bus5sbf statistics for bus
STATISTICS FOR BUSINESS AND FINANCE
BUS5SBF
2016
Credit points: 15
Subject outline
This subject develops basic quantitative skills to analyse real life problems in accounting, business and finance. It focuses 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 Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Quantitive investment analysis | Prescribed | DeFusco, R, McLeavy,D., Pinto, J., Runkle,D. | 3rd . EDN. JOHN WILEY, 2015 |
| Readings | Quantitative investment analysis workbook | Preliminary | DeFusco, R, McLeavy,D., Pinto, J., Runkle,D. | 3rd EDN, JOHN WILEY, 2015 |
Graduate capabilities & intended learning outcomes
01. Apply and interpret concepts of descriptive statistics to real life data and interpretation of results.
- Activities:
- Lecturing 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 lecture 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. 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)
- 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 running linear regressions based on CAPM model and testing hypotheses
- Activities:
- Assignment 2, computational work, interpretation of statistical results and report writing related to regression and hypothesiis 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…
City Campus, 2016, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment size60
Enrolment information Room size limitations at City Campus Limiting of numbers
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
SeminarWeek: 31 - 43
One 3.0 hours seminar per week from week 31 to week 43 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
City Campus, 2016, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment size60
Enrolment information Room size Limiting of numbers
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
SeminarWeek: 10 - 22
One 3.0 hours seminar per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
City Campus, 2016, Summer, Day
Overview
Online enrolmentYes
Maximum enrolment size60
Enrolment information Room size limitations at City Campus Limiting of numbers
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
Computer LaboratoryWeek: 45
One 1.0 hours computer laboratory per week on weekdays during the day in week 45 and delivered via face-to-face.
"Students need to obtain laptops from reception at Collins Street Campus or can provide own"
LectureWeek: 45
One 2.0 hours lecture per week on weekdays during the day in week 45 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
Melbourne, 2016, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorJae Kim
Class requirements
Laboratory ClassWeek: 11 - 22
One 1.0 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
"this class is recommended but optional"
LectureWeek: 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.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
Melbourne, 2016, Semester 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
Laboratory ClassWeek: 31 - 43
One 1.0 hours laboratory class other recurrence on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
"this class is recommended, but optional"
LectureWeek: 31 - 43
One 2.0 hours lecture other recurrence on weekdays during the day from week 31 to week 43 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
Melbourne, 2016, Summer, Day
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 recommended, but optional"
Lecture
One 2.0 hours lecture per week on weekdays during the day and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
Sydney, 2016, Study Period 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
Laboratory ClassWeek: 10 - 22
One 1.0 hours laboratory class per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
LectureWeek: 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.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
Sydney, 2016, Study Period 2, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
Laboratory ClassWeek: 31 - 42
One 1.0 hours laboratory class per week on weekdays during the day from week 31 to week 42 and delivered via face-to-face.
LectureWeek: 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.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |
Sydney, 2016, Study Period 3, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorIshaq Bhatti
Class requirements
Laboratory ClassWeek: 46
One 1.0 hours laboratory class per week on weekdays during the day in week 46 and delivered via face-to-face.
LectureWeek: 46
One 2.0 hours lecture per week on weekdays during the day in week 46 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % | ILO* |
|---|---|---|---|
| Assignment 1: Computer-assisted Assignment | Equivalent to 750 words | 15 | 01, 02, 03 |
| Assignment 2: Computer Assisted Assignment using Regression models | Equivalent to 750 words | 15 | 03, 04, 05 |
| Quiz 1 | During 5 week - 500 word | 10 | 01, 02 |
| Quiz 2 | During 11 week - 500 words | 10 | 03, 04, 05 |
| Final Exam | 3000 word equivalent | 50 | 03, 04, 05 |