标签：series scheme mpi doc bre table mes adl desc
BST811 BUSINESS DATA ANALYTICS
Academic Year 2019-2020 (Autumn Semester)
COURSEWORK
Essay Title (Choose a title that reflects your assignment)
This assessment takes the form of a structured essay and accounts for 100% of your total mark.
The deadline for submission is week 10, Wednesday 4
th December 2019. This coursework is
of two parts, a theoretical part and an empirical part.
Your coursework should be structured as follows:
Part One: 50%
1. Discuss the difference between structured and unstructured data using examples and
provide a clear description of the most suitable tools and applications to manage and
analyse different types of data sets. (500 words)
2. Critically discuss ‘‘big data” its application and uses in operations or logistics or
shipping or sustainability or supply-chain management. Please note that you are only
required to focus on one area. (1500 words).
Part Two: 50%
A. You need to use R to complete the requirements of this part of the coursework and you
are required to submit two R files (R-Markdown document and R-Markdown file).
B. You need to download the data file titled: “Coursework Data File”, also you need to
watch week 4 lecture video titled “Business Analytics Coursework The Answers Using Excel”.
This video explains the data sample you are going to use for your coursework.
C. You are required to complete the following tasks (1000 words):
1. Observe the variables “Loading Date”, “Year of Built”, “vessel type” and “cargo size”
in the dataset. (5%)
i. Check the data type (format) of the following variables: “year of built”, “vessel
type” and “cargo size”. If necessary, modify the data type.
ii. Check if these variables contain missing values. Exclude all observations where at
least one of these variables “Loading Date”, “year of built” and “vessel type” and
“cargo size” contain missing values and save it.1
2. Create a weekly time series of vessels fixture (a count of number of weekly fixed ships)
and total cargo capacity2
. (5%)
3. Plot a weekly time series showing total number of vessels fixtures and total cargo
capacity loaded onboard ships. You need to provide a table with the data used to plot
the time series3
. (5%)
4. Identify the week that had the highest number of vessel fixtures and the most loaded
cargo in tonnes4
. (5%)
5. Structure a table and provide a suitable illustration that categorises total fixtures and
cargo capacity by vessel type and year of built. (5%)
6. Forecasts are required to support decisions in the future. We need to provide the forecast
to support operational planning one week in advance. Use naïve and simple moving
average to provide one-week ahead forecast. (5%)
7. Which approach do you recommend using for this forecasting task? Critically discuss
your answer and plot your forecasts. (5%)
8. Historical time series may contain useful information that are useful for decision
makers. Do you see any pattern in the weekly time series of vessels fixtures and total
cargo capacity? Use visualisations and critically discuss to justify your answer. (5%)
The following marking criteria will be applied for each point.
i. 0% → No Attempt
ii. 2% → Poor Attempt
iii. 3% → Good Answer
iv. 4% → V. G. Answer
v. 5% → Excellent Answer
The essay should be NO MORE THAN 3,000 WORDS IN LENGTH and all sources should
be acknowledged in the appropriate place in the text. You are advised to use the Cardiff
Harvard referencing system.
What Files You Need to Submit?
1. A document file (PDF/Word) that answers the two questions in Part One. (Essential)
2. A R-markdown document that shows your work for Part Two. (5%)
3. A R-markdown file that can be used to reproduce your work for Part Two. (5%)
Submission is on week 10, Wednesday 4
th December 2019.
Essays must be submitted online on Learning Central BEFORE 11:00 p.m.
Note: You are also advised to attach a cover sheet containing: the module code, module title,
lecturer’s name, scheme of study, student’s name and student number.
1 Tip 1: this will reduce the sample size significantly.
2 Tip 2: You need to create a cargo capacity variable using the cargo size column in the data sample.
BST811留学生作业代写、代做DATA ANALYTICS作业
3 Tip 3: the horizontal axis represents time in weeks starting from week .. to week .. of 2019.
4 Tip 4: your answer should be in the form: week no. XX had a total of XX fixtures and the total cargo loaded
onboard vessels was X,XXX,XXX tonnes.
