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Top 10 Statistics Tools to Get Better Data Insights

Want to know the best statistics tools for data analytics and data science? Here we have given the detailed overview of statistics tools.

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Top 10 Statistics Tools to Get Better Data Insights

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  1. Top 10 Statistics Tools to Get Better Data Insights WWW.STATANALYTICA.COM

  2. Today's Discussion • Key Topics • Overview • Statistics tools for data analysis • SPSS (IBM) • R • Microsoft Excel • Tableau • Minitab • Statistics Tools For Data Science • Apache Hadoop • SAS • RapidMiner • Python • MATLAB (The Mathworks) • Conclusion

  3. Overview • Statistics tools are playing a crucial role in running our life. We performed various tests on data to get valuable results from the data. We can get more information from that data if we do the proper experiment on the data. Every analysis depends on appropriate planning and execution. To win the data experiment’s battle, we need to make sure that we are analyzing the data in the right ways that will help us find critical insights of data. • Analyzing the data is crucial in many aspects of our life. There are plenty of statistics tools in the world that are designed for the statistical analysis and make this process super smooth and easy for the users. Here we are going to discuss the topmost statistics tools useful in many different aspects of our lives.

  4. Statistics tools for data analysis SPSS (IBM) • SPSS is the number 1 statistics tool for human behavior research. As the name suggests, it stands for Statistical Package for the Social Sciences. That is why the statisticians used it widely for data analysis purposes. Apart from that, you can also use the GUI for the graphical depictions of results. You can also create a customized script for automatic analysis. It is one of the most potent statistics tools for advanced statistical processing. SPSS Inc introduced it, but later on, it was acquired by IBM in the year 2009. Therefore the SPSS is known as IBM SPSS.

  5. R • R is one of the best open source statistics tools for data analytics. It is use by statisticians for research purposes. It offers excellent toolboxes that are available for a vast range of applications. R is an open-source programming language, and it has a severe learning curve. It is not for beginners, and you need to have good command over coding to get started with R. It was developed at Bell Laboratory by John Chambers and colleagues. R offers a wide range of statistics and graphical techniques i.e., linear, nonlinear modeling, classical statistics test, time series analysis, and many more.

  6. Microsoft Excel • MS Excel is one of the best statistical tools for data analysis. It offers cutting edge solutions to data analytics professionals. You can use it for data visualization as well as simple statistics. It is the best statistical tool for those who want to perform basic data analysis techniques on their data.

  7. Tableau • Tableau is one of the most powerful data visualization software. The data visualization technique is widely used in data analytics. Now it is the part of Salesforce that is known for its high-end CRMs in the world. You can create the best data representation of the massive amount of data in Tableau within a few minutes. Therefore it helps the data analyst to make quicker decision making. It has an enormous amount of online analytical processing cubes, cloud databases, spreadsheets, and many more. It also offers the drag and drop interface to the users. Thus the user needs to drag and drop the data set sheet in Tableau and set the filters as per their requirements.

  8. Minitab • It is not the most popular data analysis statistics tool. But you can do the basic as well as some advanced statistical techniques using Minitab. You can also execute commands in MATLAB with the help of GUI as well as scripted commands. It was developed in the year 1972 at Pennsylvania State University. The researcher’s Barbara F. Ryan, Thomas A. Ryan, Jr., and Brian L. Joiners are the creators of this tool. In earlier days, it was known as OMNITAB. In this way, it will enable you to find a solid answer to the most challenging questions.

  9. Statistics Tools For Data Science Apache Hadoop • When it comes to data science, then Apache Hadoop is considered as the best and most reliable statistics tool. It is open-source software that is used for scalable computing. Apache Hadoop is part of the Apache software foundation under Apache license 2.0 and can solve the most complex computational problems. It is also best at data-intensive tasks. Hadoop has the best functionality that it doesn’t send the larger files directly to the node. It splits the large files into small chunks and then sends it over to the node with different instructions.

  10. SAS • SAS is one best statistics tool for data science. It is also playing a crucial role in the data science industry. You can use it either as the GUI or create your script for the advanced level statistics analysis in data science. It can produce the best graphs and charts. You can also extend the functionality of SAS using the coding feature.

  11. RapidMiner • RapidMiner is yet another best tool for data science. It offers a platform that is quite helpful in data preparation, machine learning, and predictive model deployment. You can create the data model from the initial stage to the last step easily with RapidMiner. It offers a complete data science package. It is best for machine learning, deep learning, text mining, as well as predictive analytics.

  12. Python • Python is one of the best programming languages in the world. I have mentioned it in this blog because it can work seamlessly with the statistics. It is the most straightforward programming language and offers lots of packages and models for statistics and data science. Python is a high-level, general-purpose programming language. It was created by Guido Van Rossum and released in 1991. It is the best statistics tool for data science. You can fulfill all your statistics requirements by using Python for data science.

  13. MATLAB (The Mathworks) • MATLAB is the best statistics analysis tool and the best statistics programming language in the world. It offers a variety of tools in its toolbox that makes it quite easy to use programming languages. You can do the most sophisticated statistical analysis with MATLAB i.e., EEG data analysis. You can extend MATLAB functionality with the help of add ons for toolboxes. It offers a multi-paradigm numerical computing environment. It means that you can do the procedural as well as object-oriented programming with MATLAB. Math Works developed it. It is best for matrix manipulation: data function plotting, algorithms implementations, user interface creations, and many more. You can also run the program of other programming languages with MATLAB all because of its interfacing function.

  14. Conclusion • We have seen that there are plenty of statistics tools for data analysis, as well as data science. Even there are some more statics tools available in the world that can fulfill your requirements for data analysis and data science. Even some of the statistics tools online are the alternative to these statistics tools that I have mentioned above. But all these tools are best in their class. You can use any one of these tools without having the second opinion.

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