Learning objectives
The module aims at illustrating how to organize and analyze a set of real data and introducing the main concepts of statistical reasoning in both descriptive and inductive logic fields.
Together with statistical inference, elements of probability calculus and random variables theory will be introduced to support validation.
Special attention is given to the application of methodologies taught during the module using the Excel® software.
Prerequisites
Basic knowledge of Spreadsheet software is a plus, but not mandatory.
Course unit content
With the "COMPUTER SCIENCE AND STATISTICS LABORATORY" students will gain skills in the statistics field that will be helpful in their professional career to solve either simple or complex problems.
In addition effective and consolidated software will be taught as well, such as Excel®, to help with the creation and application of most effective algorithms.
Full programme
Purposes of the statistical methods;
The sample;
The types of variables;
Histogram of frequencies and probability distribution;
Skewness, kurtosis;
Average and Median;
Dispersion parameters;
Degrees of freedom;
Standardized normal distribution;
Sources of variability and sampling;
Variability of the mean: standard error;
Hypotheses and statistical tests;
Student's t test;
t distribution;
Independent samples and paired samples;
Confidence limits of the average;
Analysis of variance;
The multiple comparisons;
The criterion of Bonferroni;
Test Student-Newman-Keuls;
Chi-square;
Goodness-of-fit test;
Test of symmetry;
2x2 table;
mxn table;
The continuity correction;
Fisher's exact test;
McNemar test;
Binomial distribution;
Standard deviation of a proportion;
Poisson distribution;
Statistical non-parametric;
Correlation of Kendall;
Spearman correlation;
Mann-Whitney test;
Wilcoxon test;
Kruskal-Wallis test;
Friedman test;
Rregression;
Requirements of the dependent variable;
Slope and intercept, parameter estimates, standard errors, and test significance.
Bibliography
A. M. Paganoni, L. Pontiggia
Laboratorio di Statistica con Excel
Ed. Pearson Education
ISBN: 978-88-7192-334-5
F. P. Borazzo, P. Perchinunno
Analisi Statistiche con Excel
Ed. Pearson Education
ISBN: 978-88-7192-333-8
E. Belluco
Excel per la Statistica
Ed. Franco Angeli
ISBN: 88-464-6997-6
M. R. Middleton
Analisi Statistica con Excel
Ed. Apogeo
ISBN: 88-503-2475-8
E. Battistini
Probabilità e Statistica: un approccio interattivo con Excel
Ed. Mcgraw-Hill
ISBN: 88-386-6163-4
Two handouts in PDF format prepared by the Teacher:
Laboratorio Informatico di Statistica
Manualetto di Statistica
Teaching materials (XLS file) provided at the beginning of the module to support the curriculum.
Teaching methods
The module will be taught using interactive teaching methods, as these are the foundations of the "COMPUTER SCIENCE AND STATISTICS LABORATORY".
Students will be involved by participating during all learning and in-depth analysis sessions.
Following a step-by-step approach all contents, ranging from the formal aspect of formula or statistic model, described in the books will be translated into algorithms and visualizations based on the data context.
Readings of scientific articles of interest will be done as well, as to highlight the importance of presenting, describing and inferring data for the scientific community.
The class will be guided throughout the creation of a conference presentation or a conference poster or a scientific article.
Assessment methods and criteria
Learning and preparation level are verified with a computer test using Excel® software.
The test will be open books.
Every student will receive a working file (DATI.XLS) with the data set to use and an handout that lists all exercises to be developed on these data.
All module topics will be included in the test.
During the module several tests will take place, similar to the final test but without grade, and useful to reveal any gap.
The grade of the test will be weighted on the overall class performance.
The final grade will be calculated as a weighted average of all the modules belonging to the course.
Other information
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2030 agenda goals for sustainable development
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