Overview
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Learning activities
Learning outcomes
Use basic statistics to solve problems in the social sciences, with an emphasis on interpretation of
results in the field of education,
Describe 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
Distinguish between an experiment, an observational study, a correlational study and other such data
gathering procedures (e.g., statistical surveys of a population vs. survey measurement tool)
Develop and formalise an understanding of the fundamental ideas of statistical measurement (e.g.,
centre, variability, distribution, association, causation, confidence, significance, power, etc.)
Use various representational forms (graphical, numerical, etc.) to communicate ideas, in particular, to
graphically represent various attributes of distributions using objects of descriptive statistics (e.g.,
histograms, frequency tables, scatter plots, etc.)
Communicate research findings with clarity using an appropriate combination of text, symbols &
pictures
Apply and interpret (i.e., infer information from) a variety of inferential statistical techniques (e.g., pvalues, t-tests, ANOVAs, correlation coefficients, linear regression, etc.)
Use software appropriately for analysis and presentation of statistical data (SPSS)
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,
and
Appreciate and adhere to ethical guidelines for conducting research with human subjects, and for
statistical practice.
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 association, sampling and sample size estimation, and simple linear regression. SPSS will be the software to analyse data in this unit