Learning outcomes
After studying this chapter, you should be able to:
• describe why data are needed and how data can be produced
• describe the processes and issues involved in the calculation of descriptive statistics
• describe the processes and issues involved in producing graphical and tabular displays
• describe the principles of probability
• describe how statistical inferences are reached.
Introduction
Quantitative information is everywhere, and many decisions that we make, or are made for us, are based on statistical data. For example, whether or not a drug is allowed onto the market depends on an analysis of its efficacy and safety. In addition, quantitative data are often used to persuade us to alter our behaviour, such as to vote for a particular political party or to buy a certain brand of toothpaste (Ben-Zvi & Garfield, 2004). Yet, it is common for decisions such as these to be made on incomplete data. For example, the polling of the electorate that takes place during an election campaign surveys only a small proportion of the voting population. During this time, campaign managers make daily adjustments depending on these polls and it is just too expensive and time consuming to poll all the voters. It is the study of the collection, organisation, analysis and interpretation of such data that makes up the discipline of statistics (Jones, Langrall & Mooney, 2007).
Unfortunately, the teaching of statistics often emphasises skills, procedures and computations that do not promote understanding of the collection and interpretation of data. Many adults in our society cannot think statistically about the information they are given which affects their lives (Jones, Langrall & Mooney, 2007). Therefore, this chapter emphasises the importance of encouraging students to take a holistic view of the discipline of statistics.
It has to be acknowledged that there is keen debate as to whether the discipline of statistics is a part of mathematics at all. Some writers (e.g. Moore, 1990) claim that statistics is an independent discipline that, like science, relies heavily on mathematics. Whether or not you agree with this argument, it should be appreciated that unlike mathematics, where numbers may be used in the abstract, statistics always uses numbers in a context.