Programmes

Statistical Methods for Social Research using SPSS

  • Methods Summer Programme
  • Department of Statistics
  • Application code ME408
  • Starting 2017

For those undertaking research in the social sciences, an ability to handle data is an essential skill. 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.  This course concentrates on transforming participants into competent and confident users of SPSS to enable them to conduct independent data analysis for their own research needs. 

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. 

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.

Dates
14 - 25 August 2017

Teaching faculty
Dr James Abdey, Department of Statistics

2017 Tuition fees
Student rate: £1,495
Academic staff/charity rate: £2,230
Professional rate: £2,800

Programme details

Key facts

Dates
14 - 25 August 2017

Format
Lectures, practical classes

Assessment
2-hour examination (optional)

Location
LSE's Central London Campus

 

Prerequisites

A foundation course in statistics at undergraduate level is recommended.

Course outline

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. (2013). Discovering Statistics using IBM SPSS Statistics. (4th 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.

Monday - Data visualisation, descriptive statistics
Tuesday - Sampling distributions, confidence intervals
Wednesday - Hypothesis testing (one- and two-sample)
Thursday - Categorical data analysis, correlation
Friday - Multiple linear regression and model building

Monday - Analysis of variance (ANOVA)
Tuesday - Discriminant analysis
Wednesday - Factor analysis
Thursday - Cluster analysis
Friday - Logistic regression + Exam (pm)

All lectures take place from 10am-1pm. Computer practical classes take place in the afternoon.

A 2-hour final examination will take place on the afternoon of Friday 25 August 2017.

Schedule

Please note: A full timetable will be provided at registration on Monday 14 August. The below schedule is subject to change.

 Week one (hours)

 

 Morning lecture

 Afternoon class

Mon

 3 hours

 1.5 hours

Tues

3 hours

1.5 hours

Weds

 3 hours

1.5 hours

Thurs

3 hours

1.5 hours

Fri

3 hours

1.5 hours

 

Week two (hours)

 

 Morning lecture

 Afternoon class

Mon

 3 hours

 1.5 hours

Tues

3 hours

1.5 hours

Weds

 3 hours

1.5 hours

Thurs

3 hours

1.5 hours

Fri

3 hours

Exam



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

Faculty

James Abdey is an Assistant Professorial Lecturer in Statistics having gained his PhD in 2009 from LSE.  His research interests include market research techniques and forensic statistics – the interplay of statistics and law.  James teaches several statistics courses to internal students and on the Summer School, and has been closely involved with the University of London International Programmes for a number of years writing numerous subject guides and undertaking many teaching visits to our partner institutions around the world.  Outside of academia, he has also worked on various quantitative-based consultancy projects in areas including the art market, the World Gold Council and the UK Parliament.

Testimonials

Dr. James Abdey is an inspiration both in terms of teaching skills and also in terms of knowledge in statistics. This course is great for students who do not have statistical training, and also good for those want a deeper understanding on this topic. 
2016 Participant

James' enthusiasm was contagious. He explained things thoroughly and clearly. All in all a gifted teacher!
2016 Participant

It's difficult to find methods courses that are targeted at academics as well as students, so this was a wonderful and much-needed opportunity!
2016 Participant

James is the best statistics lecturer I ever met in my life. Sorry for the previous lecturers who taught me statistics but it's true that James is one of his kind. He has all the traits that make a great tutor: energetic, enthusiasm, rich and robust knowledge and patience to explain. The atmosphere in his lecture is amazing as everyone is fully involved. I also would like to take this opportunity to thank James for all his help and work this summer and wish him the very best of luck.
2016 Participant

The course is not only very well structured, it is also taught in a detailed and very systematic way by a very enthusiastic and dynamic team. It'll definitely be a big plus for my research.
2015 Participant

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