Learning outcomes of the course unit
On accountof the growing use of statistical techniques as important support for whatever kindof scientific study, the course provides basic knowledge of statisticalmethods, focusing on the most common techniques in the biological field.
The purposeis firstly to make students aware of the importance of statistics for a correctinterpretation of experimental data in order to make it valuable from ascientific point of view and to make comparisons with other studies possible. Along with preliminary concepts of descriptivestatistics and basic principles of the theory of probabilities, the course willprovide some elements of inferential statistics through which students willlearn how to use correctly some of the most common parametric tests.
The course requiresknowledge of basic mathematics principles with some computational elements.
Course contents summary
1-Introduction to the various fields of statistics. Types of scales andmeasurements. Descriptive statistics for univariate distributions. Tables andgraphs. Absolute and relative frequencies. Measures of central tendencyand dispersion.
2- Introduction to the theoryof probability. Some theoric distributions:binomial, poisson, and normal distribution.
3- Rates and probabilities. The chi-square distribution. Comparison between observed andexpected frequencies: the goodness-of-fit test. Contingency tables and theindependence test for 2x2 and MxN tables.
4- Inferential statistics and hypothesis testing: the logic of the statisticaltest. Type I and II errors.
5- The Student’s-t distribution. One-sample t-test. Two-sample t-testfor paired and unpaired samples. Confidence interval of a mean and of a variance.
6- Analysis of variance for the comparison of means: One-way ANOVA. The F distribution.Requirements for ANOVA: the homoschedasticity test. Data transformation. Post-hoctests: the Bonferroni multiple-comparison test.
7- Two-way ANOVA. The concept of interaction among variables. Graphicrepresentation.
8- Descriptivestatistics for bivariate distributions. Simple Linear Regression: estimation ofthe parameters, their statistical significance and confidence interval. Regressionwith repeated data. The analysis of correlation and partial correlation.
Soliani L., "Statistica applicata". UNI.NOVA, Parma.
Camussi, F. Möller, E. Ottaviano, M. Sari Gorla,“Metodi statistici per la sperimentazione biologica”. Zanichelli, Bologna.
The course will compriseboth lessons of about two hours each and practical exercitations on statisticalissues.
An oral exam willconclude the course. However, during the semester one or two optional written testswill be supplied to students. If passed, the final exam will not concern thepart(s) of the course program included in the written tests.