### RStudio

(449)4.5 out of 5RStudio is a family of powerful and cost-effective undelete and data recovery software.#### Reviewers say compared to IBM SPSS Statistics, RStudio is:

Easier to set upEasier to adminEasier to do business with### Stata

(93)4.3 out of 5Stata puts hundreds of statistical tools at your fingertips. For data management, statistical analysis, and publication-quality graphics, Stata has you covered.#### Reviewers say compared to IBM SPSS Statistics, Stata is:

Better at supportBetter at meeting requirementsMore usable### SAS Base

(49)4.2 out of 5SAS Base is a programming language software that provides web-based programming interface; ready-to-use programs for data manipulation, information storage and retrieval, descriptive statistics and reporting; a centralized metadata repository; and a macro facility that reduces programming time and maintenance headaches.#### Reviewers say compared to IBM SPSS Statistics, SAS Base is:

Better at supportMore expensiveEasier to do business with### JMP

(48)4.3 out of 5JMP combines powerful statistics with dynamic graphics, in memory and on the desktop. Its interactive and visual paradigm enables JMP to reveal insights that are impossible to gain from raw tables of numbers or static graphs.#### Reviewers say compared to IBM SPSS Statistics, JMP is:

Easier to set upEasier to do business withEasier to admin### SAS/STAT

(25)4.0 out of 5SAS/STAT includes exact techniques for small data sets, high-performance statistical modeling tools for large data tasks and modern methods for analyzing data with missing values.#### Reviewers say compared to IBM SPSS Statistics, SAS/STAT is:

Easier to do business withBetter at supportBetter at meeting requirements### GNU Octave

(24)4.1 out of 5GNU Octave is an open-source mathematical modeling and simulation software very similar to using the same language as Matlab and Freemat.#### Reviewers say compared to IBM SPSS Statistics, GNU Octave is:

Better at supportMore usableBetter at meeting requirements### KNIME Analytics Platform

(24)4.3 out of 5KNIME® is an open source data analytics, reporting and integration platform.#### Reviewers say compared to IBM SPSS Statistics, KNIME Analytics Platform is:

Better at supportEasier to set upEasier to admin### NumXL

(17)4.8 out of 5NumXL is a suite of time series Excel add-ins. It transforms your Microsoft Excel application into a first-class time series software and econometrics tool, offering the kind of statistical accuracy offered by the far more expensive statistical packages.#### Reviewers say compared to IBM SPSS Statistics, NumXL is:

Better at supportMore usableBetter at meeting requirements### Scilab

(11)4.8 out of 5Scilab is a free open-source software for numerical computation and simulation similar to Matlab/Simulink.#### Reviewers say compared to IBM SPSS Statistics, Scilab is:

Better at meeting requirementsBetter at supportMore usable### eviews

(6)3.8 out of 5EViews offers academic researchers, corporations, government agencies, and students access to statistical, forecasting, and modeling tools through an object-oriented interface.### ROOT

(4)4.3 out of 5ROOT is a modular scientific software framework that provides all the functionalities needed to deal with big data processing, statistical analysis, visualisation and storage, it is mainly written in C++ but integrated with other languages such as Python and R.### G*Power

(2)4.8 out of 5G*Power is a tool to compute statistical power analyses for many different t tests, F tests, χ2 tests, z tests and some exact tests. G*Power can also be used to compute effect sizes and to display graphically the results of power analyses.### SAS Visual Statistics

(2)3.8 out of 5Multiple users can explore data, then interactively create and refine predictive models. Distributed, in-memory processing slashes model development time, quickly surfacing valuable insights you can act on.### nQuery Sample Size Software

(2)4.5 out of 5nQuery is the world's most trusted sample size calculation software. nQuery boasts an extensive list of features for sample size calculation and power analysis.### PS Power and Sample Size

