POLS0010 - Political Science - Data Analysis - Essay Writing Assessment Answer

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    University College London

POLS0010 - Political Science - Data Analysis - Essay Writing Assessment Answer

ESSAY QUESTIONS 2018–2019 (TERM 1 – Part 2)
Guidelines for Completing and Submitting POLS0010 Essay

  •  Read the below guidelines to avoid losing unnecessary marks.
  •  The assessment is due on Monday 7th January 2019, 14.00 hours. Please follow all designated Department of Political submission guidelines. THESE MAY BE DIFFERENT TO THOSE OF YOUR HOME DEPARTMENT. The submission guidelines are available on the Moodle page for this module. You must submit one copy of your essay via Turnitin. The word limit is 1,500 words, excluding tables and graphs, references, and your R script appendix (see below).
  •  This is an assessed piece of coursework for the POLS0010 module; collaboration and/or discussion with anyone is strictly prohibited. The rules for plagiarism apply and any cases of suspected plagiarism of published work or the work of classmates will be taken seriously.
  •  The dataset for the essay can be found in the ‘Dataset’ folder on Moodle.
  •  The data for Part A come from the Labour Force Survey, January-March 2015 – a single-stage stratified random sample household survey of the labour market in the UK. A subset of variables are included in your dataset. The data are collected about the individuals (e.g. working hours and qualifications).
  •  You may open up the dataset and work on the essay questions anytime up until the submission date. There is no limit on the number of times you may open the data files. Be sure to save your data file and R script file.
  •  The essay questions comprise two sections; you must complete each part of each section.
  •  Where appropriate, answers should be written in complete sentences; no bulleting or outlining. Be sure to answer all parts of the questions posed and interpret output statistically and substantively.
  •  You should include tabular and graphical output alongside your written answers in Part A and without any tabular and graphical output in Part B (see below).
  •  You should include a copy of your R script as an appendix to your essay. FAILURE TO INCLUDE THE R SCRIPT WILL INCUR A 5 POINT PENALTY. Note that your R script file should include comments indicating the question being addressed. Your R script file should contain only the exercises/questions asked here.
  •  All variable names are shown in italics.
  •  You should discuss the interpretation of your results and how they relate to the questions you were asked.
  •  You may assume the methods you have used (e.g. linear regression) are understood by the reader and do not need definitions, but you do need to say which techniques you have used and why.
  •  As this is an assessed piece of work, you may not email/ask the module tutors questions about the essay questions.
  •  10 points will be awarded for presentation.
  • This assessment is out of 50 marks and will count towards 50% of the term 1 mark.

PART A: Multiple Linear Regression - POLS0010
This question uses the lfs_jm2015.dta dataset. You have been commissioned by the Department for Work and Pensions to investigate gender differences in hours worked. They would like to know whether full-time working men or women work more hours and whether there are key demographic and socioeconomic factors that explain any difference. You will fit a multiple linear regression model(s) predicting hours worked by gender. You may choose to recode or transform some variables in your data. You should report any decisions you take to adjust for non-response in your data. Present your findings in a report to be read by a ministerial aide who says they has never taken a statistics course.
PART B: Regression Interpretation - POLS0010
The model below is from a paper published in a leading social science journal on the impact of childhood class on adult wellbeing using data from four birth cohort studies in the UK. The model analyses the relationship between several explanatory variables, including whether a respondent grew up in a low social class, and a wellbeing scale. The unit of analysis is persons resident in the UK in private households. The dependent variable ranges from 0-10, where higher value reflect better wellbeing. Your task is to interpret the model and write up the results as if you were writing the discussion for publication in a quantitative social science journal. Interpret the model statistically and substantively and detail its limitations. Discuss whether the results support an effect of childhood social class on adult wellbeing. A table containing descriptive statistics is appended.

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  • Posted on : August 14th, 2018
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