LABORATORY OF BIOSTATISTICS
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- Versione italiana
- Academic year
- 2019/2020
- Teacher
- ALBERTO CARRIERI
- Credits
- 6
- Didactic period
- Secondo Semestre
- SSD
- SECS-S/01
Training objectives
- The course-laboratory is the natural "practical" continuation of Biostatistics course (third year of Biological Sciences), which proposes the most of the topics covered, facing them, however, from the point of view of applications through numerous practical exercises to be carried out to the personal computer.
At the end of the course students will be able to:
use basic software for automatic calculation and graphics on personal computers, such as spreadsheets and their statistical functions and / or specific statistical software in order to give synthetic description of biological data (and not only) through the appropriate descriptive statistics and appropriate graphical representations;
set the statistical analysis appropriate to the type of biological data available and make appropriate statistical tests. Prerequisites
- To understand the more theoretical aspects of the matter is that the student must possess a solid background in basic statistical analysis methods. Therefore, the course of Biostatistics is considered preparatory to course of Laboratory of Biostatistics.
Course programme
- The course consists of 48 hours (6 CFU) of lessons including lectures (4 CFU) and exercises (2 CFU) to be performed in the computer.
The main issues discussed during the course will cover:
Exploratory Data Analysis:
the concept of variable and variable types;
measures of central tendency and dispersion;
graphical representation of data;
Basics of probability:
basic notions;
rule of the sum;
rule of the product.
Frequency distributions and probability:
theoretical discrete probability distributions;
theoretical continuous probability distributions;
the normal or Gaussian distribution;
the standard normal distribution;
Central Limit Theorem.
Estimates with a sample:
estimate of the proportion of the population;
estimate the mean of a population: s known;
estimate the mean of a population: s unknown.
Hypothesis testing with a sample:
basic concepts of hypothesis testing;
testing hypotheses on a proportion;
hypothesis test on an mean: s note;
hypothesis test on an mean: s unknown.
Inference for two samples:
inference on two proportions;
inference of two means: independent samples;
inference of two means: paired samples;
comparison of the variability of two samples.
The Chi-square test:
basic concepts;
the chi-square "goodness of fit";
contingency tables for the analysis of the association between variables.
The binomial distribution:
basic concepts of the binomial distribution;
fit testing an observed frequency distribution to the binomial distribution.
The Poisson distribution:
basic concepts of the Poisson distribution;
adaptation tests of a frequency distribution observed to the Poisson distribution.
Analysis of variance:
basic concepts of analysis of variance;
1-way analysis of variance. Didactic methods
- Lessons in the classroom on theoretical topics of the course;
practice in computer lab with exercises to be carried out through the use of spreadsheet software (MS Excel or similar) for the calculation and learning capabilities of computing and graphics as well as basic statistical functions made available from this type of software; in parallel, the same exercises will be resolved through the use of open source statistical package R-Cran Learning assessment procedures
- The aim exam is to test the level of achievement of learning objectives previously indicated.
The exam consists of a practical test to the personal computer; the student will have to solve some exercises (usually 4)of descriptive statistics (calculation of the measures of central tendency and dispersion of a set of biological data) and inferential (application of some of the statistical tests learned during the course) to deal with both a spreadsheet program (MS Excel or similar) that, at least one, with the statistical software R-Cran.
The total duration of the test is 3 hours and 30 minutes. For each exercise will be given a score from 0 to 30. The final mark is the average of the scores obtained in the various exercises. The exam is passed when it reaches the minimum score of 18 on 30. Reference texts
- Teacher’s handouts.
L'analisi dei Dati Biologici. Whitlock e Schluter. Zanichelli. 2010.
Analisi esplorativa dei dati con R. G. Espa, R. Micciolo. Maggioli Editore, 2019.
Laboratorio di Statistica con R. F. Ieva, C. Masci, A.M. Paganoni. Seconda Edizione. Pearson, 2016
