Biostatistics and design of experiments in biotechnology
A.A. 2024/2025
Obiettivi formativi
The aim of the course is to provide fundamental knowledge to describe and analyse biological and biotechnological data with the most appropriate statistical tools. The course will provide a strong theoretical foundation together with a practical use of descriptive statistics, inferential statistics and hypothesis testing. The course also aims to provide the basic tools of common experimental designs. Besides theoretical classes, close attention will be paid to computer sessions.
Risultati apprendimento attesi
Students will acquire the following skills: 1) the ability to organize, summarize and represent biotechnological data; 2) use the appropriate standard errors and margins of error to define confidence intervals for the main statistics; 3) formulate the hypothesis and apply the appropriate statistical test; 3) determine the appropriate design of experiment; 5) understand and comment on the outputs of a statistical software
Periodo: Primo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Primo semestre
Programma
As the skills acquired from this teaching are useful for experimental internship activities, students are warmly encouraged to attend the course in the first year (I semester).
The program is the same for both attending and nonattending students
Program
INTRODUCTION: DESCRIPTIVE AND INFERENTIAL STATISTICS: Samples and populations. Types of variables: qualitative, quantitative. Precision and accuracy. Theoretical class 2hrs
DATA VISUALIZATION: Absolute, relative and cumulative frequency tables. Representing the frequency distributions, diagrams and histograms, percentiles and quantiles, contingency tables. Scatterplot, line chart, maps. Theoretical class 3 hrs - practical class 2 hrs
DESCRIBING DATA: Measures of location and dispersion, geometric and arithmetic mean, median, mode, interquartile range, range of variation, deviation, variance, standard deviation, coefficient of variation. Theoretical class 3 hrs - practical class 3 hrs
ESTIMATE WITH UNCERTAINTLY: sampling distribution, standard error and confidence interval. Theoretical class 2 hrs - practical class 2 hrs
PROBABILITY: basic rules, Venn diagrams, probability trees. Sum the odds. Independence and the product rule. Conditional probability. Theoretical class 2 hrs - practical class 1 hr
HYPOTHESIS TESTING: null and alternative hypotheses and statistical significance, P-value. Hypothesis testing and confidence intervals. Error of first and second species. Theoretical class 3 hrs - practical class 1 hr
ANALYSIS OF PROPORTIONS: binomial distribution. Estimate of the proportions: confidence interval and standard error of a proportion. Chi-square test and the goodness of fit. Poisson distribution. Contingency tables for the analysis of categorical variables and chi-square test for the analysis of contingency tables. Theoretical class 4 hrs - practical class 4 hrs
NORMAL DISTRIBUTION: formula, assumptions and properties. The central limit theorem. Normal approximation for binomial distribution. Theoretical class 3 hrs - practical class 2 hrs
INFERENCE IN POPULATION WITH A NORMAL DISTRIBUTION: t-distribution, assumptions and properties. t-test for one sample. Comparison between two means, paired comparison between means, comparing the means of two samples. Theoretical class 3 hrs - practical class 2 hrs
ANALYSIS OF VARIANCE: comparisons between means of multiple groups. Theoretical class 3 hrs - practical class 3 hrs
MEASUREMENTS OF RELATIONSHIP BETWEEN VARIABLES: covariance, correlation and linear regression. Least squares. Linear regression. Theoretical class 4 hrs - practical class 2 hrs
GUIDELINES FOR DESIGNING EXPERIMENTS: the three basic principles of experimental design randomization, replication and blocking. Determining sample size. Theoretical class 4 hrs - practical class 2 hrs
The program is the same for both attending and nonattending students
Program
INTRODUCTION: DESCRIPTIVE AND INFERENTIAL STATISTICS: Samples and populations. Types of variables: qualitative, quantitative. Precision and accuracy. Theoretical class 2hrs
DATA VISUALIZATION: Absolute, relative and cumulative frequency tables. Representing the frequency distributions, diagrams and histograms, percentiles and quantiles, contingency tables. Scatterplot, line chart, maps. Theoretical class 3 hrs - practical class 2 hrs
DESCRIBING DATA: Measures of location and dispersion, geometric and arithmetic mean, median, mode, interquartile range, range of variation, deviation, variance, standard deviation, coefficient of variation. Theoretical class 3 hrs - practical class 3 hrs
ESTIMATE WITH UNCERTAINTLY: sampling distribution, standard error and confidence interval. Theoretical class 2 hrs - practical class 2 hrs
PROBABILITY: basic rules, Venn diagrams, probability trees. Sum the odds. Independence and the product rule. Conditional probability. Theoretical class 2 hrs - practical class 1 hr
HYPOTHESIS TESTING: null and alternative hypotheses and statistical significance, P-value. Hypothesis testing and confidence intervals. Error of first and second species. Theoretical class 3 hrs - practical class 1 hr
ANALYSIS OF PROPORTIONS: binomial distribution. Estimate of the proportions: confidence interval and standard error of a proportion. Chi-square test and the goodness of fit. Poisson distribution. Contingency tables for the analysis of categorical variables and chi-square test for the analysis of contingency tables. Theoretical class 4 hrs - practical class 4 hrs
NORMAL DISTRIBUTION: formula, assumptions and properties. The central limit theorem. Normal approximation for binomial distribution. Theoretical class 3 hrs - practical class 2 hrs
INFERENCE IN POPULATION WITH A NORMAL DISTRIBUTION: t-distribution, assumptions and properties. t-test for one sample. Comparison between two means, paired comparison between means, comparing the means of two samples. Theoretical class 3 hrs - practical class 2 hrs
ANALYSIS OF VARIANCE: comparisons between means of multiple groups. Theoretical class 3 hrs - practical class 3 hrs
MEASUREMENTS OF RELATIONSHIP BETWEEN VARIABLES: covariance, correlation and linear regression. Least squares. Linear regression. Theoretical class 4 hrs - practical class 2 hrs
GUIDELINES FOR DESIGNING EXPERIMENTS: the three basic principles of experimental design randomization, replication and blocking. Determining sample size. Theoretical class 4 hrs - practical class 2 hrs
Prerequisiti
None
Metodi didattici
Besides theoretical classes (4.5 CFU, 32 hours), close attention will be paid to computer sessions (1.5 CFU, 24 hours). Biostatistics will be presented with a practical approach emphasizing the rationale of statistical theory and methods rather than mathematical proofs and formalisms. Each theoretical lecture will be combined with practical applications and exercises using simple spreadsheets to analyze experimental data. Besides theoretical classes, there will also be intensive computer sessions
Students can choose to attend this course during the first year (I semester) or the second year (I semester). As the skills acquired from this teaching are useful for experimental internship activities, students are warmly encouraged to attend the course in the first year (I semester).
