Statistical Methods for Research Workers

In many disciplines, researchers wishing to publish are asked to provide a rigorous statistical analysis. Reviewers are often specific about what statistical measures they want included. Why wasn't an ANOVA done? What is the power of the test?

Statistical analyses require specialised software to perform calculations. In this course we use the statistical program R, although researchers may have a statistical package available to them.

How does one decide which is the appropriate procedure? What do all the pages of the printout mean?

This course, is designed as an overview of statistical design and analysis for researchers. There is emphasis on understanding the concepts of statistical procedures (with a minimum of mathematics, although some will be discussed) and on interpreting computer output. This course is designed to help you, the researcher. It assumes you did an undergraduate statistics subject which you may need a refresher.

Instructions on how to obtain computer printouts will be provided, with an emphasis on interpreting the computer printout (most packages produce similar printouts).  There will be computing lab sessions throughout the course.

Course Outline

Introduction

Types of experiments, scales of measurement, which method to use.

Summarising and Graphing Data

Ways of presenting data (histograms, boxplots), measures of centre and spread, analysing tables, correlation, and confidence intervals.

Comparing Groups

Hypothesis testing concepts-power, significance, P-value. Comparing two groups (t-tests, Wilcoxon). Comparing many groups - ANOVA or Kruskal-Wallis - multiple comparison tests, required sample size and repeated measures.

Finding Relationships

Correlation, predicting relationships (regression - simple). Logisitc regression

Enrolment: The course is being  revised to include an optional 3rd day. The next time the course will be offered will be in the University Semester 2 break, 30th Sepetember to 4th October 2013 (TBC). The enrolment form will be made available here once the dates have been confirmed.

Duration: 2 - 3 days, 9.30am to 5.00pm

Cost: TBA

A Certificate of Attendance will be presented to participants upon completion.

Contact: Francy Fan or Julie Hebblewhite.
School of Mathematics and Statistics, UNSW
E-mail: f.fan@unsw.edu.au or j.hebblewhite@unsw.edu.au

Phone: 02 9385 7011 or 02 9385 7053 Fax: 02 9385 7123