(1)0.5 out of 5PS is an interactive program for performing power and sample size calculations that may be downloaded for free. It can be used for studies with dichotomous, continuous, or survival response measures. The alternative hypothesis of interest may be specified either in terms of differing response rates, means, or survival times, or in terms of relative risks or odds ratios. Studies with dichotomous or continuous outcomes may involve either a matched or independent study design. The program can determine the sample size needed to detect a specified alternative hypothesis with the required power, the power with which a specific alternative hypothesis can be detected with a given sample size, or the specific alternative hypotheses that can be detected with a given power and sample size.### Mass++

This software is used to analyze mass spectrometry data.### AnalyzerPro

AnalyzerProis a productivity software application for both low and high resolution LC-MS and GC-MS data with support for multiple vendors’ data. This comprehensive post-processing utility provides optimized workflows for sample-to-sample comparison, target component analysis, quantitation and library searching for data generated from any LC-MS and GC-MS platform.### Mnova MS

Provides a common interface for different vendor data and automates all functionality such as data importing and display, integration, background subtraction, display of extracted mass chromatograms, molecule match, enumeration of molecular formulae, etc.### AcaStat

AcaStat is a data analysis and summary statistics package. Helps to import tab or comma delimited data files or use drag and drop from a spreadsheet. Format, set missing values, and recode data.### Appricon Analysis Studio

Appricon Analysis Studio is a statistical analysis software that provides an end to end model generation process designed for fast development, analysis, and deployment.

#1

"Great IDE for programming in R: Rstudio is one of the few IDEs that exist for programming in R because it is a very recent language and still little known, for this the editor Rstudio although it has little development time I think it is an application that is very well built and that works suitably for the creation of large projects using R as a language.
Technically it is very similar to other IDE created for other languages so if you are a programmer you probably do not find it hard to understand. The application in terms of configuration seemed complete and has all the features that one needs to build an efficient workspace in any IDE.
On the one hand it allows the change of appearance to a darker theme, something that we appreciate those of us who have a sight that gets tired easily when programming in environments with a lot of light. It also has a very useful command console for the execution or compilation of the project."

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#2

"Stata - You should use, no questions asked!: Stata is my favorite statistical software, by far. I have used SPSS, SAS and R, and Stata combines ease of use with powerful capabilities. SPSS is a little clunky, SAS is not as intuitive and R isn't standardized. I definitely recommend Stata for any scientist looking to perform his own statistics."

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#3

"Base SAS - Easy to learn with strong learning support, but high cost is a deal-breaker: Base SAS is a good entry-level application for new analysts. Its biggest advantages are the excellent online help system and dedicated customer support it provides on even the smallest aspect of the tool. Also, Base SAS works very well for simple data manipulations, exploratory data analysis and bi-variate analysis, although building complex models is not possible. Building complex machine learning models requires an upgrade to SAS-Stat. "

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#4

"Review de JMP: JMP es una herramienta útil para diseñar experimentos y analizar datos. Su interfaz visual lo hace extremadamente fácil de usar y quizá sea ideal para cuando se comienza a enseñar a un principiante a ejecutar diversos análisis. JMP es mucho más fácil de usar que SAS o R, ya que no se requiere programación. La entrada de datos y el análisis son absolutamente sencillos y con pocos clicks tienes todo listo.
Una de sus funciones que más me gusta es las posibilidades que ofrece a la hora de crear gráficos arrastrando las variables de interés."

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#5

"Research made easy! : I used another application similar to this called SPSS while in college but it was harder to use. I switched over to this software when I started working in the VCU research lab and was able to make sense of my data iin half the amount of time it took me with SPSS due to the easy interface and instructions on how to quantity and explain data sets. "

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#6

"My Experience With Gnu Octave: Octave is the best utility software which i have used for starting my machine learning.It is very easy to use and it is also very less demanding on cpu so,we can use it with an uninterrupted experience.It is very good for Algorithm development and it is very easy to do data visualization on GNU Octave.It is also very easy to do vectorization for data science purposes.
The CLI version is very light on my computer so it uses very ram and cpu speed.It's is the best software to use use when we enter the field of Data Science and Machine Learning.Everyone must have some experience with GNU Octave."

