Least Squares Refinement is a mathematical optimization technique used to minimize the sum of the squares of the differences between observed and calculated values. It is widely used in data fitting, regression analysis, and crystallography to improve the accuracy of models or structures by iteratively adjusting parameters to best fit the data.

Least Squares Refinement

Mathematical optimization technique

Sum of the squares

Differences between observed and calculated values

Data fitting is the process of constructing a mathematical function that best describes the relationship between a set of observed data points. It is crucial for making predictions and understanding underlying patterns in data across various scientific and engineering disciplines.

Data Fitting

Regression analysis is a statistical method used to model and analyze the relationships between a dependent variable and one or more independent variables. It helps in predicting outcomes and identifying the strength and nature of relationships, making it a fundamental tool in data analysis and predictive modeling.

Regression Analysis

Crystallography is the scientific study of crystal structures and properties, primarily using X-ray diffraction to determine the atomic and molecular arrangement within a crystal. It is crucial in fields like materials science, chemistry, and biology for understanding the structural basis of material properties and biological functions.

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