Introduction to the Experimental Method: Experiments vs. Non-Experiments and the Role of True Experiments.

Laboratory Experiments: An Introduction to Controlled Scientific Investigation and Their Role in Psychology.

Field Experiments: An Introduction to Controlled Research in Natural Settings and Their Role in Psychology.

Natural Experiments: Exploring Research Where the IV is Not Manipulated and Their Role in Psychology.

Quasi-Experiments: Understanding Research Without Random Allocation of Participants.

Non-Experiments in Psychology: Research Methods Used When Ethical Concerns or Complex Variables Make Experiments Impossible.

Observational Techniques in Psychology: Exploring Types (Naturalistic, Controlled, Covert, Overt, Participant, Non-Participant) and Design Methods (Behavioural Categories, Event Sampling, Time Sampling).

Questionnaires and Interviews in Psychology: Self-Report Techniques, Structured and Unstructured Formats, and Effective Design with Open and Closed Questions.

Correlations in Psychology: Exploring Co-Variables, Positive, Negative, and Zero Correlations, Correlation Coefficients, and Their Distinction from Experiments.

Case Studies in Psychology: In-Depth Exploration of Individuals or Groups in Non-Experimental Research.

Content, Thematic, and Discourse Analysis: Exploring Qualitative Research Methods in Psychology.

"Data Handling and Analysis: From Descriptive Statistics to Meta-Analysis"

Explore the basics of data handling and analysis in psychology, including descriptive statistics, measures of central tendency (mean, median, mode), measures of dispersion (range, variance, standard deviation), and the differences between qualitative and quantitative data. Learn how psychologists use meta-analysis to combine and interpret findings across multiple studies. Perfect for students seeking to strengthen their grasp of psychological research methods.

CONTINUOUS AND CATEGORICAL DATA

Data in psychology can be categorised as continuous or categorical (also called discrete). Continuous data refers to numerical values that can take any value within a range, such as height, weight, or reaction time. It is measured on a scale and often analysed using means or standard deviations.

Categorical data, on the other hand, involves distinct categories or groups. Examples include gender, ethnicity, or types of therapy. This data is non-numerical and is often summarised using frequencies or percentages.

Understanding the distinction is key to choosing the right statistical tests and interpreting psychological research effectively.