University of Melbourne - MAST10010: Data Analysis (Solutions)

This subject lays the foundations for an understanding of the fundamental concepts of probability and statistics required for data analysis. Students should develop expertise in some of the statistical techniques commonly used in the design and analysis of experiments, and will gain experience in the use of a major statistical computing package. They should develop skills in collecting random samples, data description, basic statistical inference including parametric and nonparametric tests to compare population proportions and means, data manipulation and statistical computing. The methods will be illustrated using applications from science, engineering and commerce. Descriptive statistics, data manipulation and the implementation of the statistical procedures covered in lectures will be reinforced in the computer laboratory classes.

Sampling; introduction to experimental design; review of simple probability; estimation; confidence intervals; hypothesis testing including types of errors and power; inferences about means and proportions based on single and independent samples; matched pairs designs; introduction to nonparametric methods; contingency tables; regression; and analysis of variance.

✔ Students completing this subject should:

• Understand the importance of random samples and experimental design in scientific research;
• Understand some fundamental concepts of statistical inference relating to confidence intervals and hypothesis testing;
• Use quantitative and graphical methods to describe a set of data;
• Develop expertise in the use of some common statistical techniques;
• Become familiar with a major statistical computing package.