# Introduction to Modelling

Provider business unit: Statistical Consulting Unit »

The Statistical Consulting Unit runs a number of courses throughout the academic year. The objective of the courses is to promote sound statistical thinking and an awareness of appropriate modern statistical practice, leading to informative analyses. This is of particular value to students who utilise statistical concepts and methods in research theses as well as those seeking to enhance their wider statistical understanding. The courses are:

• are designed for research students and ANU staff who have no or minimal training and knowledge of statistical analysis
• use a case-study, problem oriented approach to teaching
• do not require sophisticated mathematical skills
• provide an introduction to modern statistical practice
• provide an introduction to the underlying modern statistical thinking and concepts used in many analyses.

## Overview

This course, delivered online through Wattle, focuses on models using two or more variables. The aim of the course is to introduce participants to the most common modelling techniques and to raise awareness of some problems that can arise when using them. The emphasis is on concepts and the use of formulae has been minimised. There are practice exercises to support the concepts; there are also examples of analyses of data sets with an emphasis on interpretation of output from statistical packages.

## Course content

• Evaluate association between two numerical variables using plots and correlation coefficients;
• Describe and quantify the relationship between two variables using simple linear regression;
• Recognise when a relationship is nonlinear and apply an appropriate transformation;
• Describe, detect and present relationships between two categorical variables;
• Assess the independence of two categorical variables;
• Use multiple linear regression to model the effect of several variables on a numerical response variable;
• Use logistic regression to model the effect of several variables on a categorical response variable;
• Avoid reaching the wrong conclusions from not including enough variables in the analysis.

## Learning outcomes

On completion of this course participants will be able to:

• Organise their data into a form suitable for analysis using a statistics package;
• Specify a standard multiple linear regression model or logistic regression model in a statistics package;
• Interpret the output from a statistics package used for fitting linear or logistic regression models;
• Examine diagnostics and other indicators to determine whether the fitted model is appropriate;
• Judge when they need to seek specialised help from a statistical consultant and conduct a meaningful discussion about the analysis of their data.

## Assumed knowledge

Knowledge of the material taught in Introductory Statistics Online is assumed.

## Registration

This course is free to ANU Staff & Students (honours & research only).

Registrations are open year-round. Please register and follow the prompts for enrolment.

Each course provides a practical introduction to various statistical methods. There will be plenty of opportunity for discussion with course leaders on appropriate methods of analysing data, and help will be provided with interpreting results.

Understanding the basic concepts and issues makes the consultation process more efficient and effective. We recommend that all students who intend involving the SCU in their project attend some relevant courses.