What Types of Statistical Models are Used in Catalysis?
Several types of statistical models are commonly used in catalysis, including:
1. Linear Regression Models: Simple models that describe the linear relationship between two or more variables. 2. Non-linear Regression Models: These models capture more complex relationships that are not linear. 3. Response Surface Methodology (RSM): A collection of mathematical and statistical techniques useful for modeling and analyzing problems in which several variables influence the response. 4. Principal Component Analysis (PCA): A dimensionality-reduction technique that transforms data into a set of orthogonal components. 5. Machine Learning Models: Advanced algorithms such as neural networks and decision trees that can capture complex patterns in data.
