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Postgraduate course in statistics and research methods.
PSYC460 is a second-level course in statistics and data analysis, with applications for Psychology. It is assumed that you have taken an introductory course such as PSYC206, although some revision is provided. The model comparison framework for understanding inferential statistics is described, and then we spend several classes on multiple regression (including partial and semi-partial correlations; variable selection methods, mediation/moderation, and the General Linear Model), examples of generalized linear models (logistic regression, survival analysis), and mixed-model analysis of repeated-measures data. Other topics include psychometrics, exploratory and confirmatory factor analysis, path analysis, and structural equation modeling.
Understand the model comparison approach to inferential statistics, and how modelling concepts underpin data analysis. Develop research literacy in statistics based on general/generalized linear models, including multiple regression, logistic regression, survival analysis and mixed-model analysis.Develop experience with exploratory and confirmatory factor analysis, and structural equation modelling.Gain expertise in use of different software packages (Statstica, SPSS, Excel) for data analysis. Enhance understanding of the links between research practice and statistics methodology.
Subject to approval of the Head of School
Students must attend one activity from each section.
It is the policy for this course that late work is not accepted.
Field, Andy P;
Discovering statistics using IBM SPSS statistics
SAGE Publications, 2018.
Tabachnick, Barbara G. , Fidell, Linda S;
Using multivariate statistics
Pearson Education, 2013.
There are no required textbooks for this course. Assigned readings for lectures/labs will be provided online via LEARN.
Domestic fee $1,079.00
International Postgraduate fees
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
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departments and faculties