Analysing Survey Data with SPSS

Who is this course for?

It is designed for postgraduate students, early career researchers and practitioners planning to work with survey data in any discipline.

Course overview and aims

This course provides an introduction to the principles and practices of undertaking quantitative data analysis of survey data in SPSS. The course combines discussion, demonstration and hands-on exercises.

Please note: Participants will need access to SPSS in order to take part in the course.

Topics

• Exploring phenomena of interest using quantitative measures
• Types of numerical data: nominal, ordinal, interval and ratio variables
• Introduction to the SPSS interface
• Data entry
• Setting up an SPSS project with example data
• Getting to know the sample data using descriptive statistics
• Recoding and combing variables
• Describing the relationship between 2 variables
• Moving beyond the descriptive: understanding hypothesis testing and p-values
• Moving beyond the descriptive: running Chi-square, independent sample t-tests and ANOVAS
• Moving beyond the bivariate: running and interpreting a linear regression analysis
• Tips for writing up findings and tables

Learning objectives

By the end of the course, participants will be able to:

• Input and import their data into SPSS
• Explore and recode their key measures with confidence
• Interpret results of bivariate descriptive analyses and report these clearly.
• Set up a null hypothesis and interpret a p-value
• Test the relationship between two variables using appropriate inferential statistics
• Understand how to run and interpret a linear regression analysis.

Format and documentation

This course is delivered in a series of live online sessions during the day that combine discussion, demonstration and hands-on exercises. Participants have the opportunity to discuss their quantitative projects with each other, and with the facilitators. Participants are provided with slide decks, example data, reading lists and resources to further knowledge about the topics covered during the day.

Facilitator

Sarah L Bulloch, PhD is a senior associate of Qualitative Data Analysis Services and teaching fellow at the CAQDAS Networking Project at the University of Surrey, UK. Sarah has expertise in both quantitative and qualitative analysis techniques and has applied them in academic, public sector, private and third sector contexts. Her PhD explored the relationship between social trust and gender using large scale population datasets and applying multivariate linear regression, multivariate logistic regression, multi-level modelling and structural equation modelling. Her current work and research centres around enabling others to apply research methods in a meaningful, robust and flexible way.

About Qualitative Data Analysis Services (QDAS)

QDAS provide tailored and flexible training, consultancy, coaching and analysis for qualitative, quantitative and mixed-methods researchers. We specialise in facilitating high-quality analysis through the powerful use of digital tools. Our website provides information about our work, including our pedagogy - the Five-Level QDA method, which underpins the way we think about, undertake and teach methods and tools.