Knowledge of descriptive statistics. Position and variability indices. Acquisition of the principles and the techniques of regression and correlation between variables. Knowledge of inferential statistics. Analysis of Variance.
Expected learning outcomes
Describe the phenomena by the main statistical indicators; Plan a sample surveys; Use the methodology of the analysis of variance at 1 and 2 factors; understand the results of statistical surveys.
Lesson period: Second semester
(In case of multiple editions, please check the period, as it may vary)
1 - The language of statistics. 2 - The representation of data Organization of data and graphical representations. 3 - Data descriptors Measures of central tendency (mean, median mode) Measures of dispersion or variation. 4 - Bivariate analysis of data Bivariate analysis with qualitative and quantitative data. 5 - The probability The laws of probability. 6 - Random variables and probability distributions Random variables The binomial distribution The normal distribution. 7 - Sampling distributions and confidence intervals The most common estimators Desirable properties of an estimator Distribution of sample mean, The Central Limit Theorem Confidence intervals for the mean. 8 - The hypothesis testing: fundamentals The hypothesis test Stages of a hypothesis test Two-tailed tests Test for the average. 9 - Still about inference, Test on a single population hypothesis on the average hypothesis on a single proportion. 10 - Comparing two populations Test of hypothesis on the difference between the means of two populations - With independent samples - With dependent samples. 11 - Regression Analysis The simple linear regression model The inference in the case of linear regression model Confidence intervals and prediction intervals Correlation analysis. 12 - Analysis of Variance Principles of analysis of variance Fisher F distribution test for Anova.