Statistical software are analytical tools which are used for the statistical analysis of gathering, organization, analysis, interpretation of data. In world that is filled with uncertainty, business statistics play a big part in business and this in turn assist managers to make an informed decision in areas like the quality assurance, production, and operations, financial analysis, auditing and econometrics among others.
Business managers get to gather, analyze and make inferences from a huge amount of data. Statistical analysis enables them to discover patterns and trends of consumers and other useful information that assist them in making decisions.
Statistical analysis assists businesses managers to measure the performance of the workers and helps to improve the products and services produced. Managers can forecast data with the help of statistical analysis and also make correct future predictions about what could occur to the financial industry.
Simply put, statistical analysis tools assist with statistics-based collection and analysis of data to supply science-based insights into patterns and trends. They often use statistical analysis theorems and methodologies, like multivariate analysis and statistical analysis to perform data science.
Now let’s properly define what statistical Analysis means.
What is Statistical Analysis Software?
Statistical Analysis is referred to the science of collecting, exploring and presenting large amounts of data to get underlying patterns and trends and these are applied daily in research, industry and government to become more scientific about decisions that is required to be made. Statistical Analysis tools help in analysis of data.
This software works by either reading data directly from an excel spreadsheet, the user can enter the information on to the software, or the user can use a specialized data entry software to capture data.
In turn, the statistical analysis software then manipulates the data they possess to get patterns which can help the users discover business opportunities and increase their business revenues and profits. This assists users with predictive analytics, data management, business intelligence and statistical methods.
Benefits of Statistical Analysis software
Statistical Analysis can assist users with business intelligence in many various ways. As business intelligence is the practice of collecting and analyzing data and reworking it into actionable insights, statistics add more value to your business’ proprietary data. Statistical analysis also gives insight into how effectively your business is working, and assist you think ahead with predictive analytics models supported by historical data.
Statistics are often difficult to perform, but with the proper BI tools, it is often a breeze.
So, what are the advantages of employing a statistical analysis tool for business intelligence?
- It increases efficiency from streamlined and automatic business data analysis workflows
- Businesses get good returns with more accurate predictions that is supported by machine learning, statistical algorithms and hypothesis testing
- Easy customization allows you to make sure the software correctly processes the information and results you would like to get
- It also grants access to larger databases which reduces sampling error and enables more precise conclusions
- Empowers you to get data-driven decisions confidently
Points to consider when purchasing a statistical Analysis software
Before purchasing a statistical analysis tool, You should’ve the following points in mind:
What type of data does one get to analyze?
Having to use a complicated advanced tool like statistical analysis tool for easy data sets is impractical; statistical analysis tools work best with complicated sets of quantitative data. If for an example your business analysis needs are less demanding, an analytics tool could also be more suitable for you.
Products tend to supply different ranges of statistical theorems and algorithms, but some users may only get to use a small percentage of those functions. If you’ve got a huge amount of data to research on, you’ll want to option for Statistical tool built to handle large data sets with speed. You ought to search for a tool that performs precisely on the exact data analyses you would like it to. Who will use the tool?
Before you consider purchasing a statistical analysis tool, ask yourself if your analysts are experts, amateurs, or somewhere in between? Will they need to analyze data continuously in real-time, or will they be doing more statistical analysis on an ad-hoc self-service basis? Are they primarily data analysts or scientists?
The statistical analysis tool you purchase should meet the requirements of the person using it, so confirm to settle on a package that does exactly what your user needs it to.
What’s the ease of use?
Statistical analysis tools are by no means easy, and lots of statistical software platforms are often confusing and downright unintelligible to the typical user. Some tools even have a better learning curve than others, making them harder to master. After considering who are going to be using the tool, determine what their level of experience with statistics is.
Expert data scientists will feel reception crunching numbers with equations and programming languages, but novice users may feel overwhelmed with a software that presents a format that is like employing a more familiar menu-based interface.
Do your engineers need a strong statistical analysis platform with powerful coding capabilities, or do your analysts need an easier statistical tool which will display basic models, or does one need something in between?
How will your tool integrate together with your existing business solutions?
putting into consideration the interoperability and integration capabilities of prospective statistics software is a crucial step in the vetting process. While statistical analysis tools assist businesses derive deeper insights from their data, they’re often just a cog in the machine of their technology ecosystems. More frequently than not, your business may have only one solution to deal with its analytical needs.
Will the new solution work well with others? If your business currently uses the other programs, it is often advisable to use a statistical analysis tool that supports the databases, file formats and frameworks of your existing solutions.
