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Statistics -- Data processing
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The concept ** Statistics -- Data processing** represents the subject, aboutness, idea or notion of resources found in **Merrimack Valley Library Consortium**.

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Statistics -- Data processing
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The concept

**Statistics -- Data processing**represents the subject, aboutness, idea or notion of resources found in**Merrimack Valley Library Consortium**.- Label
- Statistics -- Data processing

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- A gentle introduction to statistics using SAS Studio
- A recipe for success using SAS University Edition : how to plan your first analytics project
- Access data analysis cookbook
- Base SAS 9.4 procedures guide
- Base SAS 9.4 procedures guide
- Base SAS 9.4 procedures guide : statistical procedures
- Base SAS 9.4 procedures guide : statistical procedures
- Base SAS 9.4 procedures guide : statistical procedures
- Beginning R : an introduction to statistical programming
- Beginning R : the statistical programming language
- Data analytics with R Shiny
- Data mining with SPSS
- Data science in R : a case studies approach to computational reasoning and problem solving
- Data science primer
- Developing credit risk models using SAS Enterprise Miner and SAS/STAT : theory and applications
- Diversity heuristic
- Dynamic documents with R and knitr
- Essential statistics using SAS university edition
- Fundamentals of R programming and statistical analysis
- Getting started with Haskell data analysis : put your data analysis techniques to work and generate publication-ready visualizations
- Getting started with SAS Enterprise Miner 14.1
- Getting started with SAS Enterprise Miner for machine learning : learning to perform segmentation and predictive modeling
- Gnuplot in action : understanding data with graphs
- Hands-on statistical predictive modeling
- How to become a top SAS programmer
- Introduction to R programming
- Learn R for applied statistics : with data visualizations, regressions, and statistics
- Learn by example : statistics and data science in R
- Learning to program with R
- Machine learning 101 with Scikit-Learn and StatsModels
- Machine learning in R : automated algorithms for business analysis : applying K-Means clustering, decision trees, random forests, and neural networks
- Minitab cookbook : over 110 practical recipes to explore the vast array of statistics in Minitab 17
- Modern R programming cookbook : recipes to simplify your statistical applications
- Practical statistics for data scientists : 50 essential concepts
- Predictive modeling with SAS Enterprise Miner : practical solutions for business applications
- Python library series : the definitive guide to Statsmodels
- R cookbook
- R cookbook : proven recipes for data analysis, statistics, and graphics
- R for everyone : advanced analytics and graphics
- R graphics cookbook : practical recipes for visualizing data
- R in action : data analysis and graphics with R
- R in action : data analysis and graphics with R
- R in action : video edition
- R programming LiveLessons
- R programming by example : practical, hands-on projects to help you get started with R
- R programming fundamentals : deal with data using various modeling techniques
- R projects for dummies
- R statistics cookbook : over 100 recipes for performing complex statistical operations with R 3.5
- SAS 9.4 ODS graphics procedures guide
- SAS 9.4 SQL procedure : user's guide
- SAS 9.4 SQL procedure : user's guide
- SAS 9.4 functions and CALL routines references
- SAS 9.4 language reference concepts
- SAS 9.4 macro language reference
- SAS 9.4 output delivery system : user's guide
- SAS and Hadoop technology : overview
- SAS essentials for statistics
- SAS for R users : a book for data scientists
- SAS for dummies
- Speaking 'R' : the language of data science
- Stata advanced : beyond the basics
- Stata fundamentals
- Statistical analysis using Excel LiveLessons, Volume 1
- Statistical analysis using Excel LiveLessons, Volume 2
- Statistical analysis with Excel for dummies
- Statistical analysis with Excel for dummies
- Statistical analysis with R
- Statistical application development with R and Python : power of statistics using R and Python
- Statistical data cleaning with applications in R
- Statistical programming With SAS/IML software
- Statistical programming in SAS
- Statistical programming in SAS
- Statistics for Six Sigma made easy!
- Statistics fundamentals
- Statistics series : Stats test your knowledge
- The art of R programming : tour of statistical software design
- The book of R : a first course in programming and statistics
- Using R for statistics
- What's new in SAS 9.3
- What's new in SAS 9.4

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`<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.mvlc.org/resource/JQqUC_FwUdk/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.mvlc.org/resource/JQqUC_FwUdk/">Statistics -- Data processing</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.mvlc.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.mvlc.org/">Merrimack Valley Library Consortium</a></span></span></span></span></div>`