Data analysis and applied statistics in wood science

• Introduction to statistics and the scientific method

                       Scientific approach

                       Data structuring

                       Descriptive statistics

                       Overview of analysis methods

                       A critical look at statistics

• Univariate analyses

                       Comparison tests

                       Distribution compliance

                       Simple regression and analysis of variance/covariance

• Multivariate analyses

                       Correlations and principal component analysis

                       Multiple linear regression

                       Nonlinear adjustments

• Classification and discrimination

                       Classification (supervised, unsupervised)

                       Segmentation and discrimination

• Statistical analysis tools

                       Introduction to R software

The EU "Data Analysis" course aims to teach the main methods of statistical analysis, enable students to acquire a rigorous analytical approach, and develop critical thinking skills in interpreting results.

• Understanding the role of statistics in a rigorous scientific approach
• Organize data for analysis
• Formulate an analysis requirement in statistical terms
• Perform univariate and multivariate statistical analysis
• Interpreting the results of univariate and multivariate analysis
• Know the main segmentation methods
• Manipulating data with R
• Using R functions to analyze data