Handling of Chemical Data

The Handling of Chemical Data deals with how measurements, such as those arrived at from chemical experimentation, are handled. The book discusses the different kinds of measurements and their specific dimensional characteristics by starting with the origin and presentation of chemical data. The text explains the units, fixed points, and relationships found between scales, the concept of dimensions, the presentation of quantitative data (whether in a tabular or graphical form), and some uses of empirical equations. The book also explains the relationship between two variables, and how equations such as fitting the least square lines can be applied. The text explains how the simple regression and the correlations models can be modified in three ways depending on the complexities present while studying experimental data. When data are reduced to equation form, ancillary operations - interpolation, integration, and differentiation - become useful for more precise presentation and understanding of the experimental data. The book notes the importance of smoothing or adjustment as a procedure to eliminate the effects of random error through application of the direct methods, difference methods, and the least squares method for equally space values. The text then addresses the dimensional analysis in physico-chemical problems and discusses the different dimensions (time, mass, force, energy, and temperature) that can affect systems. Researchers who are time-constrained or equipped with only fundamental training and knowledge of statistical analysis will find this book helpful. It can also be read by students of advanced mathematics and statistical analysis.

The Handling of Chemical Data deals with how measurements, such as those arrived at from chemical experimentation, are handled. The book discusses the different kinds of measurements and their specific dimensional characteristics by starting with the origin and presentation of chemical data. The text explains the units, fixed points, and relationships found between scales, the concept of dimensions, the presentation of quantitative data (whether in a tabular or graphical form), and some uses of empirical equations. The book also explains the relationship between two variables, and how equations such as fitting the least square lines can be applied. The text explains how the simple regression and the correlations models can be modified in three ways depending on the complexities present while studying experimental data. When data are reduced to equation form, ancillary operations - interpolation, integration, and differentiation - become useful for more precise presentation and understanding of the experimental data. The book notes the importance of smoothing or adjustment as a procedure to eliminate the effects of random error through application of the direct methods, difference methods, and the least squares method for equally space values. The text then addresses the dimensional analysis in physico-chemical problems and discusses the different dimensions (time, mass, force, energy, and temperature) that can affect systems. Researchers who are time-constrained or equipped with only fundamental training and knowledge of statistical analysis will find this book helpful. It can also be read by students of advanced mathematics and statistical analysis.