Experimental data are analysed statistically to allow researchers to draw conclusions from a limited set of measurements. The hard fact is that researchers can never be certain that measurements from a sample will exactly reflect the properties of the entire group of possible candidates available to be studied (although using a sample is often the only practical thing to do). If researchers have taken care to obtain a truly random or a representative sample from a large number of possible individuals, they can use this unbiased sample to judge the possibility that their observations support a particular hypothesis. Statistical analysis allows the strength of this possibility to be estimated. As an example, the authors shall explain the principles of statistical inference in a simple example involving probability, the bedrock of statistical analysis. The authors hope that the example will be sufficiently concrete to allow insight into some of the concepts, such as significance, effect size, and power. (Contains 2 figures.)