Please find links to key chapters from this area - Statistics, Descriptive and Applications, of the course below. In addition, here is a growing collection of practice questions for you to use as a reviw exercise for the whole unit. Currently there are 5 exam style questions worth 38 marks and should be completed in about 40 minutes, before looking at the solutions.
Statistics are so powerful because it allows us to create meaning from data. In this chapter we will learn the differences between types of data, how to choose useful samples, and how to recognise outliers in data.
This topic is all about these two related tools for helping us look at how a data set is spread out. Learn about filling in cumulative frequency tables, plotting the corresponding curves and using the curves to draw box plots and answer questions...
Measures of central tendency, such as the mean, median and mode, are very useful ways of respresenting large amounts of data with just one value. They can be very useful in forming conclusions about data, but they can also misrepresent data and hide infor
This topic is all about looking for relationships between variables. Does life expectancy depend on GDP? By collecting 2 variables about the things we survey we can use scattergraphs to represent the data and then look for correlation and models that we ca
Random variables are a set of possible outcomes from a random experiment. They can either be discrete or continuous. In this chapter we will find out more about discrete random variables, how they can be represented, displayed and analysed.
The normal distribution is a fascinating, naturally occurring phenomenon that has very relevant applications to understanding the world around us. When a data set is normally distributed it has some key properties that allow us to make predictions about th
Description of the concept... The following is a series of slides and videos that will help you understand, learn about and review this sub-topic. Keep track of your progress and practice the exam questions on this ACTIVITY LINK This first section...
The chi squared independence tests is a widely used technique for looking for a relationship between variables that are categorical. We can use a scatter graph to look for a relationship between GDP and life expectancy, but what about GDP and...