JMP product informationStatistical analysis software, free for students, faculty and staff from University Information Services.
Microsoft Excel product informationStatistical analysis software, free for faculty and staff from University Information Services as part of Microsoft Office.
NVivo product informationQualitative analysis software, available for purchase through University Information Services.
SAS product informationStatistical analysis software, free for academic users through University Information Services.
SPSS product informationStatistical analysis software, available free to faculty and staff for home install through University Information Services.
STATA product informationStatistical analysis software, free for faculty and staff through University Information Services.
Free and Open Source Statistical Analysis Tools
Google SheetsGoogle Sheets is a free, cloud-based spreadsheet application. It provides built-in formulas, pivot tables and conditional formatting options. It also allows easy collaboration with other users.
JASPJASP is an open-source project supported by the University of Amsterdam. It offers standard analysis procedures in both their frequentist and Bayesian form.
PythonPython is an open source programming language with excellent support for statistical analysis.
R Project for Statistical ComputingR is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS.
RStudioRStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management. RStudio is available in open source and commercial editions and runs on the desktop (Windows, Mac, and Linux). You must install R before you install RStudio.
Which Stats Test?This wizard provided as part of Sage Research Methods Core helps researchers select appropriate statistical tests by asking them a series of questions about their empirical research task.
Software Guides
Excel Data Analysis for Dummies by Paul McFedriesWith Microsoft Excel, you can, well, excel at data analysis. And Excel Data Analysis For Dummies can help, with clear and easy explanations of the mountain of features for creating, visualizing, and analyzing data. PivotTables, charts, what-if analysis, statistical functions.
Call Number: eBook
ISBN: 1119844428
Publication Date: 2022
Hands-On SAS for Data Analysis by Harish GulatiAfter a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats.
Call Number: eBook
ISBN: 9781788839822
Publication Date: 2019
Learn R for Applied Statistics by Eric Goh Ming HuiLearn R through structured and optimized, real project examples. Covers applied statistics using R, first by learning R basics, then applying to data visualizations, descriptive, inferential and regressions-based statistics.
Call Number: eBook
ISBN: 9781484242001
Publication Date: 2019
Python Data Analysis by Avinash Navlani; Armando Fandango; Ivan IdrisUnderstand data analysis pipelines using machine learning algorithms and techniques with this practical guide. Prepare and clean your data to use it for exploratory analysis, data manipulation, and data wrangling. Discover supervised, unsupervised, probabilistic, and Bayesian machine learning methods.
Using Stata for Quantitative Analysis by Kyle C. LongestUsing Stata for Quantitative Analysis offers a brief but thorough introduction to analyzing data using Stata software. Kyle C. Longest teaches the language of Stata from an intuitive perspective, allowing students with no experience in statistical software to start working with data quickly and complete a basic quantitative research project from start to finish.
Excel Data Analysis for Dummies by
With Microsoft Excel, you can, well, excel at data analysis. And Excel Data Analysis For Dummies can help, with clear and easy explanations of the mountain of features for creating, visualizing, and analyzing data. PivotTables, charts, what-if analysis, statistical functions.
Hands-On SAS for Data Analysis by Harish Gulati
After a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats.
Learn R for Applied Statistics by
Learn R through structured and optimized, real project examples. Covers applied statistics using R, first by learning R basics, then applying to data visualizations, descriptive, inferential and regressions-based statistics.
Python Data Analysis by
Understand data analysis pipelines using machine learning algorithms and techniques with this practical guide. Prepare and clean your data to use it for exploratory analysis, data manipulation, and data wrangling. Discover supervised, unsupervised, probabilistic, and Bayesian machine learning methods.
SPSS Statistics Workbook for Dummies by
Practice making sense of data with IBM's SPSS Statistics software. SPSS Statistics Workbook for Dummies gives you the practice you need to navigate the leading statistical software suite.
Using Stata for Quantitative Analysis by
Using Stata for Quantitative Analysis offers a brief but thorough introduction to analyzing data using Stata software. Kyle C. Longest teaches the language of Stata from an intuitive perspective, allowing students with no experience in statistical software to start working with data quickly and complete a basic quantitative research project from start to finish.