Introduction to Inferential Statistics
To provide the main ideas and techniques of inferential statistics in order to estimate , under a probability model, the errors involved when inferring from a sample to a population.
Combination of traditionals lectures (40 hours) and exercises sessions (24 hours)
Sampling and estimation. Populations, samples and point estimators. Properties of point estimators. Some point estimators and their probability distributions. Confidence intervals. Hypothesis tests. How to define and use a statistical test (hypotheses, errors of the first and second type, critical region). Parametric tests. Tests of large samples. Comparative tests. Some non-parametric tests.
Statistics and tests for linear multiple models. Confidence intervals for the parameters, estimated values and residuals, "studentized" residuals, test of hypotheses on single coefficients and on subsets of coefficients. Forecast.
Casella G., Berger R.L. (2002), Statistical Inference, Pacific Grove, CA: Duxbury
Mood A.M., Graybill F.A., Boes D.C. (1991), Introduction to the Theory of Statistics, McGraw-Hill, Inc.
Rogantin M.P. (2004), Introduzione alla statistica, C.L.U.T., Torino
Ross S.M. (2003), Probabilità e statistica per l’ingegneria e le scienze, Apogeo, Milano
Wasserman L. (2005), All of Statistics, Springer
Ricevimento: On appointement
Ricevimento: By appointment arranged by email with Luca Oneto luca.oneto@unige.it and Fabrizio Malfanti <fabrizio.malfanti@intelligrate.it> For organizational issues contact by email Eva Riccomagno <riccomagno@dima.unige.it>
ELDA GUALA (President)
EVA RICCOMAGNO (President)
IVANO GIANLUIGI REPETTO
EMANUELA SASSO
February 20, 2017
Oral and written exam
