BUSS1020 – Quantitative Business Analysis 定量 代写
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BUSS1020 – Quantitative Business Analysis 定量 代写
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BUSS1020 – Quantitative Business Analysis
Group ASSIGNMENT
Semester 1, 2017
This assignment is worth 20% of your total mark.
It must be submitted online on the Blackboard course website at the link
provided. You must submit the assignment using the TURNITIN link by 3:00
pm on Friday, 9 June, 2017. Late assignments will be penalized at 10% (of
the possible marks) for submission after due time on due date, plus 10%
per day late, including weekends.
The assignment must be done in your allocated groups. Serious penalties
may be applied if a student and/or group is found to have engaged in
plagiarism, including possibly receiving a mark of zero (0). Further, if a
student has not contributed at all to their group’s assignment, they will
receive a mark of zero (0).
The assignment will be marked out of 60. Marks allocated for each question
are shown below, adding up to 55 marks. Professional and clear presentation
is a required and assessed component in this assignment: 5 marks out of
60 are allocated specifically for that component.
A 15 page maximum limit applies to this assignment. As a guide,
assignments should be at least 10 pages, in order to cover the tasks
adequately.
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You have recently taken on work in the business analytics group for the US Energy
Information Administration. The administration wants to use data analytic methods to better
understand the variation and movements over time in residential prices for natural gas. They
have supplied you with a dataset that consists of monthly residential natural gas prices,
averaged over the entire US, in units of dollars per thousand cubic feet, from 2008-2012. Also
included in the dataset is the average natural gas “Wellhead price”. The wellhead price
represents the price of the gas immediately upon extraction, i.e. at the mouth of the well,
which excludes the transportation and delivery costs; i.e. the cost of getting the gas to the
consumers for their energy use is excluded.
Currently, the Administration has some fairly adhoc understandings about residential
prices, which are used to form estimates and forecasts and help form various policies and
reports for government as well as those in the natural gas industry. However, using their
recently acquired data, and having hired you to help analyse it, they are hopeful to improve
their estimation processes and understanding.
The data are in the file “Natural Gas_asst.xlsx”, available on the BUSS1020 Blackboard
site. The data consists of 60 months of two measurements on natural gas prices.
Variables include the date, the average residential natural gas price and the
average wellhead price for natural gas, across the US.
You are required to present and explain all your assumptions and discuss whether they
could be true, or not, in answering each of the questions below. Make sure to note that
the data are recorded consecutively over time.
Task 1 (10 marks) Data Summary and Visualization
BUSS1020 – Quantitative Business Analysis 定量 代写
The point of this task is for you to perform and present a summary of an initial exploratory
data analysis (EDA); one that is relevant to the goals of the assignment. Please read Tasks
2-4 now, and as you do decide what are the most appropriate things to include in an
exploratory data analysis. Then, explore and present an appropriate EDA for this data set,
focusing on the graphs and summary measures that are most relevant to the
objectives in Tasks 2-4. Discuss these graphs and statistics in both a general and
a business context, as well as how they relate or inform the issues in Tasks 2-4.
Task 2 (10 marks)
The Administration has always estimated or predicted average residential natural
gas prices differently, based on the time of the year. Specifically, the
Administration usually estimates that residential natural gas prices will be higher, by
4 dollars per thousand cubic feet, for the months of June, July, August and September,
compared to the remainder of the year.
Fully investigate whether residential natural gas prices are higher during the months of
June - September, compared to the remainder of the year, giving a plain-English business
context conclusion to your investigation. Then, fully assess the Administration’s adhoc
method of predicting residential natural gas prices described above.
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Task 3 (15 marks)
An analytics department colleague suggests that a regression model be considered to
estimate natural gas prices, employing the wellhead price as an explanatory
variable. In the past, the Administration has estimated average residential
prices as 10 + 75% of the wellhead price (in dollars per thousand cubic feet).
Using a regression analysis, fully examine the relationship between the wellhead prices
and the residential prices; then properly assess whether the Administration’s adhoc
estimation method is accurate, or not.
Task 4 (15 marks)
The head of business intelligence and analytics suggests that more explanatory variables
may be included in a regression model to estimate residential natural gas prices.
You suggest adding dummy variables for each grouping of months that has a “different”
level of residential natural gas price. Using multiple regression analysis, fully examine
the following questions:
What is the best of grouping of months that employs the minimum number
of groups (and thus dummy variables) and achieves an acceptably
accurate fit to the data? Compare (at least) the fit of the competing
models that respectively employ 2 and 3 groups of months. Fully analyze,
diagnose and discuss the best model you find .
Compare the best model with the two adhoc approaches to estimating
residential natural gas in Tasks 2 and 3.
Task 5 (5 marks)
Write an executive summary (no more than 500 words) for the management of t h e
US Energy Information Administration regarding your analyses, their assumptions, your
recommendations and your conclusions regarding methods to estimate average US
residential natural gas prices. Include a recommendation on which model or method
they should best use, and why. Use plain English language as much as possible.
END OF ASSIGNMENT
BUSS1020 – Quantitative Business Analysis 定量 代写
