This course introduces students to the methods and philosophy of modern statistical data analysis and inference, with a particular focus on applications in the life sciences.

Using tables to organise and summarise data; using graphics to present statistical information; measures of location and spread for univariate distributions. An introductory discussion of: normal and binomial distributions; sampling distributions; inference from small and large samples; confidence intervals; hypothesis testing in one- and two-sample cases; p-values; linear regression models and Analysis of Variance. Examples and applications will be drawn extensively from the life sciences, particularly Biology. The course has a strong emphasis on computing and graphical methods, and uses a variety of real-world problems to motivate the theory and methods required for carrying out statistical data analysis. The course makes extensive use of the Macintosh-based JMP statistical analysis package (previous experience with Macintosh computers is not required).

To achieve an understanding of and facility in the following:

• to summarise and graph data,
• to work with random variables and probability distributions,
• to understand and use the normal distribution;
• to carry out basic statistical inference including confidence intervals, hypothesis testing and regression and ANOVA

• assignments worth 20%.
• 5% class participation marks.
• 50 minute open-book mid-semester exam valued at 15% of the course. The mid-semester exam is compulsory. It is NOT optional or redeemable.
• A 3 hour final open-book exam valued at 60%.

Three lectures and one tutorial per week plus private study time.

 Incompatible with STAT1008 Quantitative Research Methods.

Please refer to Course Website