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London School of Economics
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Statistical Methods for Social Research using SPSS


Dr James Abdey

Dates: 17-28 August 2015

2014 Tuition fees
Standard rate: £2310
Academic rate: £1365

*The 2015 tuition fees will be published on the website soon*

Dr James Abdey
Department of Statistics

Many researchers in the social sciences use SPSS to perform data analysis, but often formal training in use of the software and how to interpret output is severely lacking. Statistical Methods for Social Research using SPSS aims to eliminate the quantitative skills deficit which exists among many social science researchers.

This course will concentrate on transforming participants into competent and confident users of SPSS to enable them to conduct independent data analysis for their own research needs. Working with datasets, the course will cover widely-used statistical methods including descriptive statistics, data visualisation, statistical inference, categorical data, correlation and regression, analysis of variance and multivariate analysis (such as factor analysis).

This applications-oriented course is designed for researchers who lack the confidence to perform data analysis independently due to:

  • a lack of understanding of various statistical methods
  • not knowing which techniques are appropriate for different types of data
  • inexperience with using statistical software packages (specifically SPSS here)
  • not knowing how to interpret output from software packages and what conclusions can be drawn.

Course benefits:
After successful completion of the course, participants should be able to:

  • perform independent data analysis in the social sciences
  • determine which statistical method is appropriate in a given situation and be able to discuss the merits and limitations of a particular method
  • use SPSS to analyse datasets and be able to interpret output
  • draw appropriate conclusions following empirical analysis

Foundation course in statistics at undergraduate level

“James was an excellent course leader - brimming with enthusiasm for the subject”
2013 participant on Statistical Methods for Social Research using SPSS

“Dr. James Abdey is without doubt one of the best university-level instructors I’ve ever had.”
2013 participant on Statistical Methods for Social Research using SPSS

“I thoroughly enjoyed James' course — the structure, breadth, ambition and passion!”
2013 participant on Statistical Methods for Social Research using SPSS

Statistical Methods for Social Research using SPSS takes a more applied approach to conventional statistics by focusing on encouraging participants to “get their hands dirty with data”. Instead of being purely theory-oriented, emphasis will be more on the practical application of a variety of statistical techniques to supplied datasets. 

The course will consist of daily lectures supported by computer-based practical classes which will allow course participants to practise implementing the lecture material hands-on in SPSS. SPSS is a popular choice of statistical software and is ideally suited for empirical research in the social sciences.

Topics covered in the course will be wide-ranging, such that participants will be exposed to a variety of statistical methods reflecting the different sorts of data which a researcher may be required to analyse. Assumptions, merits and limitations of methods will be discussed.

The course will begin with an overview of the SPSS environment, followed by data visualisation and descriptive statistics. Other topics to be covered include interval estimation and hypothesis testing (for one and two samples), categorical data, correlation and regression, analysis of variance and several multivariate analysis techniques, such as factor analysis.

Main text
Field, A. (2009) Discovering Statistics Using SPSS (3rd ed.). Sage.
However, a “course pack” will be provided which will serve as background reading.

Software used
SPSS (currently version 21)

Teaching schedule
The following teaching schedule is indicative only, and is subject to change.

Teaching schedule
  Monday Tuesday Wednesday Thursday Friday
Week 1 Data visualisation, descriptive statistics Sampling distributions, confidence intervals Hypothesis testing (one- and two-sample) Categorical data analysis, correlation (Multiple) linear regression
Week 2 Analysis of variance (ANOVA) Factor analysis Discriminant analysis Cluster analysis Logistic regression + Exam (pm)

All lectures take place from 10am-12:30pm. Computer practical classes take place in the afternoon.

A 2-hour final examination will take place on the afternoon of Friday 29 August 2014.