Modular course 1 covered content relating to strand 1 – probability and statistics. The course was divided into 5 modules. You can get a brief overview of each module and the materials used for each module here.
If you want to find out about the availability of this course in your local education centre you’ll find the schedule here.
The first module of the probability and statistics course discusses data. It starts with an overview of the data-handling cycle and goes on to discuss the different ways in which data may be collected. The potential for bias is discussed. The different types of data which occur in statistics and the most appropriate ways to represent this data using charts is also dealt with.
The second module of the probability and statistics course deals with the treatment of numeric data. For univariate data, the ways in which the centre and spread of such data are measured is discussed along with the relative merits of each measure. For bivariate data, the concept of correlation is discussed and how correlation may lead to causation.
The third module of the probability and statistics course deals with an introduction to probability. The basic concepts of probability are introduced including the probability scale and the fundamental principle of counting. Various tools for calculating probabilities are introduced, including tree diagrams, Venn diagrams and tables. The importance of combinations and permutations for working out probabilities is also discussed.
The fourth module of the probability and statistics course deals with more advanced concepts of probability pertaining to multiple events. The concepts of events which are mutually exclusive and events which are independent are discussed. The basic rules of probability for independent and non-independent events are presented and concepts of conditional probability are discussed. The use of Venn diagrams and probability trees when solving multiple-event problems is presented.
The final module of the probability and statistics course deals with the binomial and normal distributions. The use of combinations to solve problems which may be modeled as Bernoulli trials is discussed. The application of the normal distribution for making statements about a population is looked at in depth including the use of standard normal tables and z-scores.