This course concerns statistical analysis and design for experiments in Psychology to the level required for British Psychological Society graduate membership.
Course Objectives
1. To impart basic statistical skills for the analysis of data obtained in psychological experiments.
2. To teach the key characteristics of experimental design.
3. To develop statistical skills using computer packages.
4. To develop report writing skills.
Curriculum organisation and delivery
The course will be taught across a whole academic year using lectures and practical classes involving computers. It will start from an elementary level and develop quickly to advanced statistics based on the general linear model used in analysis of variance. Students will carry out a personal experimental project that will be discussed in class and in individual supervision.
Module outline
Lecture 1 Why You Need Science
Lecture 2 Reporting Research, Variables, and Measurement Algebra Clinic
Lecture 3 Summarising Data Using SPSS/Excel
Lecture 4 Fitting Models (CentralTendency) Using SPSS/Excel
Lecture 5 Presenting Data
Lecture 6 Z-Scores
Lecture 7 7 Probability
Lecture 8 Inferential Statistics Robust Estimation
Lecture 9 Hypothesis Testing Drop-in
Lecture 10 Modern Approaches to Theory Testing
Lecture 11Assumptions
Lecture 12 Relationships
Lecture 13 Relationships
Lecture 14 General Linear Model
Lecture 15 Comparing Two Means
Lecture 16 Introduction to Empirical Study
Lecture 17 Comparing Several means
Lecture 18 Factorial Designs
Lecture 19 Factorial Designs
Lecture 20 Finalising of Empirical
Course Objectives
1. To impart basic statistical skills for the analysis of data obtained in psychological experiments.
2. To teach the key characteristics of experimental design.
3. To develop statistical skills using computer packages.
4. To develop report writing skills.
Curriculum organisation and delivery
The course will be taught across a whole academic year using lectures and practical classes involving computers. It will start from an elementary level and develop quickly to advanced statistics based on the general linear model used in analysis of variance. Students will carry out a personal experimental project that will be discussed in class and in individual supervision.
Module outline
Lecture 1 Why You Need Science
Lecture 2 Reporting Research, Variables, and Measurement Algebra Clinic
Lecture 3 Summarising Data Using SPSS/Excel
Lecture 4 Fitting Models (CentralTendency) Using SPSS/Excel
Lecture 5 Presenting Data
Lecture 6 Z-Scores
Lecture 7 7 Probability
Lecture 8 Inferential Statistics Robust Estimation
Lecture 9 Hypothesis Testing Drop-in
Lecture 10 Modern Approaches to Theory Testing
Lecture 11Assumptions
Lecture 12 Relationships
Lecture 13 Relationships
Lecture 14 General Linear Model
Lecture 15 Comparing Two Means
Lecture 16 Introduction to Empirical Study
Lecture 17 Comparing Several means
Lecture 18 Factorial Designs
Lecture 19 Factorial Designs
Lecture 20 Finalising of Empirical