Abstract
<jats:p>The first part is theoretical, covering concepts related to measures of central tendency (arithmetic mean, median and ranks, mode, mid-range, harmonic, geometric, weighted, and quadratic means, and other measures of central tendency) and measures of dispersion (range, variation ratio, quartiles, variance, standard deviation), while also addressing elements such as the standard error of the mean, degrees of freedom, the coefficient of variation, and the use of the mean and standard deviation. It continues with concepts of probability (permutations, combinations, arrangements, types of probabilities, mutually exclusive events, and independent and dependent events), followed by a discussion on sampling, presenting several sampling principles and techniques. A significant portion of the theoretical material is dedicated to statistical probability distributions, including distributions for discrete variables (Bernoulli, binomial, geometric, negative binomial, Poisson, hypergeometric, discrete uniform, multinomial, and multivariate hypergeometric) and for continuous variables (continuous uniform, normal, standardized normal, multivariate normal, Student's t, Chi-square, and F), as well as an extensive treatment of various procedures for testing the assumption of univariate normality.</jats:p>