QUANTITATIVE DATA ANALYSIS

BUS5QDA

2019

Credit points: 15

Subject outline

In this subject, you will develop your quantitative data analysis skills and learn techniques which are commonly used by researchers to answer important questions and by senior managers in making informed business decisions. Topics in the first component of this subject include; descriptive statistics, probability distributions, parametric estimation methods, parametric and non-parametric hypothesis tests, and both simple and multiple regression analysis. In addition to the linear regression modeling, the subject will cover panel data analysis.This knowledge will then be extended with advanced techniques including limited dependent variable models such as logit, probit models, ordered probit and tobit. Authentic assessments in this subject will promote critical thinking, problem solving and inquiry whilst strengthening your analytical, report writing and communication skills.


SchoolLa Trobe Business School

Credit points15

Subject Co-ordinatorMohammad Al Mamun

Available to Study Abroad StudentsNo

Subject year levelYear Level 5 - Masters

Exchange StudentsNo

Subject particulars

Subject rules

Prerequisites Students must be enrolled in LHCOM (Bachelor of Commerce (Honours)) or LDPH (PhD) to do this subject. BUS1BAN or approval by subject coordinator

Co-requisitesN/A

Incompatible subjectsN/A

Equivalent subjectsN/A

Special conditionsN/A

Graduate capabilities & intended learning outcomes

01. Demonstrate the ability to create sound and empirically testable research questions in applied economics, finance and business research.

Activities:
Students will be taught in the underlying principles of a defining a #good# research question (what?, why?, how?) and also the process of developing and carrying out an empirical project using quantitative data.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

02. Provide a full and accurate explanation of relevant univariate and multivariate techniques to analyse different types of data and the underlying model assumptions that underpin these techniques.

Activities:
Learning activities will be based upon face-to-face lectures, labs sessions, online videos, readings, group discussions, and assessment tasks.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

03. Demonstrate the ability to apply various data analysis techniques using relevant statistical software.

Activities:
There will be an hour long weekly interactive lab session and an hour long weekly tutorial for 12 and 11 weeks respectively, where students will use real world data to estimate, interpret and analyse various statistical tools using relevant software.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

04. Demonstrate the ability to examine empirically research hypotheses whilst interpreting, reporting and presenting data analysis results in a scholarly way.

Activities:
The learning will be developed through weekly lecture and workshop activities that will be assessed through authentic assessments. In particular, students will replicate or extend a published research work and disseminate their findings in the final lecture in week 12 as part of their project.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

05. Demonstrate a well-developed judgement in selecting the optimal quantitative test and procedure for solving a given research issue from various quantitative methods that are frequently used in applied economics, finance and business research.

Activities:
Learning activities include lectures, online videos, and different research articles.
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Literacies and Communication Skills (Writing,Speaking,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

Subject options

Select to view your study options…

Start date between: and    Key dates

Melbourne, 2019, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorMohammad Al Mamun

Class requirements

Seminar Week: 10 - 22
One 2.0 hours seminar per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Laboratory Class Week: 10 - 21
One 1.0 hours laboratory class per week on weekdays during the day from week 10 to week 21 and delivered via face-to-face.

Tutorial Week: 11 - 21
One 1.0 hours tutorial per week on weekdays during the day from week 11 to week 21 and delivered via face-to-face.

Assessments

Assessment elementComments% ILO*
Two data analysis exercises (approximately 1200 words each)worth 15% each30 01, 02, 03, 04, 05
Data analysis project, 2000 words25% report, and 5% presentation during Week 1230 01, 02, 03, 04, 05
Final Examination (2 hours) (equivalent 3000 words)40 01, 02, 04, 05