Overview
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Learning activities
Learning outcomes
Engage basic statistics to solve problems in the social sciences, with an emphasis on interpretation of results in the field of education
Evaluate the nature and attributes of data, samples and populations with a working understanding of both levels of measurement and the benefits and limitations of quantitative educational data and associated (univariate) statistical procedures.
Develop and formalize an understanding of the fundamental ideas of statistical measurement (e.g., centre, variability, distribution, association, causation, confidence, significance, power, etc.)
Create various forms (graphical, numeric, etc.) to communicate ideas, in particular, graphically represent various attributes of distributions using objects of descriptive statistics (e.g., histograms, frequency tables, scatter plots, etc.)
Apply and interpret (i.e., infer information from) a variety of inferential statistical techniques (e.g., pvalues, t-tests, ANOVAs, correlation coefficients, etc.)
Apply (univariate) statistical analyses for addressing educational research questions, as well as appropriate interpretation of key statistical output from the varied types of statistical analyses learned
Assessments
Additional information
This course introduces the basic concepts of data analysis and statistical computing, both increasingly used in education and the social sciences. The emphasis is on the practical application of quantitative reasoning to analyse data. The goal is to provide students pragmatic tools for assessing statistical claims and conducting their own basic statistical analyses. Topics covered include basic descriptive measures, measures of mean differences, and measures of association. SPSS will be the software to analyse data in this unit.