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Content: This module will introduce students to the fundamentals of the analysis of quantitative psychological data. The first five weeks will cover topics ranging from quantitative research design, types of data, measures of central tendency and distribution, and statistical power. The rest of the module tackles a number of basic statistical tests designed to analyse different types of data, one test per week. Students will learn how to compare groups of participants on some continuous measure, how to test for correlations between variables, and how to ensure that their analyses are rigorous and reliable. In addition to this theoretical content, students will learn how to do data analysis in practice using the language R and the programme R Studio. No experience of coding or data analysis is required - we will introduce the basics of using the software, reading your data, visualising it, and transforming it for analysis, and will build upon this foundation in later lectures to cover more complex types of analysis.Ìý

Teaching delivery: The module is taught over 14 weeks. Each week consists of an hour-long taught lecture and a 90-minute practical

Indicative topics:

• The Research Process
• Psychological Data
• Summarising & Visualising Data
• Probability Theory
• Sampling
• Hypothesis Testing
• T-tests
• Correlation
• Linear Regression
• One-Way ANOVA
• Chi-square test
• Non-parametric tests
• Reproducible Science

Module Aims: This module aims:

• To introduce the principles of working with psychological data in practice, including data wrangling, visualisation, and producing summary statistics
• To introduce the foundations of psychological research, from describing data to the theory behind null hypothesis testing, and a range of basic inferential statistical tests.
• To introduce the R language for data analysis, the RStudio software, and the range of packages that we’ll be using on the course
• To teach students critical thinking skills in the context of research design and analysis, which will enable them to interpret and critique the methods and findings of quantitative psychological research studies

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