Predicate calculus.

Subsystems of second order arithmetic / by: (Language materials, printed)

The social sciences of quantification = from politics of large numbers to target-driven policies / by: (Electronic resources)

Modern quantification theory = joint graphical display, biplots, and alternatives / by: (Electronic resources)

On spatio-temporal data modelling and uncertainty quantification using machine learning and information theory by: (Electronic resources)

Optimal quantification and symmetry by: (Electronic resources)

Analysis of categorical data from historical perspectives = essays in honour of Shizuhiko Nishisato / by: (Electronic resources)

Uncertainty quantification using R by: (Electronic resources)

Measurement, mathematics and new quantification theory by: (Electronic resources)

Philosophy.

Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.

Statistics for Social Sciences, Humanities, Law.

Symmetry (Mathematics)

Data Analysis and Big Data.

Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Psychometrics.

Statistical Theory and Methods.

Uncertainty (Information theory)

Earth and Environmental Sciences.

Renewable Energy.

Statistics and Computing.

Statistics- Methodology.

Applied Statistics.

Uncertainty- Mathematical models.

R (Computer program language)

Applied Probability.

Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.

Predicate calculus.

Statistics for Business, Management, Economics, Finance, Insurance.

Computer Modelling.

Discrete Optimization.

Methodology of the Social Sciences.

Machine learning.

Social sciences- Statistical methods.

Philosophy of the Social Sciences.

Operations Research and Decision Theory.

Categories (Mathematics)