Software for Data Analysis and Modelling

SEMESTER 2 2019/20

COURSEWORK BRIEF:

Module Code: MANG6231 Assessment: Individual Project Weighting: 100%

Module Title: SAS Software for Data Analysis & Modelling

Module Leader: Nigel Ling

Submission Due Date: @ 16:00 16th March 2020 Word Count: 2000

Method of Submission: Electronic via Blackboard Turnitin ONLY (Please ensure that your name does not appear on any part of your work)

Any submitted after 16:00 on the deadline date will be subject to the standard University late penalties (see below), unless an extension has been granted, in writing by the Senior Tutor, in advance of the deadline.

University Working Days Late: Mark:

1 (final agreed mark) * 0.9

2 (final agreed mark) * 0.8

3 (final agreed mark) * 0.7

4 (final agreed mark) * 0.6

5 (final agreed mark) * 0.5

More than 5 0

This assessment relates to the following module learning outcomes:

A. Knowledge and Understanding A1. The key features of marketing data, how to collect it, analyse it and interpret the statistical output from SAS.

B. Subject Specific Intellectual and Research Skills B1. Acquire data collection skills; B2. Acquire data exploration skills; B3. Acquire data analysis skills.

C. Transferable and Generic Skills C1. Use SAS software to access and manipulate local and remote data, to create simple and advanced queries and reports and graphs; C2. Conduct Statistical modelling using marketing data in SAS;. C3. Learn and practice data collection techniques

3

Coursework Brief:

Introduction This module is 100% coursework. There will be one assignment, which will examine three distinct but inter- connected tasks. The objective of the assignment is to test your ability to formulate research hypotheses from the literature, to write a SAS program that you can use to test the hypotheses on survey data, and to write up the work carried out. Task 1 Literature Review (20%) 1. Review at least five published articles that explore how corporate social responsibility (CSR) is related to

how consumers respond to the ethical behaviour of multinational corporations, for example by changing their buying behaviour. The articles must be published in reputable journals, preferably 2* or higher on the ABS list of journals provided on Blackboard.

2. Download the assignment data that has been randomly allocated to you. The data allocated to you is named after your UoS ID. The data were collected by questionnaire both online and in person: To understand what each of the variables in the dataset measures, download from blackboard the questionnaire that was used to collect data.

3. Formulate research hypotheses that you would expect to be true based on the evidence from the literature you have reviewed. An example of a hypothesis might be:

SEMESTER 2 2019/20

Hypothesis 1: Women are more likely than men to pay more for the products or services of multinationals that they believe have behaved ethically.

4. Write up your literature review including the hypotheses arising from it. Your review must not exceed 1000 words including everything except the bibliography and reference list.

Task 2 SAS Program to read, manipulate and analyse allocated dataset (60%). Write a SAS program, which must: 1. Read the dataset you were allocated into SAS. Your data steps must include adding permanent

attributes to the data such as formats and labels; and storing the data as a permanent SAS dataset.

2. Manipulate the data: (i) The data is raw and contains errors such as missing values or data values that were entered

incorrectly. Identifying these errors will not be straightforward. You will need to inspect the data carefully and then make some decisions about what you will do to clean the data. You should then write SAS code to perform the cleaning.

(ii) Recode existing variables where necessary, for example recode a text variable into a numeric equivalent; or create new variables, for example by combining sub-variables (e.g. Qu_1_a and Qu_1_b) into a single, summated measure.

3. Conduct exploratory data analysis using descriptive statistics, charts, tables, etc.

4. Test the hypotheses you formulated from the literature review using SAS procedures such as PROC REG, GLM, etc. You may use any procedures you deem necessary even if we have not covered them in the module.

5. Use comments throughout your program to explain what you are doing. Include a comment at the top of your program to document when the program was written, your student ID and the purpose of the program.

6. This assignment is about SAS programming and data analysis using SAS. Therefore, all data manipulation, exploration and analysis must be conducted within SAS. You will lose credit if, for example, you use Excel to perform any of the data manipulation work.

7. Be selective in both the procedures you use and the variables you analyse. All your analysis must contribute towards testing your hypotheses.

Task 3 Analysis Report (20%). 1. Write up the data analysis you conducted with your SAS program. The report must describe and justify

the steps you took to explore and analyse the data; it must also report and interpret your results. The report must not exceed 1000 words including everything except the bibliography and reference list.

