Includes bibliographical references and index.

Data types -- Data presentation -- Descriptive statistics for interval scale data -- The normal distribution -- Sampling from populations. the standard error of the mean -- 95% confidence interval for the mean and data transformation -- The two-sample t-test (1): introducing hypothesis tests -- The two-sample t-test (2): the dreaded P value -- The two-sample t-test (3): false negatives, power and necessary sample sizes -- The two-sample t-test (4): statistical significance, practical significance and equivalence -- The two-sample t-test (5): one-sided testing -- What does a statistically significant result really tell us? -- The paired t-test: comparing two related sets of measurements -- Analyses of variance: going beyond t-tests -- Correlation and regression relationships between measured values -- Analysis of covariance -- Describing categorised data and the goodness of fit chi-square test -- Contingency chi-square, Fisher's and McNemar's tests -- Relative risk, odds ratio and number needed to treat -- Logistic regression -- Ordinal and non-normally distributed data. transformations and non-parametric tests -- Measures of agreement -- Survival analysis -- Multiple testing -- Questionnaires.