Course Title: Prepare financial forecasts and projections
Part B: Course Detail
Teaching Period: Term2 2009
Course Code: BAFI5150C
Course Title: Prepare financial forecasts and projections
School: 650T TAFE Business
Campus: City Campus
Program: C5178 - Diploma of Accounting
Course Contact : Gowri Raviganesh
Course Contact Phone: +61 3 9925 1337
Course Contact Email:gowri.raviganesh@rmit.edu.au
Name and Contact Details of All Other Relevant Staff
Gowri Raviganesh
PH: 9925 1377
gowri.raviganesh@rmit.edu.au
Max Kaltmann
Phone: 61 3 9925 1544
email: max.kaltmann@rmit.edu.au
Nominal Hours: 70
Regardless of the mode of delivery, represent a guide to the relative teaching time and student effort required to successfully achieve a particular competency/module. This may include not only scheduled classes or workplace visits but also the amount of effort required to undertake, evaluate and complete all assessment requirements, including any non-classroom activities.
Pre-requisites and Co-requisites
None.
Course Description
This unit describes the functions involved in preparing financial forecasts and projections. It will also provide students with the skills and knowledge in the application of statistical analyses and processing of business data.
If you are undertaking this course in Melbourne from semester 2, 2012 onwards your teacher will advise you if you require access to a computer for the course. It is recommended that you have access to a mobile computing device to allow greater flexibility in terms of where you can work on campus outside class times.
National Codes, Titles, Elements and Performance Criteria
National Element Code & Title: |
FNSICORG517B Prepare financial forecasts and projections |
Element: |
FNSICORG517B/01 Plan Preparation Table |
Performance Criteria: |
•All critical milestones are identified to ensure financial forecasts and |
Element: |
FNSICORG517B/02 Identify assumption and Parameters |
Performance Criteria: |
•Business plans and exception reports are reviewed to identify and resolve conflicts in assumptions. |
Element: |
FNSICORG517B/03 Issue Instructions and relevant aids for preparation of forecast and projection |
Performance Criteria: |
•Instructions issued are clear and unambiguous and comply with company format at to ensure ease of use and consistency of interpretation. |
Element: |
FNSICORG517B/04 Collect, consolidate, model and analyse data |
Performance Criteria: |
•Data is reviewed to ensure consistency with actual results and mode l used. |
Element: |
FNSICORG517B/05 Document Result and obtain approval |
Performance Criteria: |
•Results are documented in a clear and understandable manner. |
Learning Outcomes
Please refer to Elements of Competency.
Details of Learning Activities
An initial introduction to topics and techniques via a lecture will include the fundamentals and methods of business statistics.
Students will participate in tutorial-based discussion groups that will enable them to relate topics to the environment, in which they live and work.
They will be required to present their own thoughts, opinions and ideas. A range of learning team activities will assist them to develop and apply their knowledge in different situations that reflect tasks, which they might encounter in a business environment.
A range of self directed learning activities would be provided for students to practice, reinforce and summarise the key learning.
Students will be responsible for managing the progress of their self-directed learning. Students will work on self-directed learning activities (multiple choice & Internet based case study) independently of the lecturer.
Teaching Schedule
Week | Topic, assessment |
1 | Course Introduction Introduction to Statistics, Sampling and Data collection |
2 | Organisation and Visual representation of data |
3 | Measures of Central tendencies |
4 | Measures of Dispersion |
5 | Probability and Normal Distribution |
6 | Sampling Distribution & Estimation |
7 | Revision for test |
8 | Class Test; Assignment Distribution |
9 | Hypothesis Testing & Excel in lab |
10 | Hypothesis Testing |
11 | Correlation and Regression & Excel in lab |
12 | Correlation and Regression & Excel in lab |
13 | Time Series & Excel in lab |
14 | Index numbers |
15 | Revision; Due date for Assignment |
16 | Revision |
17 | Examination |
18 | Feedback on assessment |
Learning Resources
Prescribed Texts
Greg Dickman, Financial Forecasting and Data Analysis. Thomson. ISBN:0-17-012155-0 |
References
Levine et al, Statistics for Managers, 4th Edition. |
Other Resources
Learning support materials are made available on the Online Learning Hub www.rmit.edu.au/online.
