ECON10006 Statistical Methods
Assessment’s contribution to unit: 40%
Release Date:01/03/2024
Submission Date:20/03/2024 at 11:00 am
Feedback Released:15/04/2024
Students are strongly advised to submit their work ahead of the deadline. Should you have a problem with submission to Blackboard you should email [email protected] for guidance immediately.
• Your answer should not exceed 500 words.
• Assignments handed in after the deadline, without a pre-arranged extension, will be subject to late penalties. Details relating to penalties are at the end of this document.
• A reference list/bibliography is recommended. This list does not contribute to the word count. Information on referencing can be found via our library.
• Please use Arial or Calibri font at 12-point.
• Your assignment should be combined into a single document and submitted in pdf format with a document name containing your student number.
• You may include photographs or scans of your own hand-drawn, labelled diagrams or calculations. We would advise you to generate your own diagrams but if you include diagrams or pictures that you have not produced yourself, or are modified versions of existing images, you should ensure you reference them appropriately.
Figures and tables should normally be included inline in the text.
• Your answer will be assessed using the University Marking Criteria. This is a piece of COURSEWORK that contributes to your Unit mark and you can:
• Use resources to support you in completing your answer.
• Draw upon a range of accepted resources including, your own notes, lecture slides/recordings, course material, textbooks, journal articles, online resources. ALL work should be written in your own words.
• Ask for help from your personal tutors or academic lecturers if you do not understand an aspect of the coursework.
• Broad discussion with your tutors, fellow students, friends and family on the assessment topic and your ideas/approach may help you to further your knowledge and understanding.
• Use your network of family and friends to gain support and encouragement during the assessment period. Please remember this is a formal assessment and you should behave in a manner consistent with our values. This means
you cannot:
• Allow others to directly contribute to your written answer by revising or adding to the academic content. This is collusion and is against University Regulations.
• Share your assessment with others or ask others to share their work with you.
• Copy and paste any material (text, images, coding, calculations) from other sources, including teaching material and shared revision notes directly into your answer without appropriate acknowledgement. This is plagiarism and is against University Regulations. There is advice about referencing from the University Library.
• Pay another person or company to complete the assessment for you. This is contract cheating and is against University Regulations.
Coursework brief
You are tasked to design, and test, a hypothesis, using the tools you have developed in this unit. You should write (up to) 500 words, explaining the test, and discussing the results of the test. The test may relate to a single variable, or multiple
variables.
Your write up should include the following five sections:
1. Designing the hypothesis (25%)
Explain what hypothesis you are testing, and what the (theoretical) basis for the test is. You may build your hypothesis based upon the economic theory you learn in ECON10001. Marks will be awarded for:
a) Usage of correct notation
b) The quality of the motivation for the hypothesis being tested
c) The relationship being investigated.
2. Data (10%)
Describe the data that you are using to test your hypothesis. You may use any publicly available data source. This may include data collected for previous units (e.g. EFIM10016), but you may also collect data from sources such as:
• The OECD
• FRED
• The World Bank
You may also use data that we have seen in lectures.
Your description of the data should include an explanation of what variable(s) you are considering, what the source of the data is, and why you have chosen that data, along with a summary of the data chosen. Marks will be awarded for the quality of the discussion of the data.
3. Formal test of the hypothesis (30%)
You will need to choose an appropriate estimator to estimate the population characteristic of interest. Using your estimates, formally construct a test of the hypothesis, and provide an interpretation of your results.
Marks will be awarded for:
a) Correct usage of estimators
b) Correct formulae used
c) Correct tests
d) Correct interpretation of results.
You should include all your working.
4. Evaluate your results (20%)
You need to discuss whether the results you have obtained are likely to be valid. Are there any threats, or limitations to the results you have constructed? For example, are there any sources of bias? Can the results be applied to other situations? Marks will be awarded for appropriate critical evaluation of your results
5. Conclusions (15%)
What are the wider implications of the results?Penalties for late work
Assignments handed in after the deadline, without a pre-arranged extension will be subject to the following penalty:
• A fixed absolute penalty of 10 marks is applied for each 24-hour period work is submitted after the agreed deadline. Please note, weekend days count towards the calculation of late penalties. Public holidays in England, and University closure days do not.
