2000 words, excluding references but including tables, and graphs (USE SPSS FOR GRAPHS). NB: The report should use multiple regression. Therefore, it is important that you choose a
continuous dependent variable.
• Form a sociological hypothesis/ research expectation about inequality in health, pensions,
health behaviours and well-being and their link to stratification variables such as class,
ethnicity, and gender
– You should aim to build on your Report plan however, it can be possible that your thinking
has evolved and you instead choose other data – describe in a sentence or two why you
needed to use other data.
– Link the hypothesis (es)/ research expectations and to existing literature (from class and/or
additional sociological scholarship)
– Write a brief Literature review that sums up what previous studies have done, max 300-400
words
– Posit a potential confounder / mediator / moderator in this relationship. You are encouraged
to posit a moderator as this is more challenging, and extra points will be given for
attempting this.
– Describe the data that you will be using and the variables you are going to focus on, 150-max
200 words, post a link to the UK data Service if the data can be found there or from other
websites from which it can be downloaded). We usually include such sections in papers
because they mean that our analysis can be replicated.
C. Test your hypothesis with data
a. Create a table which describes the distributions of your independent, dependent, and mediator or confounder variables. It is important to demonstrate.
i. appropriate variable choice and coding
ii. Appropriate format of descriptive statistics
iii. correct interpretation of table
b. Create a table of stepwise regression results
i. At least two models: (1) simple regression, (2): 1 + one
mediator/confounder main effect.
If a moderator is chosen, you will also have to provide results for a third
model: 2 + interaction effects
ii. Correct interpretation of each model, and changes in coefficients
between models
D. Drawing conclusions from your work
