DATA ANALYSIS

Fabio MADONNA DATA ANALYSIS

0512700005
DEPARTMENT OF CHEMISTRY AND BIOLOGY "ADOLFO ZAMBELLI"
EQF6
ENVIRONMENTAL SCIENCES
2020/2021

OBBLIGATORIO
YEAR OF COURSE 2
YEAR OF DIDACTIC SYSTEM 2016
SECONDO SEMESTRE
CFUHOURSACTIVITY
432LESSONS
224EXERCISES
Objectives
THE COURSE AIMS TO INTRODUCE STUDENTS TO UNDERSTANDING THE FOLLOWING TOPICS:
• DESCRIPTIVE STATISTICS;
• THEORY OF PROBABILITY;
• ERROR ANALYSIS;
• PROBABILITY DISTRIBUTIONS
• APPLICATION OF THE MAIN STATISTICAL TESTS MOST COMMONLY USED IN SCIENTIFIC RESEARCH (IN PHYSICS, CHEMISTRY, BIOLOGICAL, ENVIRONMENTAL STUDY).
STUDENTS WILL BE TRAINED IN THE USE OF CALCULATION SHEETS, AS AN ESSENTIAL STEPS TO LEARN ONE OR MORE PROGRAMMING LANGUAGES FOR DATA ANALYSIS.
THE KNOWLEDGE ACQUIRED WILL ALLOW THE STUDENTS TO UNDERSTAND THE MOST FREQUENT METHODOLOGICAL APPLICATIONS IN SCIENTIFIC LITERATURE RELATING TO THE STUDY AND MONITORING OF THE ENVIRONMENT.
THE LESSONS WILL BE INTEGRATED BY EXERCISES WITH THE INVOLVEMENT OF STUDENTS WITH THE AIM OF INCREASING THEIR SKILLS IN THE APPLICATION OF THEORETICAL KNOWLEDGE.
AT THE END OF THE TEACHING, STUDENTS WILL BE ABLE TO IDENTIFY THE MOST APPROPRIATE STATISTICAL TOOLS TO USE IN SOLVING EXPERIMENTAL PROBLEMS, INTERPRETING THE RESULTS AND IDENTIFYING POSSIBLE SOURCES OF ERROR.
Prerequisites
BASIC MATHS, DERIVATIVES, INTEGRALS
Contents
• STATISTICAL NOMENCLATURE: POPULATION, UNITS, VARIABLES AND DISTRIBUTIONS.
• THE CONCEPT OF MEASUREMENT AND DATA ANALYSIS: DATA AND METADATA. ENVIRONMENTAL MEASUREMENTS. SAMPLING STRATEGIES.
• PROBABILITY: RANDOM EVENTS AND VARIABLES. DEFINITIONS AND PROBABILITY PROPERTIES. TOTAL PROBABILITY. CONDITIONAL PROBABILITY. THE BAYES THEOREM. AXIOMATIC DEFINITION OF PROBABILITY.
• DESCRIPTIVE STATISTICS: THE GRAPHICAL DESCRIPTION OF THE VARIABLES, FREQUENCY DISTRIBUTIONS AND HISTOGRAMS, THE CUMULATED PROBABILITY, BOX AND WHISKERS PLOT
• MEAN, MEDIAN, QUARTILES, PERCENTILES
• AVERAGE WEIGHING.
• HOW TO REPRESENT AND USE UNCERTAINTIES,
• STATISTICAL ANALYSIS OF UNCERTAINTIES
• RANDOM VARIABLES AND DISTRIBUTIONS,
• BINOMIAL, GAUSSIAN, POISSON DISTRIBUTION
• OUTLIERS AND DATA REJECTION.
• LEAST-SQUARE METHOD.
• LINEARIZATION OF NON-LINEAR MODELS
• COVARIANCE AND CORRELATION.
• STATISTICAL TESTS: Z-TEST, T-TEST, CHI-SQUARE TEST.
• USE OF CALCULATION SHEETS, BASIC PROGRAMMING ELEMENTS IN R.
Teaching Methods
THE COURSE INCLUDES 32 HOURS OF FRONTAL TEACHING AND 24 HOURS OF EXERCISES
Verification of learning
THE EXAM INCLUDES THE PERFORMANCE OF INTER-COURSE TESTS AND A FINAL ORAL TEST.
THOSE WHO DO NOT TAKE THE INTERCOURSE TESTS WILL CARRY OUT A WRITTEN TEST (WITH THE SAME METHOD OF THE INTERCOURSE TESTS) AND AN ORAL TEST.
THE FINAL TEST IS AIMED AT THE ASSESSMENT OF THE LEVEL OF KNOWLEDGE, UNDERSTANDING AND INDEPENDENCE MATURED BY THE STUDENT ON THE TOPICS COVERED IN THE PROGRAM.
THE INTERCOURSE TESTS AND THE WRITTEN TEST WILL WEIGH FOR 50% OF THE FINAL MARK.
THE INTERCOURSE AND WRITTEN TESTS WILL BE CARRIED OUT WITH THE USE OF THE PC. IT IS NOT PERMITTED TO CONSULT TEXTS OR CONNECT TO THE INTERNET, THE USE OF THE STATISTICS TABLES IS PERMITTED.
Texts
TAYLOR, JOHN R. AN INTRODUCTION TO ERROR ANALYSIS: THE STUDY OF UNCERTAINTIES IN PHYSICAL MEASUREMENTS. ISBN 13: 9780935702750.
More Information
ALL PRESENTATIONS AND TEACHING MATERIALS ARE PROVIDED ON THE " MATERIAL" PAGE IN THE "DATA ANALYSIS" GROUP, ON MICROSOFT TEAMS.
  BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2022-05-23]