Mathematical statistics - Data processing.

Step-by-step basic statistics using SAS by: (Electronic resources)

Step-by-step basic statistics using SAS by: (Electronic resources)

Understanding statistical concepts using S-plus by: (Electronic resources)

Data Manipulation with R by: (Language materials, printed)

Introducing Monte Carlo methods with R by: (Language materials, printed)

The basics of S-Plus by: (Language materials, printed)

Computational statistics by: (Language materials, printed)

Core concepts in data analysis = summarization, correlation and visualization / by: (Electronic resources)

Problem solving and data analysis using Minitab = a clear and easy guide to six sigma methodology / by: (Electronic resources)

An introduction to statistical computing = a simulation-based approach / by: (Electronic resources)

Data wrangling with R by: (Electronic resources)

The R primer / by: (Language materials, printed)

Computer age statistical inference = algorithms, evidence, and data science / by: (Electronic resources)

Basic statistics with R = reaching decisions with data / by: (Electronic resources)

Intermediate statistical methods and applications : = a computer package approach / by: (Language materials, printed)

Elements of simulation / by: (Language materials, printed)

Genstat 5 release 3 reference manual / by: (Language materials, printed)

Applied statistics : = a handbook of Genstat analyses / by: (Language materials, printed)

Computational statistics / by: (Language materials, printed)

MACSYMA for statisticians / by: (Language materials, printed)

SAS/STAT user's guide : = version 6. by: (Language materials, printed)

Computer-interactive data analysis / by: (Language materials, printed)

SAS procedures guide : = version 6. by: (Language materials, printed)

SAS screen control language : = reference : version 6. by: (Language materials, printed)

Statistical modelling using GENSTAT / by: (Language materials, printed)

Mathematical statistics with Mathematica / by: (Language materials, printed)

Data analysis for the behavioral sciences using SPSS / by: (Language materials, printed)

Categorical data analysis using the SAS system / by: (Language materials, printed)

SAS system for mixed models / by: (Language materials, printed)

Data analysis using stata / by: (Language materials, printed)

A gentle introduction to Stata / by: (Language materials, printed)

The basics of S-Plus by: (Electronic resources)

Getting started with the SAS System = version 8. by: (Electronic resources)

The basics of S and S-Plus by: (Electronic resources)

Base SAS 9.1 procedures guide by: (Electronic resources)

SAS?for Monte Carlo studie = a guide for quantitative researchers / by: (Electronic resources)

The little SAS book = a primer / by: (Electronic resources)

SAS/STAT 9.1 = user's guide. by: (Electronic resources)

The R book / by: (Language materials, printed)

Applied statistics and the SAS programming language / by: (Language materials, printed)

Statistical modelling in R / by: (Language materials, printed)

Guide to intelligent data analysis = how to intelligently make sense of real data / by: (Language materials, printed)

Computational statistics : = an introduction to R / by: (Language materials, printed)

Computational statistics handbook with MATLAB / by: (Language materials, printed)

Computing statistics under interval and fuzzy uncertainty = applications to computer science and engineering / by: (Electronic resources)

SPSS for starters.. Part 2 by: (Electronic resources)

Excel 2007 for educational and psychological statistics = a guide to solving practical problems / by: (Electronic resources)

The Numerati / by: (Language materials, printed)

Applied statistical inference with MINITAB by: (Electronic resources)

Statistics and data analysis for microarrays using R and Bioconductor / by: (Language materials, printed)

Mathematical statistics with applications in R / by: (Language materials, printed)

Advances in complex data modeling and computational methods in statistics by: (Electronic resources)

Basic statistics = an introduction with R / by: (Electronic resources)

Mathematical statistics with applications in R by: (Electronic resources)

Statistical analysis and data display = an intermediate course with examples in R / by: (Electronic resources)

Political analysis using R by: (Electronic resources)

An introduction to statistics with Python = with applications in the life sciences / by: (Electronic resources)

A Course in statistics with R / by: (Language materials, printed)

An introduction to data analysis using aggregation functions in R by: (Electronic resources)

Modern data science with R / by: (Language materials, printed)

Statistical analysis with R / by: (Language materials, printed)

Comparative approaches to using R and Python for statistical data analysis by: (Electronic resources)

Statistical data analysis using SAS = intermediate statistical methods / by: (Electronic resources)

QCA with R = a comprehensive resource / by: (Electronic resources)

Advanced R statistical programming and data models = analysis, machine learning, and visualization / by: (Electronic resources)

