BIOMEDICAL LABORATORY TECHNIQUES | University of Parma

Professor: Giuseppe PEDRAZZI
Academic discipline: Statistica per la ricerca sperimentale e tecnologica (SECS-S/02)
Field: Scienze interdisciplinari
Type of training activity: Characterising

16 hours
of face-to-face activities

2 credits

hub: -

course unit
in - - -

lectures timetable unavailable

exam calls

Integrated course unit module: PHYSICS

Learning objectives

Introduce the student to the logic of statistical thinking and its application to practical problems.

Prerequisites

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Course unit content

Review of general principles of statistical inference. Sampling distribution. Hypotheses and hypothesis tests. I and II type errors. Power of a test and operating curve. Parametric test : Student t-test, an overview of analysis of variance. Non-parametric test: Wilcoxon test, Mann-Whitney test, Kruskal-Wallis test, Friedman test, median test, Chi-square test, Fisher’s exact test.

Linear regression and correlation.

Overview of multivariate statistics: Main components. Discriminant analysis.Cluster analysis

Practical sessions with the statistical software R and SPSS on medical data.

Full programme

Design and analysis of experiments.
Power analysis, effect size and sample size calculations.
Probability calculus, combinatorial analysis and special probability distributions.
Review of univariate statistics and elementary descriptive statistics.
Review of general principles of univariate statistical inference. Sampling distribution. Hypothesis and hypothesis testing. Type 1 and type 2 error. Power of a test and operating curve.
Parametric test : Student t-test, ANOVA and repeated measures ANOVA.
Non-parametric test: Wilcoxon test, Mann-Whitney test, Kruskal-Wallis test, Friedman test, median test, Chi-square test, Fisher exact test.

Multivariate Statistics
Overview of multiple regression, logistic regression, principal component analysis, classification and cluster analysis.

Practical session with the professional statistical systems "R" and "SPSS" on medical data.

Bibliography

1) Lecture notes
3) Sidney Siegel, N. John Castellan Jr. : Statistica non parametrica, ed. McGraw-Hill
4) 4) Internet resources and links

Teaching methods

classroom lectures

Assessment methods and criteria

written exam

Other information

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2030 agenda goals for sustainable development

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Contacts

Toll-free number

800 904 084

Segreteria studenti

E. [email segreteria @unipr] (modificare link a email)
T. +39 0521 000000

Servizio per la qualità della didattica

Manager della didattica:
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T. +39 0521 000000
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