units

STA2216

Faculty of Science

# Undergraduate - UnitSTA2216 - Data analysis for science

This unit entry is for students who completed this unit in 2014 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

## 6 points, SCA Band 2, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

 Level Undergraduate Faculty Faculty of Science Offered Gippsland First semester 2014 (Day)Gippsland First semester 2014 (Off-campus)Malaysia Second semester 2014 (Day) Coordinator(s) Dr Andrew Percy and Dr Philip Rayment (Gippsland); Dr Chen Won Sun (Malaysia)

### Synopsis

This unit is designed to develop an understanding of some of the most widely used methods of statistical data analysis, from the view point of the user, with an emphasis on planned experiments. Students will become familiar with at least one standard statistical package. Topics covered include: parametric and nonparametric procedures to compare two independent and matched samples; review of simple linear regression; multiple linear regression - analysis of residuals, choice of explanatory variables; model selection and validation; nonlinear relationships; introduction to logistic regression; basic principles of experimental design; one-way and two-way analysis of variance models; planned and multiple comparison techniques; power and sample size considerations in design; usage of some available statistical packages including Minitab and/or SPSS, data preparation, interpretation of output.

### Outcomes

On completion of this unit students will be able to:

1. Recognise the requirements for design of an effective experiment and the nature of data arising from these situations;

1. Demonstrate an understanding of some of the important parametric and non-parametric methods of statistical data analysis, including analysis of variance, multiple linear regression and logistic regression;

1. Identify and apply an appropriate statistical technique for analysing a given design/ data set;

1. Formulate a model relating a response variable to a number of given independent variables;

1. Use a statistical package for applying statistical techniques covered in the unit.

### Assessment

Assignments (three): 30%
Mini-project report: 10%
Examination (3 hours): 60%

### Chief examiner(s)

Semester One - Associate Professor David Paganin; Semester Two - Dr Chen Won Sun