Sciences and Teaching of Natural Systems

Introduction: Basic Statistics (mean, variance, measure of location, frequency distributions). Graphical representations and summary statistics.Probability distributions : The Normal distribution and its relevance in modeling biological dataProbability distributions: Student’s t.The t test: general concepts, two sample t test, two sample paired t test, t test with unequal variances. Chi-squared Tests: When and how to use it; chi-square as a goodness of fit test, chi square in contingency tables.Analysis of Variance: some theory, Fisher Snedecor F distribution, relationships between t and F tests.Basic Experimental design for the analysis of variance; factorial esperiments: with two and multiple factors.Linear regression and correlation: Pearson correlation, the linear model with one covariate.Basic elements of multiple regression and generalized linear models.Introduction to multivariate statistical analysis: Principal components analysis and correspondence analysis.

Basic knowledge of descriptive statistics. Some familiarity with matrix algebra is appreciated.

Slides and texts available online from http://elearning2.uniroma1.it/course/view.php?id=2211that is the elearning systemof Sapienza university van Emden H. Statistics for terrified biologists Blackwell Publishing, UK CAST http://cast.massey.ac.nz/collection_public.html Zuur, Ieno & Smith (2007) Analysing Ecological data. Springer

Lectures will be given according to sapienza governance choices. All lectures are developed with a first part where theory is introduced and a second part where while learning the use of the R software, the theory is applied to real data.

On the elearning of the class (https://elearning.uniroma1.it/course/view.php?id=2211) slides, reports, books, and R scripts are available for those unable to attend. For the 2021/2022 year the recording of all lectures is also available upon request The 2022/2023 course recordings are also available on request.

The class is split into working group. Each group must prepare a report on a real dataset. When the report is approved each student can access the oral exam.

van Emden H. Statistics for terrified biologists Blackwell Publishing, UK CAST http://cast.massey.ac.nz/collection_public.html Zuur, Ieno & Smith (2007) Analysing Ecological data. Springer

Lectures will be given according to sapienza governance choices. All lectures are developed with a first part where theory is introduced and a second part where while learning the use of the R software, the theory is applied to real data.

Introduction: Basic Statistics (mean, variance, measure of location, frequency distributions). Graphical representations and summary statistics.Probability distributions : The Normal distribution and its relevance in modeling biological dataProbability distributions: Student’s t.The t test: general concepts, two sample t test, two sample paired t test, t test with unequal variances. Chi-squared Tests: When and how to use it; chi-square as a goodness of fit test, chi square in contingency tables.Analysis of Variance: some theory, Fisher Snedecor F distribution, relationships between t and F tests.Basic Experimental design for the analysis of variance; factorial esperiments: with two and multiple factors.Linear regression and correlation: Pearson correlation, the linear model with one covariate.Basic elements of multiple regression and generalized linear models.Introduction to multivariate statistical analysis: Principal components analysis and correspondence analysis.

Basic knowledge of descriptive statistics. Some familiarity with matrix algebra is appreciated.

Slides and texts available online from http://elearning2.uniroma1.it/course/view.php?id=2211that is the elearning systemof Sapienza university van Emden H. Statistics for terrified biologists Blackwell Publishing, UK CAST http://cast.massey.ac.nz/collection_public.html Zuur, Ieno & Smith (2007) Analysing Ecological data. Springer

Lectures will be given according to sapienza governance choices. All lectures are developed with a first part where theory is introduced and a second part where while learning the use of the R software, the theory is applied to real data.

On the elearning of the class (https://elearning.uniroma1.it/course/view.php?id=2211) slides, reports, books, and R scripts are available for those unable to attend. For the 2021/2022 year the recording of all lectures is also available upon request The 2022/2023 course recordings are also available on request.

The class is split into working group. Each group must prepare a report on a real dataset. When the report is approved each student can access the oral exam.

van Emden H. Statistics for terrified biologists Blackwell Publishing, UK CAST http://cast.massey.ac.nz/collection_public.html Zuur, Ieno & Smith (2007) Analysing Ecological data. Springer

Lectures will be given according to sapienza governance choices. All lectures are developed with a first part where theory is introduced and a second part where while learning the use of the R software, the theory is applied to real data.