619-100 Experimental Design and Statistical Analysis

Note:

1. Students may not gain credit for both 619-100 and 617-141.

Credit Points:

Coordinator:

Prerequisite/s:

Timetable:

Contact:

Objectives:

Students completing this subject should:

Comprehend:

• the basic concepts of experimental design, statistical inference and the underlying distribution theory;

• the concept of statistical variation, particularly leading to the notion of sampling distribution;

• the concept of a random variable; and the difference between a discrete random variable and a continuous random variable.

• the concepts of confidence interval and hypothesis test, particularly as applied to proportions and means.

Have developed the skills:

• to carry out a simple exploratory data analysis; and, in particular, to use simple numerical and graphical methods of summarising data;

• to carry out probability calculations involving the binomial and normal distributions;

• to carry out basic procedures of statistical analysis;

• to recognise and analyse a simple relationship between variables.

Appreciate:

• the elements of experimental design, and the importance of correct design for providing data capable of meaningful analysis;

• the practical applications of the Central Limit Theorem;

• the need to make assumptions and approximations;

• the application of computer software in statistical analysis -- in particular, the use of the package MINITAB.

Content:

Introduction to bivariate data, including correlation and linear regression. Scientific method and experimental design, including randomisation, blocking, factorial structure. Data description and analysis. Elementary distribution theory: binomial and normal distributions. Random sampling, simulation of random samples. Population parameters and sample statistics. Estimation, confidence intervals and hypothesis testing based on the binomial and normal distributions. Introduction to distribution-free methods. Contingency tables. Application of computer software to data analysis and simulation.

Assessment: