Introduction or 'What is statistics?' -- The presentation of data -- Probability, its meaning, real and theoretical populations -- Basic properties of the normal distribution -- Some properties of sampling distributions -- Applications of normal sampling theory; significance tests -- Normal sampling theory: test for difference between several sample means, analysis of variance, design of experiments -- Normal sampling theory: estimation of 'parameters' by confidence intervals, by maximum likelihood -- The binomial distribution: laws of probability, applications of the binomial distribution, the multinomial distribution -- The Poisson, negative exponential, and rectangular distributions -- The [chi]p2s test for 'goodness of fit': test for 'association' -- Fitting lines and curves to data, least squares method -- Regression curves and lines, correlation coefficient, normal bivariate distribution -- Some distribution-independent (or 'distribution-free' or 'non-parametric') tests -- Note on sampling techniques and quality control -- Some problems of practical origin.