PROBABILITY
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Random experiments. Axiomatic definition of probability. Addition rule. Conditional probability. Total probabilities and Bayes' theorem. Independence of events. Assignment of probabilities. Applications: diagnostic test, relative risk and odds ratio. |
MAIN DISTRIBUTIONS
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Discrete and continuous random variables. Mean and variance. Main discrete and continuous distributions.
Binomial and multinomial models. Other discrete models: hypergeometric, Poisson, negative binomial.
Continuos models: Normal, log-normal, exponential, chi-square, t-student, F Fisher-Snedecor. |
| INTRODUCTION TO HYPOTHESIS TESTS. FREQUENCY TABLES: MEASURES AND TESTS |
Introduction to hypothesis testing: type I error, type II error, significance level and p-value. Parametric and non-parametric statistical techniques. Tests for the mean and for the variance of a normal population. Confidence intervals.
Frequency tables. Measures of association in frequency tables: nominal and ordinal variables. Prediction and concordance.
Goodness-of-fit tests. Proportions, chi-square test.
Independence and homogeneity tests. Normality test.
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| INFERENCE TECHNIQUES TO COMPARE GROUPS |
Comparisons between 2 groups. F test to compare variances. Student's t-test to compare means. Comparisons of more than 2 groups. ANOVA and multiple comparisons tests. Homogeneity of variances. Model hypothesis testing and alternative nonparametric techniques.
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