ADVANCED STATISTICS AND DATA ANALYSIS

Description

This module builds on knowledge gained in year 1 modules PSY1020 and PSY1032. In particular, it reflects on what you previously learnt on ANOVAs, regression, and correlation, before moving on to more complex versions of these statistical analysis. For example, you will learn how to conduct mixed ANOVAs rather than simple one-way ANOVAs and build on your understanding of a simple regression to conduct advanced multiple and logistic regressions. This will extend your portfolio of statistical analyses, enabling greater flexibility in the application of your skills to real world situations, thus enhancing your employability skillset. Classes each week are structured around a statistical analysis, exploring its theoretical and mathematical basis, via research examples. How to conduct and correctly report each analysis will also be examined. In class activities and weekly workshops, offer a practical component. Predominantly this uses the digital software Jamovi, in a supportive environment with lecturers and teaching assistants. Indicative topic areas are: Revision and introduction of statistical concepts, methods, and key topics Advanced ANOVA-related techniques Simple and multiple regression techniques Logistic regression Scale Development Mediation and Moderation Develop students' ability to understand the theoretical and mathematical basis of advanced statistical procedures. Strengthen students' decision-making for choosing the appropriate advanced statistical procedure for analysing experimental and observational data, with knowledge of the assumptions and limitations of each procedure. Advance students' skillset in conducting univariate and multivariate statistical analysis. Progress students' ability to conduct advanced statistical procedures using digital tools such as Jamovi and interpret results. Progress students' skills in utilising the correct formats for presenting data and results. Develop skills in collaboratively solving research statistical questions. Attributes Developed 001 Recognise when advanced statistical procedures are appropriate given the conditions and test assumptions. KCPT 002 Know which statistical analysis should be conducted for a given research problem and its data set. KCPT 003 Run univariate and multivariate analyses in Jamovi and understand how to handle large data sets and its output. KPT 004 Evaluate the assumptions, robustness, power, strengths, and limitations for each statistical procedure covered. KC 005 Interpret and report the results of advanced statistical analyses appropriately. KCPT