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#7

"Powerful & Easy to Use Predictive Analytics / Data Mining: KNIME offers a delightful blend of power and ease-of-use. It uses a workflow (flowchart) interface. It offers you a collection of icons that represent steps in your analysis. You position each icon in a diagram and connect them with arrows that represent the flow of data or models from step to step. Double-clicking on an icon will open a dialog box allowing you to set the parameters of how that step should run.
You can document the workflow by clearly labeling each step, and by color coding entire sections of the diagram. As a result, you can look at another person's analysis and quickly get the big picture of what was done. If a diagram gets too complex, you can select a whole section of it and collapse it into a "metanode" so that one icon then represents all the steps. It's also easy to rerun an analysis on new data by simply changing the node(s) that read in data. Note that KNIME does not have a scripting language, nor does it need one.
I particularly like the company's view of open source software. The full desktop version of KNIME is free and open source, regardless of how much data you have. Its closest competitor price-wise is RapidMiner, which is free only if you have fewer than 10,000 cases. KNIME also offers excellent integration with a wide range of other open source software such as: Python, R, Spark, and even ImageJ for image analysis.
The server version of KNIME has a commercial license, i.e. not free. The company also sells software to let work groups share node libraries. For example, if I develop a new node in, say, R, and email it to everyone, then when I improve it, I'll have to email it again. Everyone using it would have to edit their work flows, but at least that's a free solution. However, if we purchase the collaboration extensions, I would make a change to the shared node, and everyone's work would be updated automatically. I appreciate having so much control over what to spend on a KNIME solution."

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#8

"More Than your Average Spreadsheet: I love the compatibility of this software as well as the ease of use. "

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#9

"Scilab: Scilab(Scientific Laboratory) is free and open source software for numerical computation providing a powerful computing environment for engineering and scientific applications. For usual engineering and science applications including mathematical operations and data analysis. Graphics functions to visualize, annotate and export data and many ways to create and customize various types of plots and charts. Algorithms to solve constrained and unconstrained continuous and discrete optimization problems."

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#10

"A little unfriendly but plenty powerful enough for me: Flexibility with model creation/testing."

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#11

"A large package for every need - hard to learn easy to user: There are two main points about ROOT - its open source and its a product of generations of scientists. Descending from Paw (still in FORTRAN), ROOT was the C++ version for the comprehensive data analysis first for the high energy physicists and then for the general programming community to use. Most attractive features include cross-platform, ability to call from Python or R, JS-viewer and the GUI libraries that can be easily incorporated into any c++ design (so that program is easily portable from Win to POSIX and back and its the same libraries being called)."

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#12

"G*Power for Independent Research: G*Power was straight forward, easy to use, and user friendly for someone who is not a statistics expert. It allowed me to conduct an a priori power analysis to determine an appropriate sample size for my research study. I did not have the ability to hire a statistician to do this for me, so this resource was really helpful. The website also provides a ready-to-use citation."

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#13

"Very good product: I have used a variety of SAS programs to complete my tasks. I really enjoy using Visual Statistics because it helps me in creating models for my complex queries and hypotheses that I want to test."

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#14

"nQuery helped me to solve my problems and taught me about sample size calculation: There are some topics that I appreciate about nQuery: one of them is the facility to use nQuery for sample size calculation. Another one is the possibility to access the webinars, how-to videos, tutorials and training courses. I also appreciate that people working at Statsols (the provider of nQuery) have the skills and determination to help me when I need it and do that in a friendly way."

#15

"Hated software: I don’t like this software at all it’s not good "

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#20

Be the first to review Mass++!

#20

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#13

Be the first to review Mnova MS!

#17

Be the first to review AcaStat!

#15

Be the first to review Appricon Analysis Studio!