News / Blog: #regression

What are data analysis methods?

Data analysis methods are techniques used to examine and analyze data to identify trends, patterns, and other useful information. Some of the most common data analysis methods are regression analysis, cluster analysis, descriptive statistics, exploratory data analysis, machine learning, hypothesis testing, and causal analysis.

What are machine learning algorithms?

Machine learning algorithms are algorithms that learn autonomously by analyzing information from existing data. They enable computer systems to learn from experience and apply it to new data and situations, allowing them to solve problems without explicit instructions. Machine learning algorithms include artificial neural networks, decision trees, support vector machines, Bayes networks, regression methods, and clustering algorithms.

What is a regression equation?

A regression equation is a mathematical equation used to determine a measure of the relationship between two or more variables. It is usually used to describe a linear relationship between variables in order to make predictions about the relationship between them.

What is regression analysis?

Regression analysis is a mathematical technique used to predict future outcomes and determine the relationships between different variables. It can be used to predict the effect of a particular influencing factor on another variable or to determine which variables contribute most strongly to a particular metric. Applications of regression analysis include predicting sales volumes, determining prices, and determining credit risk.

What are the Gauss-Markov assumptions?

The Gauss-Markov assumptions are a group of assumptions used in linear regression analysis. They include the assumption that the influencing factors (the predictor variables) are independent of each other, the relationship between the influencing factors and the dependent variable is linear, the variance of the dependent variable is constant, and the residuals are normally distributed. The Gauss-Markov assumptions form the basis for linear regression analysis.