Understanding Data Processing, Analysis, and Management

Given the general context of an increase in the amount of naturalistic and scientific data collected/available and a growing need to collect, process, analyze, and archive this data, this module offers learners training that equips them to tackle these issues with confidence.

The specific objectives will be to learn and use the methods and tools necessary for entering, verifying, managing, and analyzing scientific and naturalist data. Acquire statistical vocabulary and master descriptive statistics. Acquire the knowledge and approach necessary to take statistical aspects into account when implementing sampling protocols. This will be divided into three sequences as follows:

Sequence 1: Concepts in data processing and descriptive statistics

Theoretical and practical knowledge of data entry, formatting, manipulation, control, and visualization (using Spreadsheet/R). Descriptive statistical vocabulary (e.g., mean, median, variance), proficiency in descriptive statistical tools.

Sequence 2: Concepts in inferential statistics

Inferential statistics (most commonly used hypothesis tests), power analyses (case studies).

Sequence 3: Tools and indices for describing diversity

Biodiversity indices (e.g., Shannon and Simpson diversity indices, species richness), tools used to study it (accumulation curves, clustering analyses [NJ, UPGMA]) - Case study using R software.

Open to continuing education

Skills targeted by the EU:

- E-1 Understand descriptive statistics (trend, dispersion, distribution)

- E-2 Knowledge of standard tests, conditions, and limitations of use

- E-4 Know how to use statistical knowledge to implement a sampling and/or experimentation plan

- E-5 Be able to describe data numerically and represent it graphically

- E-6 Know how to choose and perform a hypothesis test appropriate to the biological question and type of data (t-test, Fisher's exact test, chi-square test, comparison of two proportions, correlation)

- E-7 Know how to use a spreadsheet and R software for simple statistical analyses, calculations, and data manipulation and representation.

- I-17 Be able to use computer tools for data entry, analysis, and backup (spreadsheet, R)