population mean 2.1 The population mean 2.2 Families of distributions: the mean 2.3 The mean of a continuous random variable 3. The population variance 3.1 The variance of a discrete random variable 3.2 Families of distributions: the variance 3.3 The variance of a continuous random variable 4. Two models for uniformity 4.1 The discrete uniform distribution 4.2 The continuous uniform distribution 5. Is the model a good fit? Unit A5 Events occurring at random 1. The Poisson distribution 1.1 Rare events 1.2 Poisson's approximation for rare events 1.3 Applications of the Poisson approximation 2. Waiting times between events 2.1 Bernoulli processes 2.2 The exponential distribution 3. The Poisson process 3.1 A continuous-time analogue of the Bernoulli process 3.2 Is a Poisson process a good model? 4. Population quantiles 4.1 Quantiles for continuous distributions 4.2 Quantiles for discrete distributions 4.3 Finding quantiles using MINITAB 5. Probability plotting for exponential distributions |