Learning objectives
The course and the exam require the ability to input data and to explain results (output) of different tests; when two or more tests are available, how to choose the most robust
Course unit content
The course is for students who know basic statistics on parametric methods, and bioinformatics. The programme will add knowledge and applications on some concepts and data analysis, through application of the software PAST and G-Power.
Testing for goodness of fit; contingency tables: chi-square, log-lihelihhod ratio, Kolmogorov-Smirmov
One-sample and two-sample methods parametric and nonparametric
Statistical hypothesis, sample size, detectable difference, power in tests concerning the means and medians.
Confidence limits for the population mean and median.
Testing for difference between variances.
Multisample hypotheses and the analysis of variances parametric and nonparametric; multiple comparisons parametric and nonparametric, multiple contrasts parametric and nonparametric
Data transformations
Multiway factorial analysis of variances
Nested (hierarchical) analysis of variances
Simple linear regression parametric and nonparametric
Simple linear correlation parametric and nonparametric
Bibliography
Soliani Lamberto (2008) I test non parametrici più citati nelle discipline scientifiche, UNI.NOVA, Parma. (pagg. VII + 828); ISBN: 978-88-6319-022-9; www.uninova.net
Lamberto Soliani (2008) Statistica applicata. UNI.NOVA, Parma. (pagg. X + 694);
ISBN:978-88-6319-041-0; www.uninova.net
UNINOVA Parma, gruppo Pegaso Libreria;Via Cavedani, 7
- Sokal R. R. and F. J. Rohlf (1995). Biometry, 3rd Edition. W. H. Freeman & Co., New York.
- Zar Jerrold (2010). Biostatistical Analysis, Fifth Edition. Pearson Education International
- EPA 530/R-09-007, March 2009, Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities. Unified Guidance, Environmental Protection Agency, United States (pp. 888)
- EM 1110-1-4014, 31 Jan 2008, Environmental Quality - ENVIRONMENTAL STATISTICS
