# Econometrics

Bond University

## Course Description

Econometrics

• ### Host University

Bond University

• ### Location

Gold Coast, Australia

• ### Area of Study

Economics, Statistics

• ### Language Level

Taught In English

• ### Prerequisites

Students must have successfully completed STAT11-100 Business Maths OR STAT11-111 Business Statistics OR STAT11-112 Quantitative Methods or equivalent prior to undertaking ECON12-200

• ### Course Level Recommendations

Upper

ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

### Hours & Credits

• Credits

10
• Recommended U.S. Semester Credits
3 - 4
• Recommended U.S. Quarter Units
4.5 - 6
• ### Overview

Introduction
Econometrics is a sub-discipline of both statistics and economics and presents one interface between statistical theory and the real world. It provides the tools with which to test hypotheses and to generate forecasts of business activity. Topics include the classical regression model, remedial measures for violation of regression assumptions, binary choice models, panel data models and their applications. The technique such as hypothesis testing and its application will allow students to specialise in areas such as market research and other disciplines. The skills that students will develop in this subject are crucial in any applied work and will constitute an essential ingredient in most jobs in the field of business application, whether in the public or private sector.

Learning Objectives
1. Understand the Classical Linear Regression Model, its maintained assumptions and relevant properties. This model is by far the most frequently used by researcher in many disciplines such as Accounting, Economics, Finance, Marketing and Management and among others to analyse the behaviour of the variables of interest in their relevant disciplines.

2. Apply the Classical Regression Models to decision making problems for the purpose of hypothesis testing and prediction.

3. Learn how to determine, vis-a-vis diagnostic statistics, when the maintained assumptions of the Classical Linear Regression Model are violated and how to address the violations so that correct statistical inference can be drawn.

4. Use econometrics package EVIEWS most frequently used by practitioners to analyse the data.

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