Statistics - Data processing.

Programming with data : = a guide to the S language / by: (Language materials, printed)

Numerical issues in statistical computing for the social scientist / by: (Language materials, printed)

Developing statistical software in Fortran 95 / by: (Language materials, printed)

Elements of computational statistics by: (Language materials, printed)

Step-by-step programming with base SAS software by: (Language materials, printed)

A first course in statistical programming with R / by: (Language materials, printed)

Applied statistics with SPSS / by: (Language materials, printed)

Computing in statistical science through APL / by: (Language materials, printed)

Statistical analysis of clinical data on a pocket calculator = statistics on a pocket calculator / by: (Electronic resources)

The Art of R programming : = a tour of statistical software design / by: (Language materials, printed)

R cookbook / by: (Language materials, printed)

Design and analysis of experiments with R / by: (Language materials, printed)

Dynamic documents with R and knitr / by: (Language materials, printed)

Beginning data science with R by: (Electronic resources)

Data scientists at work by: (Electronic resources)

Foundations of statistical algorithms / by: (Language materials, printed)

Using R and RStudio for data management, statistical analysis, and graphics by: (Electronic resources)

Panel data analysis using EViews by: (Electronic resources)

A Python data analyst's toolkit = learn Python and Python-based libraries with applications in data analysis and statistics / by: (Electronic resources)

Leadership in statistics and data science = planning for inclusive excellence / by: (Electronic resources)

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

Fundamentals of data analytics = with a view to machine learning / by: (Electronic resources)

Open source software for statistical analysis of big data = emerging research and opportunities / by: (Electronic resources)

The data book = collection and management of research data / by: (Electronic resources)

R 4 data science quick reference = a pocket guide to APIs, libraries, and packages / by: (Electronic resources)

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

SAS companion for the Microsoft Windows environment : = version 6. by: (Language materials, printed)

HyperStat : = Macintosh hypermedia for analyzing data and learning statistics / 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)

SAS applications programming : = a gentle introduction / by: (Language materials, printed)

Learning SAS in the computer lab / by: (Language materials, printed)

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

Quick start to data analysis with SAS / 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)

Introduction to business statistics : = a computer integrated approach / by: (Language materials, printed)

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

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

Introduction to business statistics : = a computer integrated, data analysis approach / by: (Language materials, printed)

Introductory statistics with R / by: (Language materials, printed)

Elements of computational statistics / by: (Language materials, printed)

Data analysis and graphics using R : = an example-based approach / by: (Language materials, printed)

Computational methods in statistics and econometrics / by: (Language materials, printed)

Stata multivariate statistics : = reference manual : release 9. by: (Language materials, printed)

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

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

Introductory statistics with R by: (Language materials, printed)

SAS/IML user's guide 9.1 by: (Language materials, printed)

SAS programming by example by: (Language materials, printed)

Data analysis and graphics using R : = an example-based approach / by: (Language materials, printed)

SAS programming = the one-day course / by: (Language materials, printed)

Developing Statistical Software in Fortran 95 by: (Language materials, printed)

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

Introductory statistics with R by: (Language materials, printed)

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

Using R for introductory statistics / by: (Language materials, printed)

Applied econometrics with R / by: (Language materials, printed)

A beginner's guide to R / by: (Language materials, printed)

Instructor's solutions manual to accompany A First course in business statistics / by: (Language materials, printed)

R for Stata users by: (Language materials, printed)

Symmetry studies = an introduction to the analysis of structured data in applications / by: (Electronic resources)

Behavioral research data analysis with R by: (Electronic resources)

Beginning R = an introduction to statistical programming / by: (Electronic resources)

Using R for introductory statistics / by: (Language materials, printed)

Using R for statistics by: (Electronic resources)

Dynamic documents with R and knitr / by: (Language materials, printed)

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

SPSS for starters and 2nd levelers by: (Electronic resources)

Python for probability, statistics, and machine learning by: (Electronic resources)

Principles of data science by: (Electronic resources)

SAS for R users = a book for budding data scientists / by: (Electronic resources)

Statistics with Julia = fundamentals for data science, machine learning and artificial intelligence / by: (Electronic resources)

Beginning R 4 = from beginner to pro / by: (Electronic resources)

Beginning data science in R 4 = data analysis, visualization, and modelling for the data scientist / by: (Electronic resources)

Modern statistics = a computer-based approach with Python / by: (Electronic resources)

Data analytics and AI by: (Electronic resources)

Statistics applied with Excel = data analysis is (not) an art / by: (Electronic resources)

Introductory applied statistics = with resampling methods & R / by: (Electronic resources)

The stata survival manual by: (Electronic resources)

Introductory statistical procedures with SPSS by: (Electronic resources)

Probability and statistics with R / by: (Language materials, printed)

Beginning R = an introduction to statistical programming / by: (Electronic resources)

Elements of computational statistics by: (Language materials, printed)

Introductory statistics with R by: (Language materials, printed)

Using R with multivariate statistics / by: (Language materials, printed)