Submit to Blackboard: 1. A single pdf document containing (i) your literature review, (ii) your analysis report and (iii) your SAS

program text (copied and pasted from SAS program Editor to MS word). Please name your files using your student ID number, e.g. 12345678.pdf and 12345678.sas. Do not include your name etc.

SEMESTER 2 2019/20

Nature of Assessment: This is a SUMMATIVE ASSESSMENT. See ‘Weighting’ section above for the percentage that this

assignment counts towards your final module mark.

Word Limit: +/-10% either side of the word count (see above) is deemed to be acceptable. Any text that exceeds an

additional 10% will not attract any marks. The relevant word count includes items such as cover page, executive

summary, title page, table of contents, tables, figures, in-text citations and section headings, if used. The relevant word

count excludes your list of references and any appendices at the end of your coursework submission.

You should always include the word count (from Microsoft Word, not Turnitin), at the end of your coursework

submission, before your list of references.

Title/Cover Page: You must include a title/ cover page that includes: your Student ID, Module Code, Assignment Title,

Word Count. This assignment will be marked anonymously, please ensure that your name does not appear on any part

of your assignment.

References: You should use the Harvard style to reference your assignment. The library provide guidance on how to reference in the Harvard style and this is available from: http://library.soton.ac.uk/sash/referencing

Submission Deadline: Please note that the submission deadline for Southampton Business School is 16.00 for ALL

assessments.

Turnitin Submission: The assignment MUST be submitted electronically via Turnitin, which is accessed via the

individual module on Blackboard. Further guidance on submitting assignments is available on the Blackboard support

pages.

It is important that you allow enough time prior to the submission deadline to ensure your submission is processed on time as all late submissions are subject to a late penalty. We would recommend you allow 30 minutes to upload your work and check the submission has been processed and is correct. Please make sure you submit to the correct assignment link. You will know that your submission has completed successfully when you see a message stating ‘Congratulations – your submission is complete…’. It is vital that you make a note of your Submission ID (Digital Receipt Number). This is a unique receipt number for your submission, and is proof of successful submission. You may be required to provide this number at a later date. We recommend that you take a screenshot of this page, or note the number down on a piece of paper. You should also receive an email receipt containing this number, and the number can be found after submitting by following this guide. This method of checking your submission is particularly useful in the event that you don’t receive an email receipt. You are allowed to test submit your assignment via Turnitin before the due date. You can use Turnitin to check your

assignment for plagiarism before you submit your final version. See “Viewing Your Originality Report” for guidance.

Please see the Module Leader/lecturer on your module if you would like advice on the Turnitin Originality report.

The last submission prior to the deadline will be treated as the final submission and will be the copy that is assessed by the marker. It is your responsibility to ensure that the version received by the deadline is the final version, resubmissions after the deadline will not be accepted in any circumstances. Important: If you have any problems during the submission process you should contact ServiceLine immediately by email at [email protected] or by phone on +44 (0)23 8059 5656.

Late Penalties: Further information on penalties for work submitted after the deadline can be found here.

Special Considerations: If you believe that illness or other circumstances have adversely affected your academic

performance, information regarding the regulations governing Special Considerations can be accessed via the

Calendar: http://www.calendar.soton.ac.uk/sectionIV/special-considerations.html

SEMESTER 2 2019/20

Extension Requests: : Extension requests along with supporting evidence should be submitted to the Student Office

as soon as possible before the submission date. Information regarding the regulations governing extension requests

can be accessed via the Calendar: http://www.calendar.soton.ac.uk/sectionIV/special-considerations.html

Academic Integrity Policy: Please note that you can access Academic Integrity Guidance for Students via the Quality

Handbook: http://www.southampton.ac.uk/quality/assessment/academic_integrity.page?. Please note any

suspected cases of Academic Integrity will be notified to the Academic Integrity Officer for investigation.

Feedback: Southampton Business School is committed to providing feedback within 4 weeks (University working days).

Once the marks are released and you have received your feedback, you can meet with your Module Leader / Module

Lecturer / Personal Academic Tutor to discuss the feedback within 4 weeks from the release of marks date. Any

additional arrangements for feedback are listed in the Module Profile.

Student Support: Study skills and language support for Southampton Business School students is available at:

http://www.sbsaob.soton.ac.uk/study-skills-and-language-support/.