• A mark of zero is automatically applied to work submitted late such that at least four such 24-hour periods have elapsed.
Academic Integrity
In academic writing, plagiarism is the inclusion of any idea or any language from someone else without giving due credit by citing and referencing that source in your work. This applies if the source is print or electronic, published or unpublished, another student’s work, or any other person.
The University's Examination Regulations state that “Any thesis, dissertation, essay, or other course work must be the student’s own work and must not contain plagiarised material. Any instance of plagiarism in such coursework will be
treated as an offence under these regulations.” (Section 3.1).
The Examination Regulations give information on the University's procedures for dealing with cases of plagiarism in undergraduate programmes (Section 4)
More information about plagiarism, and how to avoid it is available from the Library website.
Use of AI tools (such as ChatGPT).
• You may make use of AI tools to research this assignment, but this must be clearly referenced at the end of your assignment.
• You must not use AI for writing the assignment. The University treats the use of artificial intelligence or chatbots to complete all or part of an assessment as contract cheating. If you are suspected of using AI to write all, or part, of your essay, you will be investigated under the contract cheating process.
Referencing
If you reference papers in your answers, you should reference them using a consistent referencing system, such as the Harvard referencing system; you should normally cite sources in the text. As a general rule, you should avoid using footnotes to reference.
• If you include a quote, it should be in quotation marks, and a page number included in the in-text reference.
• Whilst you should normally avoid larger quotes, if you include them, you should also indent the text.
If you cite a paper in your essay, you should also include a full reference to the paper in the reference list at the end of the paper.
• Do not list papers in your reference list that you have not referenced in the paper
University marking criteria
|
|
Fail (<40) |
3rd (40-49) |
2.2 (50-59) |
2.1 (60-69) |
1st (70+) |
|
Attainment of Learning Outcomes |
Attainment of only minority of the learning outcomes. |
Limited attainment of intended learning outcomes |
Some limitations in attainment of learning objectives but has managed to grasp most of them. |
Attained all the intended learning outcomes for a unit. |
Excellent range and depth of attainment of intended learning outcomes. |
|
Application of Methods |
Able to demonstrate a clear but limited use of some of the basic methods and techniques taught. |
Able to use a proportion of the basic methods and techniques taught. |
Able to use most of the methods and techniques taught. |
Able to use well a range of methods and techniques to come to conclusions. |
Mastery of a wide range of methods and techniques |
|
Analysis, Comprehension and Synthesis |
Weak and incomplete grasp of what has been taught. |
Evidence of study and comprehension of what has been taught, but grasp insecure. |
Evidence of study and comprehension of what has been taught |
Evidence of study, comprehension, and synthesis beyond the bounds of what has been explicitly taught. |
Evidence of study and originality, combined with evaluation and synthesis of material clearly beyond the bounds of what has been taught. |
|
Technical Mastery |
For technical material, students may be able to apply a limited number of basic concepts, with significant errors |
For technical material, students will be able to apply basic concepts, but there may be some substantial errors |
For technical material, students will be able to apply most standard concepts, but with some errors or major omissions. |
For technical material, students will be able to apply most standard concepts, and some advanced concepts but there may be some errors or minor omissions |
For technical material, students will be able to apply all standard concepts, and select appropriate advanced concepts; errors will normally be few and minor in impact |
|
Evaluation/Critical Analysis |
Deficient understanding of the issues and concepts underlying the techniques and material taught. |
Some grasp of the issues and concepts underlying the techniques and material taught, but weak and incomplete |
Some grasp of issues and concepts underlying the techniques and material taught |
Able to employ critical analysis and judgement of the techniques and material taught |
Able to display a command of critical analysis and judgement of the techniques and material taught |
|
Quality of presentation |
Poor presentation |
Poor presentation |
Adequate presentation
|
Very good presentation |
Excellent presentation |
Note: Because the marking criteria consider a number of dimensions, it is unlikely that a single piece of work fits nicely into all of the descriptions above. For example, a piece of work may have excellent presentation, but due to significant errors, and major deficiencies, the piece of work may still be awarded a fail mark.