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Free Statistical Software

Free Statistical Software
Updated 02/13/2015 -- added MaxStat statistical software This page contains links to free software packages that you can download and install on your computer for stand-alone (offline, non-Internet) computing. They are listed below, under the following general headings: General Packages: support a wide variety of statistical analyses Subset Packages: deal with a specific area of analysis, or a limited set of tests Curve Fitting and Modeling: to handle complex, nonlinear models and systems Biostatistics and Epidemiology: especially useful in the life sciences Surveys, Testing and Measurement: especially useful in the business and social sciences Excel Spreadsheets and Add-ins: you need a recent version of Excel Programming Languages and Subroutine Libraries: customized for statistical calculations; you need to learn the appropriate syntax Scripts and Macros: for scriptable packages, like SAS, SPSS, R, etc. Curve-fitting & Modeling: Biostatistics and Epidemiology: Miscellaneous:

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Statistical Science Web: Free Statistical Programs Statistical Computing Software for Population Analysis. A directory of software sources for analysing animal abundance. Gordon's choices: BUGS. Data Preprocessing Tools Advance Macintosh Data Recovery Software and macintosh file retrieval tool for deleted or formatted apple macintosh hard drives. Mac Recovery Software is the most advanced Mac File Recovery application that recovers data from formatted, deleted or corrupted Mac partitions or External mac hard drives. Best Mac Data Recovery Tools is risk-free mac data recovery utility that recovers all important data lost accidental format, virus, file/directory deletion, or even a sabotage. Software fixes damaged mac hard disk and restore mac files within minutes.

Qualrus - The Intelligent Qualitative Analysis Program Qualrus is an innovative qualitative data analysis tool that helps you manage unstructured data. Use it to analyze interviews, organize field notes, measure survey responses & more... or download the free demo Fast, accurate codingQualrus learns your coding trends and offers relevant suggestions as you go. See your data clearlyVisual semantic network display helps you visualize relationships among codes.

wikiCalc Beta Test Home wikiCalc is currently released in late Beta test. This means that it is not fully tested, has bugs, but has all of the features that will be in the 1.0 release. It is quite useful in its own right and is able to create, publish, and maintain a wide variety of web pages. For example, this page and many of the ones it links to about wikiCalc were created with the wikiCalc Beta.

Do Faster Data Manipulation using These 7 R Packages Introduction Data Manipulation is an inevitable phase of predictive modeling. A robust predictive model can’t be just be built using machine learning algorithms. But, with an approach to understand the business problem, the underlying data, performing required data manipulations and then extracting business insights. Social Network Analysis Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA]. ONA allows you to x-ray your organization and reveal the managerial nervous system that connects everything. To understand networks and their participants, we evaluate the location and grouping of actors in the network.

EXCEL 2007: Descriptive Statistics for Univariate Data EXCEL 2007: Descriptive Statistics A. Colin Cameron, Dept. of Economics, Univ. of Calif. - Davis This January 2009 help sheet gives information on how to obtain Descriptive statistics for data using Data Analysis Add-in Statistics using individual function commands. Introduction to Principal Component Analysis (PCA) - Laura Diane Hamilton Principal Component Analysis (PCA) is a dimensionality-reduction technique that is often used to transform a high-dimensional dataset into a smaller-dimensional subspace prior to running a machine learning algorithm on the data. When should you use PCA? It is often helpful to use a dimensionality-reduction technique such as PCA prior to performing machine learning because: Reducing the dimensionality of the dataset reduces the size of the space on which k-nearest-neighbors (kNN) must calculate distance, which improve the performance of kNN. Reducing the dimensionality of the dataset reduces the number of degrees of freedom of the hypothesis, which reduces the risk of overfitting.

Intelligent Archive / Centre for Literary and Linguistic Computing / Research Institutes, Centres & Groups / Research / Humanities and Social Science / Schools Developed at the Centre for Literary and Linguistic Computing , University of Newcastle, Australia Hugh Craig R Whipp, Michael Ralston Introduction

Statistics With Excel? Excel is available to many people as part of Microsoft Office. People often use Excel as their everyday statistics software because they have already purchased it. Excel’s limitations, and its errors, make this a very questionable practice for scientific applications. For business applications where questions might be simpler and precision not as necessary, Excel may be just fine. Below are some of the concerns with using Excel for statistics that are recorded in journals, on the web, and from personal experience. Downloadable Sample SPSS Data Files Downloadable Sample SPSS Data Files Data QualityEnsure that required fields contain data.Ensure that the required homicide (09A, 09B, 09C) offense segment data fields are complete.Ensure that the required homicide (09A, 09B, 09C) victim segment data fields are complete.Ensure that offenses coded as occurring at midnight are correctEnsure that victim variables are reported where required and are correct when reported but not required. Standardizing the Display of IBR Data: An Examination of NIBRS ElementsTime of Juvenile Firearm ViolenceTime of Day of Personal Robberies by Type of LocationIncidents on School Property by HourTemporal Distribution of Sexual Assault Within Victim Age CategoriesLocation of Juvenile and Adult Property Crime VictimizationsRobberies by LocationFrequency Distribution for Victim-Offender Relationship by Offender and Older Age Groups and Location Analysis ExamplesFBI's Analysis of RobberyFBI's Analysis of Motor Vehicle Theft Using Survival Model

Introduction and guide A short video guide to this site and to the Caqdas Networking Project site. This site is designed for several different kinds of user who have questions about QDA (qualitative data analysis) and CAQDAS (Computer Assisted Qualitative Data AnalysiS) programs. The links below are for some of these categories of users. A video of a talk on online resources including the CAQDAS Networking site (part 1) and this website (part 3) and a look at Methodspace and a discussion (part 2).

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