Statistical software

• R and R-Studio – are separate packages – you will need to install R first. R Studio is an add-on that make R easier to use for beginners.
• R-Commander – first steps with R using GUI…
• Rattle – A Graphical User Interface for Data Mining using R.
• Statistica (PL and ENG) – for data analysis using GUI.
• QGis and Geoda – for spatial data modeling and geovisualizations. 
• DAD 4.6 oraz DASP – Distributional Analysis Stata Package and stand-alone DAD version. 
• Tableau Public – It is a data visualization tool that allows you to easily create interactive data visualizations. Tableau Public is a free version of Tableau Desktop and allows you to publish and share visualizations online.
• Gephi – This is a social network analysis and visualization tool. Gephi offers many features such as centrality analysis, community detection, network visualization, etc.
• OpenRefine – This is a data cleaning and processing tool. OpenRefine offers many functions for processing and organizing data, such as merging, splitting, filtering, extracting, etc.
• Orange3 – This is a data analysis platform that offers many functions such as data visualization, data processing, statistical analysis and machine learning. Orange3 has an easy-to-use graphical interface and many built-in modules.
• Trifacta – This is a data processing tool that offers an easy-to-use graphical interface and many functions for cleaning and processing data. Trifacta makes it easy to combine and process data from different sources.
• Apache Zeppelin – This is a data analysis platform that allows you to easily create and share code notes. Zeppelin offers multiple interpreters for programming languages such as R, Python, SQL, Spark, etc.
• Links to other statistical packages are available in the “links” section.

Statistical tables – necessary to perform the estimation procedure, parametric and non-parametric tests without the use of computer packages (although in some cases of non-parametric tests are still needed) – here.

• Python – It is also a programming language and environment that offers many libraries for data analysis, such as Pandas, Numpy, Matplotlib, Scikit-learn, TensorFlow, etc.
• Apache Hadoop – This is an open source software that allows processing of large data sets on clusters of computers. Hadoop includes many modules, such as MapReduce, HDFS, YARN, etc.
• Apache Spark – This is a data processing engine that runs on clusters of computers. Spark offers many modules, such as Spark SQL, Spark Streaming, MLlib, GraphX, etc.
• Apache Cassandra – This is a NoSQL database that is designed to store large data sets on clusters of computers.
• Apache Kafka – This is a platform for processing streaming data. Kafka enables real-time data processing and integration of different systems.
• Elasticsearch – This is a search engine and analytics engine that enables fast data search and analysis.
• Kibana – This is a data visualization tool that integrates with Elasticsearch. Kibana allows you to create interactive visualizations and dashboards.
• Grafana – This is another popular data visualization tool that allows you to create interactive dashboards.
• KNIME – It is a data analytics platform that enables easy creation of workflows (workflows) for data processing and analysis. KNIME offers many built-in plug-ins and modules, such as visualizations, text analytics, machine learning, etc.
• Weka – This is a machine learning tool that offers many machine learning algorithms and data visualization tools.
• Orange – This is a data analysis and machine learning tool that offers easy-to-use graphical interfaces and many modules and plugins.
• RapidMiner – This is a data analysis platform that offers easy-to-use graphical interfaces, data processing modules and machine learning algorithms.
• Talend – This is an integration platform that makes it easy to connect, process and analyze different data sources. Talend offers many built-in modules and tools for data integration and analysis.