ABSTRACT
This chapter introduces the mathematical and statistical concepts and calculations underlying the analysis of data. Our examples illustrating the relationship between values and their associated probabilities should provide a good base for understanding the construction of confidence intervals and hypothesis testing. The chapter extends the concept of a random variable to explaining the relationships between them through linear measures of association known as covariance and correlation. It explains how to construct confidence intervals for the arithmetic mean and the standard deviation and in doing so, introduce the reader to the t and chi-squared probability distributions. Hypothesis testing can be applied to testing the significance of relationships between random variables. The chapter explains the concept of bias and precision in estimation using the sampling distribution of sample means and showed how a point estimate may be adjusted to allow for a margin of error through the construction of a confidence interval.
