ABSTRACT
Understanding statistics can be very complicated, so this chapter uses the simple track of a bouncing ball as an example. Average versus mean and root mean square (RMS) tracks of a ball are explained, after which the chapter explains how numbers can be filtered and smoothed – a method often used to predict the travel path of a ball. Curve fitting, regression, and least squares equations are discussed with their applications. The more complex conical equations are referred to along with accuracy, and the probability of a prediction being correct. It finishes with a simple explanation of Bayes’ Theorem for prediction. ‘Further Reading’ is then offered, including an exercise on predicting property prices – always a useful tool when buying or selling an apartment or house.
