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(objectives)
THIS COURSE IS AIMED TO PROVIDE STATISTICAL, MATHEMATICAL AND COMPUTER COMPETENCES NEEDED TO COLLECT EXPERIMENTAL DATA, SYNTHESIZING THE QUANTITATIVE INFORMATION, COMPARE THE RESULTS AND MAKE PREVISIONS EVALUATING THE RISK OF FAILURE. PRACTICALS WILL MAINLY ADDRESSED TO BIOLOGICAL PHENOMENA ALSO CONCERNING DAY-LIFE ASPECTS
LESSONS (9 CFU) AND PRACTICALS (3 CFU) DESCRIBE:
- THE PRINCIPAL METHODS FOR STATISTICAL SYNTHESIS: INDEXES, HISTOGRAMS, SCATTER PLOTS (XY PLOTS);
- THE STATISTICAL LAWS THAT GOVERN THE EXPERIMENTAL OBSERVATIONS AND CAUSE THE UNCERTAINTIES ASSOCIATED WITH MEASUREMENTS AND DATA PROCESSING.
- BASIC KNOWLEDGE ABOUT PROBABILITY AND PROBABILITY DISTRIBUTION FUNCTIONS, NAMELY: BINOMIAL, POISSON, UNIFORM, GAUSS.
- USE OF “REJECTION TESTS” TO UNDERSTAND AND COMPARE THE EXPERIMENTAL RESULTS.
- USE OF THE BAYES THEOREM, SPECIALLY TO UNDERSTAND THE DIAGNOSTIC TESTS.
THE COURSE WILL PROVIDE THE FOLLOWING ABILITIES
- TO USE STATISTICAL METHODS TO SYNTHESIZE THE QUANTITATIVE INFORMATION IN AN EXPERIMENTAL DATA SET.
- TO EVALUATE THE UNCERTAINTY ON DIRECT AND INDIRECT MEASUREMENTS
- TO EVALUATE THE EXPERIMENTAL RESULTS APPLYING STATISTICAL TESTS
- TO APPLY THE BAYES THEOREM IN ORDER TO QUANTITATIVELY UNDERSTAND THE PROBABILITY OF A CAUSE
ACTIVITIES WILL USE BASIC SOFTWARE (SPREADSHEETS) FOR STATISTICAL DATA ANALYSIS
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Università Roma Tre