Statistics for Financial Decisions

STAT6003 Module 5 Assessment 1
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Subject Code and Title STAT 6003: Statistics for Financial Decisions
Assessment Module 5 – Assessment 1: Short written assessments
Individual/Group Individual
Length NA
Learning Outcomes 1. Analyse and present data graphically using
spreadsheet software (Excel).
2. Critically evaluate summary statistics against suitable
3. Apply judgement to select appropriate methods of
data analysis drawing on knowledge of regression
analysis, probability, probability distributions and
sampling distributions.
4. Select and apply a range of data analysis tools to
inform problem solving and decision making.
5. Conduct quantitative research both individually and as
part of a team and articulate and present findings to a
wide range of stakeholders, from accounting and non
accounting backgrounds.
Submission By 11:55pm AEST/AEDT Sunday at the end of each
Weighting 30% (Total of all written assessments throughout the
Total Marks 100 marks

The short written module assessments allows you to apply your knowledge on the concepts
and ideas discussed during the Module. These assessments will also prepare you for the
final report.
You are required to apply your knowledge and draw links between the scenario and the
learning resources. In your answers, reflect upon and analyse issues of the key discussion
points of the module. Your answers should also effectively communicate and demonstrate
that key concepts have been reviewed and that you can apply these concepts to the
problems posted.

STAT6003 Module 5 Assessment 1
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The Board of Directors of Schmeckt Gut would like to forecast sales figures for the
Federated Islands for this year (2016) based on a data set that has collected information
over the past 25 years.
The dataset which is provided in the EXCEL file is for the Federated Islands and includes
other variables.
Assume that the development of the sales of Energy Bars (in US$) in a country is highly
dependent on:
• The development of the income of that country approximated by GDP data in
• The development of prices approximated by an average price index (in %)
• The population development (15-65 years of age)
• Satisfaction of customers with the product which is approximated with a survey
score – this is the average result of a customer satisfaction survey (0=not
satisfies, 10=very satisfied)
• The advertisement of energy bars – number of average advertisements, and
• The Number of stores where the energy bars can be purchased.
If we would rewrite this relationship with a regression: