Teacher
|
LAURETI Tiziana
(syllabus)
Data collection. Qualitative and quantitative variables. Univariate analysis: Distribution (frequency tables), Central tendency (mean, median, and mode), Dispersion (range, quantiles, variance, standard deviation, coefficient of variation, heterogeneity), Graphical representation (diagram, histogram and box plots), inequality measures, shape of the distribution (skewness).
Bivariate analysis: Cross-tabulations and contingency tables, Graphical representation (scatterplots), measures of dependence (chi-square, coefficient of correlation).
Introduction to Probability: sample spaces, events and sets. Probability axioms and simple properties. Interpretations of probability (classical, frequentist, subjective), conditional probability. Bayes Theorem. Random variables. Discrete probability models (Bernoulli, Binomial distribution, Poisson distribution) Continuous probability models (Normal distribution, T-Student, Chi-squared).
Statistical Inference. Samples and sampling distributions. Point estimations of parameters. Interval estimation. Hypothesis testing. Independence.
(reference books)
Barrow, M. (2009). Statistics for economics, accounting and business studies. Pearson Education.
|