Statistical Tools for Marine Ecosystem Analysis

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Statistical Tools for Marine Ecosystem Analysis

The main objective of this course is to implement the knowledge and skills of statistical programming based on the R platform, to incorporate the theoretical knowledge of ecological data modeling and export and  visualization of the results.
The content is based on the correct use of R (environment and programming language with a focus on statistical analysis) to be able to implement biological data analysis and modeling techniques related to calibrate and validate statistical models that help the understanding and prediction of ecological phenomena.
Image from A. J. canepa

Introduction to programming in R and RStudio

  •  Operations and mathematical functions and basic statistics.
  • Introduction to the R programming software and the RStudio graphic interface.
  • Download, installation and maintenance (Housekeeping) of the R software and the statistical packages.
  • Download, installation and configuration of the graphical interface software RStudio.
  • Management of the workspace and of scripts.

Data types and structures in R

  • Structure of data in R and statistical analysis.
  • Basic programming and general calculations (R as a calculator).
  • Basic programming oriented to objects (vectors, lists, matrix and dataframes).
  • Concatenation and data combination.
  • Ordering, indexing and general manipulation of objects

Import and handling of data in R

  • Importing data from different platforms.
  • Handling of dataframes.

Basic functions in R

  • Basic functions and descriptive statistics.
  • Data creation.
  • Introduction to statistical graphs.
  • Graphs in the base distribution of R.
  • Exportation of graphs.

Advanced functions in R

  • Introduction to the loops.
  • Advanced statistical functions in R.
  • Advanced statistical graphics.
  • Introduction to the “ggplot2” package.
  • Visual exploration of data for statistical purposes.

Statistical modeling with R

  • Introduction to statistical modeling in R.
  • Introduction to statistical models.
  • Linear models. Generalized linear models.
  • Additive Models. Generalized Additive Models.

A previous edition of this course was held in Escuela de Ciencias del Mar, PUCV in Valparaiso Chile  (July 2017).

The course was framed within the project: Model and Implementation of a Visualization System for the Program of Red Tides and Larvae of Mytilids, in the Geographic Information System of the undersecretary of Fisheries and Aquaculture, (Stage II. FIPA N ° 2016-13).  The theoretical-practical course  was taught to the professionals of the Division of Aquaculture of SUBPESCA .

+ CONTENTS

Introduction to programming in R and RStudio

  •  Operations and mathematical functions and basic statistics.
  • Introduction to the R programming software and the RStudio graphic interface.
  • Download, installation and maintenance (Housekeeping) of the R software and the statistical packages.
  • Download, installation and configuration of the graphical interface software RStudio.
  • Management of the workspace and of scripts.

Data types and structures in R

  • Structure of data in R and statistical analysis.
  • Basic programming and general calculations (R as a calculator).
  • Basic programming oriented to objects (vectors, lists, matrix and dataframes).
  • Concatenation and data combination.
  • Ordering, indexing and general manipulation of objects

Import and handling of data in R

  • Importing data from different platforms.
  • Handling of dataframes.

Basic functions in R

  • Basic functions and descriptive statistics.
  • Data creation.
  • Introduction to statistical graphs.
  • Graphs in the base distribution of R.
  • Exportation of graphs.

Advanced functions in R

  • Introduction to the loops.
  • Advanced statistical functions in R.
  • Advanced statistical graphics.
  • Introduction to the “ggplot2” package.
  • Visual exploration of data for statistical purposes.

Statistical modeling with R

  • Introduction to statistical modeling in R.
  • Introduction to statistical models.
  • Linear models. Generalized linear models.
  • Additive Models. Generalized Additive Models.

+ Previous EDITIONS

A previous edition of this course was held in Escuela de Ciencias del Mar, PUCV in Valparaiso Chile  (July 2017).

The course was framed within the project: Model and Implementation of a Visualization System for the Program of Red Tides and Larvae of Mytilids, in the Geographic Information System of the undersecretary of Fisheries and Aquaculture, (Stage II. FIPA N ° 2016-13).  The theoretical-practical course  was taught to the professionals of the Division of Aquaculture of SUBPESCA .

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