Statistical Analysis
Cod: 21008
Department: DCET
ECTS: 6
Scientific area: Mathematics
Total working hours: 156
Total contact time: 26
In this course we study the basic concepts of random variables, distribution laws for discrete and continuous variables, and classical statistical inference, with a view to applications in management.
Probability distributions
Statistical Inference
Hypothesis Testing
At the end of this course, students should be able to define and implement the most appropriate probability models for problems that are proposed. Similarly, they should be able to identify and use the classical methods of statistical inference, including methods of estimating from sample data unknown parameters of populations. Are studied parametric and nonparametric tests for two or more (brief reference) samples and tests of association. The studied methods could be used as a tool for decision support in management problems.
• The usefulness of statistics in various areas, particularly in management and economics.
Distinction between Descriptive Statistics and Statistical Inference.
Review of the Fundamentals of Probability Theory. Function of Probability / Density and Distribution Function of discrete and continuous random variables.
Distribution laws. Discrete variables: Bernoulli, Binomial, Poisson, Hypergeometric, Geometric. Continuous variables: Uniform, Normal, Exponential, Chi-square and Student t. Approximations of sums of random variables. Central Limit Theorem.
Estimation of parameters. Confidence Intervals. Parametric and nonparametric tests for one, two and k populations (t tests), Reference to ANOVA and nonparametric alternatives). Chi-square test.