References
Ensure all sources of information are referenced correctly using the Cardiff Harvard Style of
Referencing – if unsure see the handout from the library.
Unfair Practice
This is an individual assignment and you are advised not to engage in any activity that might
lead to suspicions of Unfair Practice. Details of the University Regulations may be found at
https://intranet.cardiff.ac.uk/students/your-study/exams-and-assessment/sittingyourexam/cheating-and-unfair-practice
and you should familiarise yourself with these
regulations before starting your coursework.
On the front page of the assignment, you should include:
§ Name
§ Student number
§ Title of coursework
§ Title of Module and module number
§ Name of lecturer
§ Date of submission
§ Word count
Students are advised to keep a second copy for themselves. Should there be special
circumstances that mean you are unable to meet the submission deadline, you must obtain an
extension from the Chair of the Board of Examiners. Forms are available from room A-04 or
Learning Central. If you are not in Cardiff then contact your Personal Tutor.
Good luck
Dr. Wessam Abouarghoub
Coursework marking-criteria
For 90%+
An outstanding piece of work, showing mastery of the subject matter, with a highly developed ability to analyse,
synthesise and apply knowledge and concepts. All objectives of the assignment are covered and the work is free
of error with very high level of technical competence. There is evidence of critical reflection; and the work
demonstrates originality of thought, and the ability to tackle questions and issues not previously
encountered. Ideas are expressed with fluency. All coursework requirements are met and exceeded.
For 70% - 89%
An excellent piece of work, showing a high degree of mastery of the subject matter, with a well-developed ability
to analyse, synthesise and apply knowledge and concepts. All major objectives of the set work are covered, and
work is free of all but very minor errors, with a high level of technical competence. There is evidence of critical
reflection, and of ability to tackle questions and issues not previously encountered. Ideas are expressed clearly.
However the originality required for a 90+ mark is absent. All coursework requirements are met and some are
exceeded.
For 60%-69%
A very good piece of work, showing a sound and thorough grasp of the subject-matter, though lacking the breadth
and depth required for a first class mark. A good attempt at analysis, synthesis and application of knowledge and
concepts, but more limited in scope than that required for a mark of 70+. Most objectives of the work set are
covered. Work is generally technically competent, but there may be a few gaps leading to some errors. Some
evidence of critical reflection, and the ability to make a reasonable attempt at tackling questions and issues not
previously encountered. Ideas are generally expressed with clarity, with some minor exceptions. All coursework
requirements are addressed adequately.
For 50%-59%
A fair piece of work, showing grasp of major elements of the subject-matter but possibly with some gaps or areas
of confusion. Only the basic requirements of the work are covered. The attempt at analysis, synthesis and
application of knowledge and concepts is superficial, with a heavy reliance on course materials. Work may
contain some errors, and technical competence is at a routine level only. Ability to tackle questions and issues not
previously encountered is limited. Little critical reflection. Some confusion and immaturity in expression of
ideas. Most coursework requirements are addressed.
For 40%-49%
A poor piece of work, showing some familiarity with the subject matter, but with major gaps and serious
misconceptions. Only some of the basic requirements of the work set are achieved. Little or no attempt at analysis,
synthesis or application of knowledge, and a low level of technical competence, with many errors. Difficulty in
beginning to address questions and issues not previously encountered. Some intended learning outcomes are
achieved.
For 30%-39%
Work not of passable standard, with serious gaps in knowledge of the subject matter, and many areas of confusion.
Few or none of the basic requirements of the work set are achieved, and there is an inability to apply knowledge.
Technical competence is poor, with many serious errors. The student finds it difficult to begin to address questions
and issues not previously encountered. The level of expression and structure is very inadequate. Few intended
learning outcomes are achieved.
Below 30%
A very poor piece of work, showing that the student has failed to engage seriously with any of the subject matter
involved, and/or demonstrates total confusion over the requirements of the work set. Virtually none of the
intended learning outcomes are achieved.
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标签：series scheme mpi doc bre table mes adl desc
原文地址：https://www.cnblogs.com/simplebluejava/p/11978658.html
