Research Methods and Data Analysis III

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• understand the rationale behind different statistical tests, probability and hypothesis testing, various research methods, statistical significance, power, reliability, generalizability, and replicability
• evaluate and compare different research methods and designs
• interpret and present the output of statistical tests and measures
• write-up results of various statistical tests following APA guideline
• evaluate ethical issues relating to psychological research
• formulate experimental designs to answer simple research questions
• select and apply appropriate statistical tests and measures via hand calculations and SPSS

• Refresher from the year one (descriptives, probability, normal distribution and z-scores, sampling distribution, CLT, power); Hypothesis testing
• Hypothesis tests applied to means: t-tests for independent and related samples)
• Nonparametric equivalent of t-tests
• Simple Analysis of Variance (for independent and related samples)
• Nonparametric equivalents to ANOVA
• Factorial Analysis of Variance (between, within, and mixed models)
• Correlation (parametric, nonparametric, partial)
• Simple and Multiple Regression
• Categorical data and chi-square
• Ethics

Teaching and learning methods

Theoretical lectures, followed by physical/interactive SPSS lectures and tutorials/feedback sessions (preferably 1 x 90 minute session per week delivered on campus).

In the theoretical lectures students learn about different statistical techniques, their rationale, requirements and hand computations. Then the second set of physical/interactive lectures will be mostly SPSS based - students will learn how to carry out different tests, interpret SPSS outputs and write up results.

The associated tutorials/feedback sessions are entirely practical and involve the use of hand calculations and SPSS in data analysis.

There are Teaching Assistants who actively ensure that students are understanding and completing the tasks. Office Hours are offered and extra revision sessions are scheduled before the final exams.

Resources & Reading list

Textbooks

Field, A. (2003). Discovering Statistics using IBM SPSS Statistics. SAGE Publications Ltd.

Howell, D. (2009). Statistical Methods for Psychology. Wadsworth.

Assessment strategy

There are 4 sets of MCQ tests run every few weeks that together are worth 20% of the module mark. The remaining 80% is the final assessment, consisting of hand and SPSS computational tasks.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat Information

Repeat type: Internal & External