Quantitative Methods & Data Analysis - SOC00006M

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  • Department: Sociology
  • Module co-ordinator: Dr. Timothy Huijts
  • Credit value: 20 credits
  • Credit level: M
  • Academic year of delivery: 2019-20

Module will run

Occurrence Teaching cycle
A Autumn Term 2019-20

Module aims

The module aims to introduce graduate students in the social sciences to a range of common quantitative data analysis skills and techniques. At the end of the module students should be able to both carry out their own analyses of large scale statistical datasets using SPSS and be able to critically interpret the use of such techniques in the work of others.
The module makes no assumptions about a prior knowledge of computing or statistics. The module counts as 20 credits. The module does not cover experimental techniques. Instead, the focus is on both exploratory and explanatory methods, particularly in relation to those key topics in contemporary statistics of the sort that are routinely found in sociological literature and survey research. Students should be able to choose an appropriate statistical technique to deal with their question research and to justify their choice. Each technique has advantages and disadvantages that influence the way social world is interpreted. Students should be aware of them at the end of the course. A critical attitude with regard to the various quantitative methods is then encouraged. To help students in this approach, many examples of the way statistical techniques have been used in social sciences researches will be given and discussed.
A social scientist is a craftsman who needs to choose carefully his tools in order to make skilfully and thoughtfully his/her art. Remember this: statistics do not lead your analyses; you do. They are only instruments helping social scientists in their reflection on the social world.

Module learning outcomes

On completing this module students will be able to:

  • Use SPSS to conduct basic statistical analysis
  • Carry out basic exploratory analyses of a set of data
  • Calculate basic descriptive statistics for a set of data
  • Understand the concept of statistical significance and carry out basic inferential procedures
  • Construct and interpret contingency tables
  • Carry out and interpret analyses of variance
  • Calculate and interpret appropriate coefficients describing bivariate relationships
  • Carry out a multiple linear regression and a binary logistic regression

Assessment

Task Length % of module mark
Essay/coursework
Quantitative Methods & Data Analysis - Essay
N/A 100

Special assessment rules

None

Reassessment

Task Length % of module mark
Essay/coursework
Quantitative Methods & Data Analysis - Essay
N/A 100

Module feedback

Feedback on all work is provided in a variety of ways and you must make the most of all opportunities do discuss your assessment and study progress:

1. After each open assessment you will receive feedback on the strengths and weaknesses of your work. This will be available within 4 weeks of the submission deadline

2. You will meet with your supervisor twice a term and you should discuss any concerns that you have and also present your assessment feedback for further comment

3. You will be asked to comment on the teaching of the modules and results will be discussed at Teaching Committee

4. You will have five supervision meetings with your dissertation supervisor through the summer months to enable you to discuss the different aspects of your work.

Indicative reading

These will be available on the module sites through the Yorkshare VLE. Most reading materials will be journals or book chapters which will be in pdf format. These can be downloaded and annotated on your pc if you don't want the expense of printing.

Recommended books will be available in the library.



The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.