Descriptive statistics
Introduction: problems of descriptive statistics and their applications in the experimental sciences.
Elements of descriptive statistics: discrete variables and continuous variables, population; character; sample; absolute frequency; relative frequency; cumulative frequency; variable; statistics; dot plot; bar graph, pie chart.
Main statistics: mode, median, quartiles, quantiles, arithmetic mean, deviation.
Statistical averages: Cauchy means; Chisini means; the arithmetic mean; geometric mean; harmonic mean; weighted arithmetic mean; their properties (proofs and applications).
Variability indexes: the range of the data; deviance; variance and standard deviation; coefficient of variation; their properties (proofs and applications).
Form of a distribution: the concept of symmetry; asymmetry; the standardized variable; Pearson index of asymmetry; Fisher asymmetry index; Kurtosis and Pearson kurtosis index.
Dependence analysis: two-variable data table; conditional distribution and independence; scatterplots; Chi-Square for contingency table; Cramer's V index; linear regression and least squares technique; association; regression coefficient and its interpretation; variance of regression and its decomposition; coefficient of determination; polynomial regression; linearization methods.
Interdependence analysis: the concept of interdependence; measure of concordance; discordance; the correlation coefficient of Bravais -Pearson and its interpretation.