Students should be able to apply statistical description methods, including both univariate and bivariate analysis, in common engineering applications.

Univariates Descriptive Statistics Review Exploratory data analysis. Discrete and continuous data; Frequency tables; Measures of location, variability, skewness and kurtosis; Graphs: pie, bar, histogram, stem-and-lead and boxplots; Outliers.

Bivariate Statistical: Simple linear regression and data plots. Least squares estimators; Correlations coefficients: Pearson, Spearman and bi-serial point; Coefficient of association: Phi and Cramer.

Probability Calculus : Sample space, events. Event probability; Additives rules. Conditional probability. Multiplicative rules; Bayes’ rule and Bayes’ theorem.

Random variables and probability distributions : Some discrete distributions: binomial e poisson; Some continuous distributions: normal, chi-squared and t-student.


Inferential Statistics :Point and interval estimation for unknown population parameter; Confidence intervals for population mean and proportion. Hypothesis Tests.