Research Methods and Data Analysis I

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Conduct and interpret results from basic statistical techniques and analyses.
• Understand the basic concepts of research methods and statistics within the context of experimental psychology.
• Present data and perform basic analyses, by hand and using the statistics package SPSS.

• Experimental Questions: Hypothesis formation, the null hypothesis, variables (independent, dependent, discrete, continuous). Measurement scales (nominal, ordinal, interval, ratio)
• Research Methods: Experimental vs. non-experimental, case studies, correlation, laboratory vs. field, independent samples, repeated measures, mixed factorial designs, control groups, random allocation, sampling methods (random, stratified, snow-ball, convenience, etc.), reliability, validity, controlling for participants' expectations and experimenter effects.
• Descriptive Statistics: Means, modes, medians, percentiles, variance, standard deviation, interquartile range.
• Presenting Data: Tables, frequency plots, cumulative frequency plots, histograms, stem & leaf plots, box & whisker plots, scatter plots, bar charts, applied to simple and factorial designs, including interactions.
• Samples & population distributions: skew, kurtosis, bimodal distributions, transforming data, normal distribution, z-scores, sampling distribution of the mean, Central Limit Theorem, standard error, confidence intervals.
• Statistical Tests: z-test and one-sample t-test.

Teaching and learning methods

Students listen to a theoretical lecture each week, where rationale, limitations and interpretation of results of various statistical techniques is presented. They also learn about basic statistical concepts. This can be also presented in form of a recording. Then, they have a chance to put theory into practice during obligatory feedback sessions/workshops (online or in-class).

Resources & Reading list

Textbooks

Howitt, D & Cramer, D. (2014). Introduction to Research Methods in Psychology. Harlow,England; New York: Pearson.

Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics. Sage.

Assessment strategy

Formative assessment: Answers and feedback will be provided for the tutorial exercises to give students the chance to monitor their own progress.

Summative assessment: Students will also take 4 sets of MCQs tests to check their knowledge and understanding of the material covered in the recordings - this will be worth 8% of module marks. The second element of assessment, midterm coursework, will be weighted at 29.5% – students will design a study according to the criteria explained to them in advance; the third, end-of-semester assessment, will be weighted at 60%. This assessment includes hand and SPSS computations. Participation in the Research Participation Scheme provides 2.5% of module marks.

Feedback The primary source of feedback comes from the tutorial sessions, as well as provided exercises and their explanations. General feedback on the mid-semester assessment is provided during the lectures. Example past exam questions will be also provided, together with model answers and information required to generate the answers (moclk exam). There will be a revision session in the last lecture of the semester. Should students have any concerns about their progress on the course, or understanding of a particular area, they are welcome to schedule appointment during office hours of both lecturers.

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