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STAT6117 COURSEWORK 2 ASSIGNMENT 2021

Submission

Your solution to the following tasks is worth 60% of the overall marks for this module. This coursework is due in on January 13, 2022 at 16:00 (4:00pm). You should submit coursework electronically via the TurnitinUK on Blackboard in PDF format (see more information on pp. 4-5).

The coursework should not exceed 3,500 words. You can use appendices to display additional information and big tables, but these appendices should not exceed 5 pages. If you exceed these limits, your mark will be reduced (see more information on pp. 4-5).

The word count includes:

• Body of Text

• Section Headings and Subheadings

• Quotes and citations that are within the body of text

 

The word count excludes:

• Title and Subtitle

• Table of Contents

• Abstracts (if relevant)

• Tables and Figures including captions • List of figures, list of tables etc.

• Acknowledgements

• Appendices (which have their own limit of 5 pages)

• Bibliography / List of References

 

This coursework assignment relates to materials taught in lectures 13-24 and computer workshops/tutorials 5-8.

Marking criteria used in marking this piece of coursework can be seen on p. 6 and marks breakdown for each section of the assignment is shown on pp. 2-3.

   

Assignment

People may be (dis)advantaged in the job market depending on their socio-demographic characteristics. For instance, it is more common for women than men to be in part-time employment, particularly if the woman has caregiving responsibilities. Markey et al. (2002) suggest this could put women in a disadvantaged position in the workplace.

Thus, you will investigate, whether there is an association between gender and the likelihood of being in part-time employment and whether that association depends on marital status, which is a proxy indicator for caregiving responsibilities, as married individuals are more likely to have children than those not married. In addition, you will take your investigation of whether women are disadvantaged in the workplace further by examining the association between gender and occupational social class (while controlling for relevant explanatory variables).

Use literature to guide you in choosing which explanatory variables to include in your models (unless otherwise instructed on p. 3 of this document), to explain the motivation for the study, and to discuss the results. The citation mentioned above is a good place to start, but you also need to search relevant literature yourself. Do not forget to cite relevant literature when discussing the methods you use in your coursework assignment (hint: you can use textbooks for this purpose).

The data used in this assignment were extracted from the Jan-Mar 2015 Quarterly Labour Force Survey in the United Kingdom and include the following variables:

Variable name Variable label

Categories

id

New random ID number

  

sex

Respondent's gender

0 = Woman, 1 = Man

marstat

Marital status (recoded)

1 = Single, 2 = Married/cohabiting, 3 =

Divorced, widowed

soc_class

Occupational social class

 1 = Routine and manual, 2 = Intermediate, 3 =

Professional

educ

Highest educational qualification

0 = No education, other qualification or not known, 1 = GCSE or A-level, 2 = Degree or higher

ftpt

Full-time or part-time in main job

 0 = Full-time, 1 = Part-time

country

Country in the UK

 0 = England, 1 = Wales, 2 = Scotland, 3 =

Northern Ireland

age

Respondent's age

  

The specific tasks of the coursework assignment are outlined below. Use the task numbers when writing up your answer (e.g. “1 Introduction” and “2.1 Distribution of the outcome variable”).  

Specific tasks 

1. Introduction to the research problem and dataset including a relevant literature review [10 marks].

2. Model the binary measure of working full- or part-time (ftpt).

2.1. Present relevant descriptive statistics. [10 marks]

2.2. Which type of regression do you use and why? [5 marks]

2.3. Build the model. Explain your choice of variables showing supporting evidence, such as statistical significance tests and measures of the fit of the model. [8 marks]

2.4. Test whether there is an interaction between gender (sex) and marital status (marstat). Explain the reasons for (not) including the interaction effect in your final model showing supporting evidence, such as statistical significance tests and measures of the fit of the model. [5 marks]

2.5. State the equation of the final model. Present and interpret the results of the model using relevant regression coefficients or their transformations. [12 marks]

3. Model the multicategory measure of social class (soc_class). The variable is ordered, as routine/manual group is seen as lower than the intermediate group, which again is seen as lower status than the professional group. In this section, only use variables sex, age and marstat as explanatory variables.

3.1. Present relevant and informative exploratory/descriptive analysis, but do not repeat information already shown in section 2.1. [5 marks]

3.2. Discuss the two types of regression models you could use for this outcome. Choose the one that is more appropriate for your model. Explain your choice and provide evidence justifying it. [8 marks]

3.3. State the equation of the final model. Present and interpret the results using relevant regression coefficients or their transformations. Comment on statistical significance of the explanatory variables and on the fit of the model. [12 marks]

4. Summarize the conclusions of the analyses for tasks 2 and 3 as if you were requested to present the result to a non-technical audience. Make sure there is a link between the introduction and this section. [15 marks]

In addition, up to 10 marks will be awarded for report quality (neat, well-labelled tables and plots, clear language) and for showing imagination and initiative (e.g. critically commenting and interpreting the results or insightfully discussing the model building process).

