An Introduction to Quantitative Methods, first edition, employs a handy 11 chapter structure, aiding the user through the subject matter in a coherent manner. Chapter one introduces the basic concepts of quantitative methods discussing issues such as statistics, population and sample, scales of measurement and data types. Chapter two discusses frequency distribution and graphs. Chapter three gives detailed information and understanding into the measures of central tendency or location. This includes the mean, mode, median and their relationship, geometric mean, harmonic mean and weighted mean. Chapter four describes the measures of variability or dispersion focusing on range, mean deviation, mean absolute deviation, variance, standard deviation and coefficient of variation. Issues relating to distribution shapes are also discussed. Chapter five presents the definition and concepts of probability. It discusses the three main approaches as classical, empirical and subjective approaches. Rules of probability and Bayes' theorem are also covered. Chapter six covers probability distributions with emphasis on random variables, density and mass functions, Binomial, Poisson and Normal distributions, standard normal distribution, normal approximations to the binomial and sampling distribution of the mean. Chapter seven introduces the concept of point and interval estimation. Chapter eight deals with hypothesis testing. Chapter nine examines non-parametric tests and the assumptions underlying their use. Chapter ten deals with the concept of correlation and linear regression analysis. Chapter eleven introduces the idea of generalized linear models with emphasis on the logistic and Poisson regression models. Application examples of various statistical techniques are demonstrated using the R programming language in chapters 2 to 11. The book is a practical text that is comprehensive and suitable for teaching, self-study and reference.