Learning outcomes
The course of Statistic Methods for the Social Sciences: Inference, places itself after the course of of Statistic Methods for the Social Sciences :descriptive analysis (and in the second year of course). In fact it wants to deepen the statistic competence already matured till now by the student with descriptive statistics and possibly to allow him to gather some applications. Using himself/herself notions already acquired in precedence, the student will enter into the world of the probability in gradual way and progressively sharpening the previews knowledge. To face such thematic rather complex, we will used only the tools of elementary mathematical analysis, skipping limits, differential calculus, integral ecc that they overcome the least program of the senior high schools. Some concepts can need only intuitions, for others verifications will be developed, but in the big part of the cases the results gotten at the end of these two teachings courses are substantially equivalent to those of a fundamental course of statistic.
-Random samples, tables of random numbers, errors of survey in the sample investigations .
-Some premises of probabilities.
-The probability according to the different theories.
-Discreet casual variables: Hyper-geometrics, discreet uniform, Poisson.
-Some important distributions: the normal distribution, the binomial distribution, the distribution the average's sample.
-Degree of confidence on the statistic inference, the appraisers' ownership, Bernoulli sampling, punctual evaluation; distribution of the mean.
-Interval of confidence for an average.
-The dimension of the champion.
-Test of hypothesis in the case of a sample.
-Measure of dependence in the case of two jointed variables: definition of statistic independence.
Texts for the examination:
Delvecchio Francesco, Statistica per la ricerca sociale, Cacucci Editore, Bari, 1987.
