a) Introduction to Statistical Inference
b) Introduction to sampling theory
a) To provide an introduction to concepts and techniques from statistical inference which are fundamental to provide a probabilistic measure of the error committed when estimation is based on a sample from a large population.
b) To deal with theoretical and practical elements of the design, analysis and inference of survey data obtained by probabilistic sampling.
At the end of the course students will be able:
Part a:
Mathematical Analysis: function of a variable, integral calculus. Algebra: elements of vector and matrix algebra. Probability: elementary probability
Part b:
Probability and Statistical Inference
a) Combination of traditionals lectures (40 hours) and exercises sessions (24 hours).
b) Combination of traditionals lectures and lab sessions with the software R (24 hours).
a)
Estimation. 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. Large sample tests. 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.
b)
Statistical sampling from ea finite polulation. Simple random sampling with and without replacement. Stratified sampling. proportional allocation and optimal allocation. Statistical estimators of means and their variances.
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.
Ross S.M. (2003), Probabilità e statistica per l’ingegneria e le scienze, Apogeo, Milano
Wasserman L. (2005), All of Statistics, Springer
Handouts on aulaweb
Vic Barnett Sample Survey, Principle and methods, Third Edition, John Wiley & Sons, Ltd, 2002
William Cochran, Sampling Techniques, John Wiley & Sons, 1977
Sharon L. Lohr, Sampling: Design and Analysis. Second Edition, Brooks/Cole, 2010
Ricevimento: Write an email to guala@dima.unige.it to arrange an appointment
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)
MARTA NAI RUSCONE
EMANUELA SASSO
The class will start according to the academic calendar.
The exam consists of a written and a oral part.
During the semester there will be three (not evaluated) mock exams. The lecture after each mock exam will start with a 15-minute closed-book written examination.
The first two closed-book examinations are evaluated at most 3 marks and the third one at most 2 marks, for a maximum total of 8 marks.
For the students who attempted all of the three closed-book examinations, the final written examination consists of a 2-hour open book examination, which is evaluated at most 23 marks to be added to the marks of the three on-course closed-book examinations.
For the students who did not attempt the three closed-book examinations, the final written examination consists of two parts: a 45-minute closed-book examination and a 2-hour open-book examination. The closed-book part is evaluated at most 8 points, the open-book part is evaluated at most 23 points.
Written exam with multiple choice and open questions. a group project on a topic agreed with the teachers. discussion of the report and written test.
The on-course examination and the closed-book part of the final examination test the comprehension of the theory.
The two-hour open-book examination evaluates the acquired ability to apply the theoretical ideas for simple data analysis.
Main points of evaluation are the level of acquisition of the learning objectives and the ability to communicate in a written report the data analyzes carried out during the course.
