Introduction to statistics

Welcome to the Introduction to statistics module. This module introduces you to some of the concepts required to interpret statistics published in journal articles and other literature, as well as to a range of ways you can analyse your own data using statistics. (Please note that if you are not doing either of these things, but instead would like an understanding of how to interpret a few common graphs and tables and calculate a few key values, you may find sections of the Statistics and probability page of the Numeracy fundamentals module more suitable instead.)

You may wish to work your way through the entirety of the module in the order provided, or you may wish to jump to certain pages or sections of the module according to need or preference. In particular, if you are just looking to learn about how to interpret published statistics you may only want to work through the first page of the module, or if you are interested in analysing your own data using statistics you may wish to start from the second page of the module. Additionally, if you are interested in finding out how to conduct the statistical tests detailed in this module in the statistical software SPSS, you might also like to check out the Introduction to SPSS module (note that all graphs and tables included in this module have been created using SPSS, with the exception of the tables in the first page which have been taken from journal articles).

Before you get started, you may also like to have a read of this How to get confident with statistics post on The Research Whisperer blog. It provides some excellent, practical advice on how to boost your confidence when it comes to statistics, and will hopefully assist you in making the most of this module.

Your feedback on this module is very welcome and can be provided at any time on the feedback page, or alternatively for any questions about the module please contact Library-UniSkills@curtin.edu.au

What you will learn

  • How to interpret and critically evaluate published statistics, including how to differentiate between descriptive and inferential statistics and statistical and practical significance as required (skip to Interpreting statistics).
  • What data and variables are, and how to distinguish between categorical and continuous data and independent and dependent variables (skip to Data and variable types).
  • What descriptive statistics are, and how to display data and calculate descriptive statistics for one and two variables at a time for both categorical and continuous data (skip to Descriptive statistics).
  • What the normal and sampling distributions are, and how to know whether a variable is normally distributed or the sample size is large enough that the sampling distribution of the mean approximates a normal distribution (skip to The normal distribution).
  • What inferential statistics are, including how to distinguish between estimation and hypothesis testing, how to calculate confidence intervals and how to interpret these and p values (skip to Inferential statistics).
  • How to compare means of continuous variables using t-tests or one-way ANOVA (skip to Comparing means).
  • How to test for relationships between pairs of variables using the Chi-square test of independence or Pearson’s correlation (skip to Looking for relationships).