ABSTRACT
Route map
This chapter brings together everything you've learnt so far to try to explain how we use statistics to test hypotheses. The first step is to see whether summaries of our data (like the mean) are representative of our population and we can do this using the standard error and confidence intervals. We then look at the rationale behind fitting statistical models to test hypotheses. You will discover that the experimental and null hypothesis can be conceptualised in terms of a statistical model that is fitted to our data. The exact model depends on what data you have and what your hypotheses are, but in general terms every model throws out a statistic with known properties. Based on these properties, we can work out whether a value as large as the one we have would be likely if the null hypothesis is true. The final part of the chapter is spent giving you a brief overview of a range of statistical models and giving examples of when they should be used.