Reliability and statistical computing = modeling, methods and applications / by: (Electronic resources)

The R primer by: (Electronic resources)

Computational statistics handbook with MATLAB / by: (Language materials, printed)

Applications in statistical computing = from music data analysis to industrial quality improvement / by: (Electronic resources)

Guide to intelligent data science = how to intelligently make use of real data / by: (Electronic resources)

Artificial intelligence, big data and data science in statistics = challenges and solutions in environmetrics, the natural sciences and technology / by: (Electronic resources)

An introduction to statistics with Python = with applications in the life sciences / by: (Electronic resources)

Mathematical statistics with applications in R by: (Electronic resources)

Applications in reliability and statistical computing by: (Electronic resources)

Using MATLAB to solve statistical problems = a practical guide to the book "Statistics for chemical and process engineers" / by: (Electronic resources)

The R book by: (Electronic resources)

Advanced statistical methods in process monitoring, finance, and environmental science = essays in honour of Wolfgang Schmid / by: (Electronic resources)

Methodological and applied statistics and demography.. III,. SIS 2024, short papers, contributed sessions 1 by: (Electronic resources)

A step-by-step guide to exploratory factor analysis with Stata by: (Electronic resources)

SAS language : = reference : version 6. by: (Language materials, printed)

XploRe : = application guide / by: (Language materials, printed)

Complex models and computational methods in statistics / by: (Language materials, printed)

Basics of matrix algebra for statistics with R / by: (Language materials, printed)

Using R and RStudio for data management, statistical analysis, and graphics / by: (Language materials, printed)

Computational statistics handbook with MATLAB / by: (Language materials, printed)

Using statistics in the social and health sciences with SPSS and Excel / by: (Electronic resources)

The stata survival manual by: (Electronic resources)

R programming = statistical data analysis in research / by: (Electronic resources)

Applied statistics and the SAS programming language / by: (Language materials, printed)

SAS/IML software : = usage and reference, version 6. by: (Language materials, printed)

Basic statistical computing / by: (Language materials, printed)

Advanced data analysis with SYSTAT / by: (Language materials, printed)

Smoothing techniques : = with implementation in S / by: (Language materials, printed)

Statistics laboratory manual : = experiments using minitab/ by: (Language materials, printed)

Modern applied statistics with S-Plus / by: (Language materials, printed)

Minitab handbook / = Barbara F. Ryan, Brian L. Joiner. by: (Language materials, printed)

Mastering the SAS system / by: (Language materials, printed)

SAS/AF guide for personal computers by: (Language materials, printed)

Data analysis for managers with MINITAB / by: (Language materials, printed)

SAS/STAT technical report : = spatial prediction using the SAS system. by: (Language materials, printed)

SAS software : = changes and enhancements, release 6.11. by: (Language materials, printed)

SAS/STAT software : = changes and enhancements for release 6.12. by: (Language materials, printed)

Applied statistics and the SAS programming language / by: (Language materials, printed)

Advances in stochastic simulation methods / by: (Language materials, printed)

The basics of S and S-Plus / by: (Language materials, printed)

Intelligent data analysis : = an introduction / by: (Language materials, printed)

Statistical computing : = an introduction to data analysis using S-Plus / by: (Language materials, printed)

Modern applied statistics with S / by: (Language materials, printed)

Foundations of statistical analyses and applications with SAS / by: (Language materials, printed)

Intelligent data analysis : = an introduction / by: (Language materials, printed)

The basics of S-Plus / by: (Language materials, printed)

JMP for basic univariate and multivariate statistics = a step-by-step guide / by: (Electronic resources)

The Basics of S-PLUS by: (Language materials, printed)

Statistical computing with R / by: (Language materials, printed)

Introducing Monte Carlo methods with R / by: (Language materials, printed)

Two-way analysis of variance = statistical tests and graphics using R / by: (Electronic resources)

Getting started with R : = an introduction for biologists / by: (Language materials, printed)

Getting Started with R = An introduction for biologists / by: (Electronic resources)

Sharpening your advanced SAS skills / by: (Language materials, printed)

R data analysis without programming by: (Electronic resources)

Statistical disclosure control for microdata = methods and applications in R / by: (Electronic resources)

The data science design manual by: (Electronic resources)

Basic elements of computational statistics by: (Electronic resources)

Core data analysis = summarization, correlation, and visualization / by: (Electronic resources)

Deep learning with R / by: (Language materials, printed)