STATISTICS FOR BUSINESS AND FINANCE

BUS5SBF

2017

Credit points: 15

Subject outline

In this subject you will develop basic quantitative skills to analyse real life problems in accounting, business and finance. You will focus on volatility measure of portfolio risk return distributions, basic concepts of probability and statistics, methods of statistical inference, measure of linear relationship between various business and finance variables including regression analysis. There is a strong emphasis on the application of these techniques to real world problems in business and finance using MS-Excel. This subject lays a solid foundation to the further study of quantitative analysis in business and finance. The contents of the subject are in line with 'Chartered Financial Analyst - CFA' quantitative analysis curriculum and hence follows CFA textbook.

SchoolLa Trobe Business School

Credit points15

Subject Co-ordinatorIshaq Bhatti

Available to Study Abroad StudentsYes

Subject year levelYear Level 5 - Masters

Exchange StudentsYes

Subject particulars

Subject rules

PrerequisitesN/A

Co-requisitesN/A

Incompatible subjects FIN5SBF

Equivalent subjects FIN5SBF

Special conditionsN/A

Learning resources

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsQuantitive investment analysisPrescribedDeFusco, R, McLeavy,D., Pinto, J., Runkle,D. (2015)3rd. EDN. JOHN WILEY
ReadingsQuantitative investment analysis workbookPreliminaryDeFusco, R, McLeavy,D., Pinto, J., Runkle,D. (2015)3rd EDN, JOHN WILEY

Graduate capabilities & intended learning outcomes

01. Apply and interpret concepts of descriptive statistics to real life data and interpretation of results

Activities:
Activities on cash flow topics with linkage to Statistical methodology
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)

02. Apply probability theory in business and financial decision making

Activities:
Based on subject material, weekly computer labs are conducted to impliment statistical computations using SPSS software or Excel
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,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. Use sampling methods to estimate and infer accounting, economics and financial models using data

Activities:
Assignment 1, computational work, research question and solution to enable critical thinking and report writing
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

04. Develop competency in estimating linear regression models and testing hypothesis

Activities:
Assignment 2, computational work, interpretation of statistical results and report writing related to regression and hypothesis testing
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

05. Develop ability to present work in a professional manner

Activities:
Presentation and interpretation of statistical results and report writing related to Multiple regression models related to return and CAPM Models
Related graduate capabilities and elements:
Literacies and Communication Skills (Writing,Quantitative Literacy)
Literacies and Communication Skills (Writing,Quantitative Literacy)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

Subject options

Select to view your study options…

Start date between: and    Key dates

City Campus, 2017, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 10 - 22
One 1.0 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Seminar Week: 11 - 22
One 2.0 hours seminar per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

City Campus, 2017, Semester 2, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 32 - 43
One 1.0 hours computer laboratory per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Seminar Week: 31 - 43
One 2.0 hours seminar per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

City Campus, 2017, Summer, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 46
One 1.0 hours computer laboratory per week on weekdays during the day in week 46 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture Week: 46
One 2.0 hours lecture per week on weekdays during the day in week 46 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

Melbourne, 2017, Semester 1, Day

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 11 - 22
One 1.0 hours computer laboratory per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

Melbourne, 2017, Summer, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 46
One 1.0 hours computer laboratory per week on weekdays during the day in week 46 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture Week: 46
One 2.0 hours lecture per week on weekdays during the day in week 46 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

Melbourne, 2017, Semester 2, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 32 - 43
One 1.0 hours computer laboratory per week on weekdays during the day from week 32 to week 43 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture Week: 31 - 43
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

Online, 2017, Online StudyPeriod 2, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Unscheduled Online Class Week: 10 - 16
One 6.0 hours unscheduled online class per week on any day including weekend from week 10 to week 16 and delivered via online.
"This subject is delivered entirely online. Students are required to undertake online learning and assessment activities."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words030 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words030 03, 04, 05
Quiz 1equivalent to 375-words. Week 3. Quiz is 50% of the blended version.010 01, 02
Quiz 2equivalent to 375-words. Week 5. Quiz is 50% of the blended version.010 03, 04, 05
Quiz 3equivalent to 750-words. Week 7020 03, 04, 05

Online, 2017, Online StudyPeriod 4, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Unscheduled Online Class Week: 28 - 34
One 6.0 hours unscheduled online class per week on any day including weekend from week 28 to week 34 and delivered via online.
"This subject is delivered entirely online. Students are required to undertake online learning and assessment activities."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words030 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words030 03, 04, 05
Quiz 1equivalent to 375-words. Week 3. Quiz is 50% of the blended version.010 01, 02
Quiz 2equivalent to 375-words. Week 5. Quiz is 50% of the blended version.010 03, 04, 05
Quiz 3equivalent to 750-words. Week 7.020 03, 04, 05

Online, 2017, Online StudyPeriod 6, Online

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Unscheduled Online Class Week: 44 - 50
One 6.0 hours unscheduled online class per week on any day including weekend from week 44 to week 50 and delivered via online.
"This subject is delivered entirely online. Students are required to undertake online learning and assessment activities."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignment & Presentationequivalent to 1500 words. Week 3.030 01, 02, 03
Assignment 2: Computer-assisted assignment using regression models & Presentationequivalent to 1500 words. Week 6030 03, 04, 05
Quiz 1equivalent to 375-words. Week 3. Quiz is 50% of the blended version.010 01, 02
Quiz 2equivalent to 375-words. Week 5. Quiz is 50% of the blended version.010 03, 04, 05
Quiz 3equivalent to 750-words. Week 7020 03, 04, 05

Sydney, 2017, Study Period 3, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory
One 1.0 hours computer laboratory per week on weekdays during the day and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture
One 2.0 hours lecture per week on weekdays during the day and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

Sydney, 2017, Study Period 2, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 31 - 42
One 1.0 hours computer laboratory per week on weekdays during the day from week 31 to week 42 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture Week: 31 - 42
One 2.0 hours lecture per week on weekdays during the day from week 31 to week 42 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05

Sydney, 2017, Study Period 1, Blended

Overview

Online enrolmentYes

Maximum enrolment sizeN/A

Enrolment information

Subject Instance Co-ordinatorIshaq Bhatti

Class requirements

Computer Laboratory Week: 10 - 22
One 1.0 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"This class is strongly recommended, but optional"

Lecture Week: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"In addition, students are expected to undertake between 1 h and 3 h of online learning and assessment activities each week prior to class."

Assessments

Assessment elementComments% ILO*
Assignment 1: Computer-assisted assignmentequivalent to 1500 words30 01, 02, 03
Assignment 2: Computer-assisted assignment using regression modelsequivalent to 1500 words30 03, 04, 05
Quiz 1equivalent to 750-words. Week 5.20 01, 02
Quiz 2equivalent to 750-words. Week 11.20 03, 04, 05