Students can choose to attend this course during the first year (I semester) or the second year (I semester). As the skills acquired from this teaching are useful for experimental internship activities, students are warmly encouraged to attend the course in the first year (I semester).
Materiale di riferimento
Slides of any lecture, exercises, datasets, procedures for data analysis and bibliographic material will be provided by the teacher through the Ariel online platform (www.ariel.unimi.it) at https://pcrepaldib.ariel.ctu.unimi.it/v5/home/Default.aspx
The core text is: The analysis of Biological data - Second edition. Whitlock M.C. Schluter D.
Ed. By W.H. Freeman and company
Other reference books will be suggested during the course.
The material and suggested books are the same for both attending and nonattending students
The core text is: The analysis of Biological data - Second edition. Whitlock M.C. Schluter D.
Ed. By W.H. Freeman and company
Other reference books will be suggested during the course.
The material and suggested books are the same for both attending and nonattending students
Modalità di verifica dell’apprendimento e criteri di valutazione
The exam consists of a written and a practical examination. The written part consists of 6 Squestions (1 multiple choice question, 2 open theoretical questions; 2 practical problems; 1 statistical analysis to comment on (points 0-4 for each question), and a computer session with 1 dataset to analyze. The biostatistical test will assess the ability to organize, summarize, and represent biotechnological data by choosing the appropriate experimental methodologies and statistical tests. The final score will be the summation of the points obtained in the different parts (written part , points 0-4 for each questions, computer session points 0-6), aimed at ascertaining:
(a) your knowledge and ability to understand the topics of the course as well as mastery of the specific language related to the use of statistical techniques and the ability to present topics in a clear and orderly manner
(b) your ability to apply knowledge and understanding through the analysis of a dataset or the execution and discussion of a statistical problem using excel
(c) your ability to understand and interpret the results of statistical analysis by commenting on an analytical output of statistical software used during the course and your ability in organize an experimental plan.
The final evaluation is based on a total of 30 points.
Activities carried out by students during the course, such as commentaries on analyses, completion of exercises, a compilation of a dictionary of terms, etc. will also be taken into account when determining the final grade.
Specific procedures for students with disabilities or specific learning disabilities (DSA) will be applied. . Here the complete information:
https://www.unimi.it/en/study/student-services/services-students-disabilities
https://www.unimi.it/en/study/student-services/services-students-specific-learning-disabilities-sld
In case you need specific procedures, please inform the teacher by e-mail at least 10 days before the exam, including in the addresses [email protected] or [email protected].
Examination mode is the same for both attending and non-attending students
(a) your knowledge and ability to understand the topics of the course as well as mastery of the specific language related to the use of statistical techniques and the ability to present topics in a clear and orderly manner
(b) your ability to apply knowledge and understanding through the analysis of a dataset or the execution and discussion of a statistical problem using excel
(c) your ability to understand and interpret the results of statistical analysis by commenting on an analytical output of statistical software used during the course and your ability in organize an experimental plan.
The final evaluation is based on a total of 30 points.
Activities carried out by students during the course, such as commentaries on analyses, completion of exercises, a compilation of a dictionary of terms, etc. will also be taken into account when determining the final grade.
Specific procedures for students with disabilities or specific learning disabilities (DSA) will be applied. . Here the complete information:
https://www.unimi.it/en/study/student-services/services-students-disabilities
https://www.unimi.it/en/study/student-services/services-students-specific-learning-disabilities-sld
In case you need specific procedures, please inform the teacher by e-mail at least 10 days before the exam, including in the addresses [email protected] or [email protected].
Examination mode is the same for both attending and non-attending students
AGR/17 - ZOOTECNICA GENERALE E MIGLIORAMENTO GENETICO - CFU: 6
Esercitazioni in aula informatica: 32 ore
Lezioni: 32 ore
Lezioni: 32 ore
Docente:
Crepaldi Paola
Turni:
Turno
Docente:
Crepaldi PaolaDocente/i
Ricevimento:
Su appuntamento richiesto tramite messaggio e-mail
Sezione di Zootecnica Agraria, I piano, via Celoria 2