Description
Module description:
Module Content
This course is designed to provide you with proficiency in using and interpreting quantitative data and statistics and will expect no prior knowledge of statistical analysis. You will be taught through a series of lectures and practical sessions, working with relevant data sets in order to get a feel for the manipulation of real data. You will have the opportunity to consider application of statistical analyses to your own research plans and to gain familiarity with the open source computing package R.
Indicative Topics
Topics may include descriptive statistics, hypothesis testing and probability distributions, non-parametric methods, univariate tests of group difference, correlation and regression analysis, and the relationship between quantitative and qualitative methods.
Learning Outcomes
Having completed the course you will:
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Be able to demonstrate critical awareness of basic data types and statistical approaches used in contemporary research
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Have an understanding of the mathematical foundations and limitations of basic statistical techniques
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Be able to demonstrate the correct selection, use, and interpretation of basic statistical techniques on a range of data sources and types
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Feel confident in identifying opportunities and limitations of mixed-methods approaches involving statistical techniques
Teaching Delivery
Sessions consist of a lecture followed by supervised and unsupervised practical exercises. The sessions integrate the use of computers throughout.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 19th August 2024.
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