41301 - Statistical Inference

Academic Year 2017/2018

  • Docente: Paola Monari
  • Credits: 10
  • SSD: SECS-S/01
  • Language: Italian
  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: First cycle degree programme (L) in Statistical Sciences (cod. 8873)

Learning outcomes

By the end of the course, the student should know the main topics in statistical inference. Specifically, the student should be able to: 1- derive an estimator and its properties; 2- use estimating methods; 3- define and verify parametric and non parametric statistical hypothesis in simple contexts; 4- build confidence intervals.

Course contents

  • Random sampling, sample space and random variables
  • Probability density functions of statistics
  • The likelihood concept
  • Point estimation: methods for finding and methods for evaluating estimators. Maximum likelihood and least squares estimates
  • Interval estimation
  • Testing statistical hypotheses: Fisher significance theory and Neyman-Pearson theory
  • Test-statistics of comparing means, proportions, variances, distributions.

    • Readings/Bibliography

    Teacher's notes

    Text book


    G. Cicchitelli, Statistica: principi e metodi, Pearson, Milano, 2012

    A. Montanari, P. Agati, DG.Calo, Statistica con esercizi commentati e risolti, OPEN, Masson, 1998

    Teaching methods

    Classroom

    Lab classes

    Assessment methods

    Written examen  including 5-6 numerical and therical exercises

    Oral examen about all the topics of the program with particular attention on the results of written examen 

    Teaching tools

    Teacher's notes

    Text books

    Lab classes

     

    Office hours

    See the website of Paola Monari