Present your results in a written coherent report including relevant tables, figures, and your written answers to the tasks. The report should be easy to understand even if read by a person who has not been trained in statistical methods. Make sure all tables and figures are neat and clear. Give informative titles to every table and figure – the reader should be able to understand the table/figure without reading the text. Number tables and figures consecutively

(Table 1, Table 2, etc.; Figure 1, Figure 2, etc.; Appendix table 1, Appendix table 2, etc.; Appendix figure 1, Appendix figure 2, etc.) Use these numbers when referring to tables/figures in text. Do not use jargon or variable names in the text.

   

Additional information about coursework submission

You should submit coursework electronically via the TurnitinUK plagiarism device on Blackboard, by not later than the published date and time. Turnitin is a plagiarism detection tool which checks your work against electronic sources and other submissions for the same assignment.  

Login to the Blackboard site for this module and select the Assignments link from the lefthand menu.  Find the coursework and click View/Complete. There will be a series of screens to complete and then you will upload your assessment as an electronic file.  

For a tutorial explaining the submission procedure in detail please go to the iSolutions website: http://elearn.southampton.ac.uk/blackboard/student/studentplagiarism/ 

When you submit an assignment through Turnitin you will receive a confirmation email containing a submission ID number, which is proof that you have submitted your work. Make sure you keep a copy of the confirmation email you receive which will act as a receipt for your electronic submission. If you do not receive a submission ID number or an email it means that you have not submitted. If this is the case you will be penalized. If you think you have submitted but do not receive this email then you should contact the module coordinator as soon as possible.

You are advised to leave plenty of time before the deadline for electronic coursework submission, delays due to computer ‘glitches’ will not be considered as justification for late submission.  

Penalty for late submission  

When coursework is set a due date for submission will be specified and there will be associated penalties for handing in work late unless a deadline extension has been formally granted.  

Work submitted up to 5 days after the deadline will be marked as usual, including moderation or second marking, and feedback prepared and given to the student. The final agreed mark is then reduced by the factors in the following table.

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  

Zero  

 

For example, if your mark for the coursework is 63% but you hand in your work 3 working days late, then your final mark would be 63*0.7 = 44.1%.   

Working days are Monday to Friday throughout the calendar year, including student vacation periods (but excluding University closure dates at Easter and Christmas).  

Policy for overlength work  

Your assignment should not exceed 3500 words (+ up to 5 pages of appendix).  Your work will be overlength if you go even one word over the stipulated length or upper limit. There is no percentage leeway over the stated word length.  Overlength work will be addressed through marking only that portion of work that falls within the word limit.  Your mark will be based on this portion of your work only, with the result that the mark will usually be lowered.

Procedure for coursework extensions  

If you know there will be a valid reason why you cannot submit the work by the given deadline you must request an extension as soon as possible.  Coursework extension requests should provide adequate detail of the reasons why you are seeking an extension and be made on the ‘Special Considerations and Deadline Extension request form’ available on the Form store on the FSS Faculty Student Hub or at

http://www.southampton.ac.uk/quality/assessment/special_considerations.page  

Applications must be accompanied by documentary evidence e.g. self-certification of illness form or certification by a qualified doctor specifying nature of illness to include duration and impact on ability to study, letter from qualified counsellor, copy of police incident report, etc.

Your completed form should be submitted to the Student Office who will arrange for your request to be reviewed.  The Student Office will contact you via your University email account to let you know once approval has been made.  It is your responsibility to request an extension in a timely manner. 

In cases where further extensions to the original application are requested, students should submit a new application making reference to the original.

Academic integrity and referencing 

See module outline on Blackboard for more information.


Social Statistics and Demography Marking Criteria: Quantitative assessment

This marking rubric is to be used in conjunction with the University grade descriptors available here: http://www.southampton.ac.uk/quality/assessment/framework/principles_and_definitions.page#assessment_descriptors. Note that the rating given for each criterion is descriptive and does not necessarily relate in a direct numerical way to the mark achieved.   

 

Criterion

Excellent

Very good

Good

Competent

Acceptable

Poor

Inadequate

Technical and practical competence, including the use, collection and /or analysis of data, and implementation of appropriate methods and/ or software (if applicable)

 

 

 

 

 

 

 

Knowledge and content, including the choice of a method to answer the question/task; interpretation of the results

 

 

 

 

 

 

 

Organisation and communication, including the report structure, exposition, quality of writing (if appropriate)

 

 

 

 

 

 

 

Presentation, including formatting, front matter, layout, graphs and tables, visual clarity  

 

 

 

 

 

 

 

 

Critical analysis of the literature, data and methods, with evidence of original thinking (as appropriate)

 

 

 

 

 

 

 

Citation and referencing, both within the text and in the list of references (if appropriate)