Access to an Internet connected computer outside of class times – Internet connected computers are available in the Business Portfolio labs on Level 3 of Building 108, 239 Bourke Street Melbourne.
Students are required to have a non-programmable calculator that can perform basic mathematical functions. Formula sheets are provided for class tests. Please note that calculators that have the capacity to store text are not permitted in tests.
Floppy disks OR other suitable storage media are required for the submission of assignment softcopies.
Overview of Assessment
Assessment may incorporate a variety of methods including technical requirements documentation, homework, assignments, group and/or individual projects, in class exercises, written and practical tests, problem solving exercises, presentations, direct observation of actual and simulated work practice, presentation of a portfolio of evidence which may comprise documents, and/or photographs and/or video and audio files, review of products produced through work-based or course activities.
Students are advised that they are likely to be asked to personally demonstrate their assessment work to their teacher to ensure that the relevant competency standards are being met. Students will be provided with feedback throughout the course to check their progress.
Assessment Tasks
1 Test (held in week 8)
In-class test worth 20 % will be held in week 8. Test will be closed book and one & ½ hour in duration. Formula sheet will be provided and only non-programmable calculators are allowed.
2 Group Assignment (due week 15)
Students need to source information from specified web sites. Analyse data using EXCEL “Data Analysis” tool pack and write reports. This is worth 20% and due in week 15.
3 Exam (During Exam period)
A closed book exam worth 60% covering all topics will be held during exam period.
To be deemed competent in this course, students must pass all performance elements, assessed in the assignment and final test.
Additionally, students will be graded in this course. The grade will be determined on the overall mark attained for all assessment tasks and based on the grade criteria listed below.
Grade Criteria
High distinctionHD 80-100
DistinctionDI 70-79
CreditCR 60-69
PassPA 50-59
FailNN <50
DNS Did not submit
NYC Not yet competent
Assessment Matrix
Test | Group Assignment | Examination | |
Plan Preparation Table | Y | Y | Y |
Identify assumption and Parameters | Y | Y | Y |
Issue Instructions and relevant aids for preparation of forecast and projection | Y | Y | |
Collect, consolidate, model and analyse data | Y | Y | Y |
Document Result and obtain approval | Y | Y |
Other Information
Course Content
1.1Identify types of statistics that are common to business
1.2Differences between Sample and Population
1.3Introduction to sampling
1.4Distinguish primary and secondary data
1.5Explain why data is presented visually
1.6Organising raw data into Frequency and grouped frequency distribution
1.7Represent data tables graphically
* Histograms
* Polygons
* Ogives
* Bar chart
* Pie chart
1.8Calculate the measure of central tendencies (only for raw data)
* Mean
* Mode
* Media
1.9Identify the appropriate measure for a given situation
1.10 Discuss the significance of skewness of a data
Calculate the measure of dispersion (only for raw data)
* Range
* Inter-Quartile range
* Standard deviation
1.11Writing a brief Business report
1.12Use of software (excel) for analysing data
2.1 Distinguish between a population and a sample
2.2 Describe the special features of a normal distribution
2.3 Understand and apply central limit theorem
2.4 Calculate point estimates and confidence interval for the population mean
2.5 Solve business problems that can be represented by a normal distribution
2.5 Understand the principles of statistical inference
2.6 Identifying research questions and Formulate hypothesis
2.8 Decision-making based on test statistics
Use of EXCEL
3.1 Discussing examples where there is association between two variables
3.2 Understand dependent and independent variable
3.3 Draw and interpret a scatter diagram
3.4 Assess relationship with the help of correlation coefficient
3.5 Interpret of correlation coefficient
3.6 Understand linear regression
3.7 Establish linear relation between two variables using the method of Least squares Regression
3.8 Prediction based on linear regression equation
3.9Check the goodness of fit using coefficient of determination
Use of EXCEL
4.1 Identify and interpret the four basic measures of variation in a time series analysis
4.2 Describe a time series and explain its use by giving example
4.3 Use common methods of fitting secular trend lines to time series (including semi averages, moving averages and least-squares)
4.4 Forecast using trend
Use of EXCEL
5.1 Use of simple, composite & weighted Price indices to measure the change in retail prices.
5.2 Special applications of the CPI
Course Overview: Access Course Overview