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Introduction to Statistical Analysis

Description:

This course provides a refresher on the foundations of statistical analysis. The emphasis is on interpreting the results of a statistical test, and being able to determine the correct test to apply. Practicals are conducted using a series of online apps, and we will not teach a particular statistical analysis package, such as R. For courses that teach R, please see the links below.

Aims:During this course you will learn about:

  • Different types of data, distributions and structure within data
  • Summary statistics for continuous and discrete data
  • Formulating a null hypothesis
  • Assumptions of one-sample and two-sample t-tests
  • Interpreting the result of a statistical test
  • Statistical tests of categorical variables
  • Non-parmetric versions of one- and two-sample tests

Objectives: After this course you should be able to:

  • State the assumptions required for a one-sample and two-sample t-test and be able to interpret the results of such a test
  • Know when to apply a paired or independent two-sample t-test
  • Assess the distribution of your data and decide if a parametric or non-parametric test is required
  • To perform simple statistical calculations using the online app
  • Understand the limitations of the tests taught within the course
  • Know when more complex statistical methods are required

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