What quality of graphics does one need?
Some statistical analysis tools are feature-packed with data visualization options, while others generate graphics that are far more bare-bones, with less customization available option.
Ask yourself if your business will prefer interactive or static visualizations? Would you like your statistical analysis software to supply visually appealing graphics outright? Or if you’ll output the graphics to a different program, can the software export in the quality you prefer?
If visualization is a crucial prerequisite for your business, it’s certainly worthwhile to look into the graphical output capabilities of your would-be statistics software.
What is your budget like?
Statistical analysis packages come in price ranges from free for open-source tools like Python and R, to thousands of dollars per license for more robust offerings. Would you like only one license, or several? There also are many statistical analysis platforms that have academic versions available to students and teachers at a reduced rate.
The cost of your statistical analysis tool will affect which statistical analysis software is best for your business.
Does the Statistical analysis tool have documentation or support?
Nothing is as frustrating as a solution tool creating more problems than it solves. It’s much easier to use programs with comprehensive documentation than ones where you’ve got to work it out yourself. Before choosing a statistical analysis tool, confirm that your tool of choice comes with documentation that your users can understand, or at the very least, access to technical support should have questions.
These are a number of the points to think about before purchasing a statistical analysis tool for your business.
The 5 best statistical analysis tools for your business
Since we’ve highlighted the points to loot out for when purchasing a Statistical analysis tool, Let’s dive into the best statistical analysis tools for your business.
Below are a number of the ones we’ve selected:
This is a statistical analysis tool that delivers statistical analysis, data visualizations and data analytics to assist users improve data-driven solutions. It can analyze all types of datasets, from small to large, and automates statistical calculations and the creation of graphs, allowing users to place their focus on data analysis. Minitab also allows users to customize menus and toolbars, preferences, profiles and powerful scripting macro capabilities.
Minitab is available for download on Windows or Mac operating systems only, with no SaaS or mobile options.
Features of MiniTab
To have and experience one-click import process, Minitab takes the diligence out of data to prep and allow users to quickly sort through and transfer their data.
Descriptive and Inferential statistics offer
Using this statistical tool, you can carry out analysis on data sets and identify distributions, correlations, outliers and missing values. With a spread of analyses at their command which includes; analysis of variance, regression, experiment design, variable control charts, reliability/survival, users can probe their data with any number of statistical tests.
Analytics are Predictive
With an advanced predictive analytics and machine learning algorithms at its disposal, MiniTab takes a deeper dive into data. The tools for logistic regression, statistics analysis, correlational analysis and variables that users can take a sneak peep into future possibilities.
Visualizations of Graphics
Minitab also generates a good range of graphics to display their findings, including scatterplots, matrix plots, boxplots, histograms, charts, statistics plots, probability plots and more. These set of graphics automatically update just as the data changes, and users can dig deeper on their visualizations with a brushing feature that zooms into sections of their graphs.
Users can also export their graphics to TIF, JPEG, PNG, BMP, GIF, or EMF files, or on to Microsoft Word or Powerpoint for sharing with other apps.
Another point is that this statistical analysis tool offers Minitab Assistant, which assists to guide its users through the analytical process and also enable them interpret and present their results. These features an interactive decision tree that enables users pick the right statistical analysis for his or her needs. There is also a step-by-step support which includes; definitions of terms and illustrated examples, to assist provide better context and clearer guidelines for effective, accurate analysis.
With simple dialogs and fields that dynamically change supported input, the assistant streamlines the statistical analysis process and returns a series of reports that are easy to know which help users interpret their results confidently.
Provides support and documentation
Using this tool, you get access to free Quick Start resource that introduces users to the platform’s basic functions and navigation. Also, there is a provision for animated lessons and hands-on exercises, sold separately as Quality Trainer e-Learning courses. There’s also a number of technical documentations, guides, blogs and webinars, available on the Minitab website.
Pricing for Minitab starts from $29 for 6 months and increases to about $45 or more annually for extra features.
Stata statistical analysis tool is designed for use for data scientists, used for data manipulation, exploration, visualization and statistical analysis. With both a graphical interface and instruction structure, Stata is made available to users with or without coding knowledge.
Stata is used by researchers in many fields these includes; behavioral science, education, medical research, economics, politics, public policy, sociology, finance, business and marketing. It also has some level of graphics customization, as users can customize the dimensions of the text, markers, margins and other elements in their graphics.
Stata is out there in four different packages, which can be used to analyze different numbers of variables and need more or less memory to run:
Stata/MP: the fastest and largest version of Stata
Stata/SE: Stata for giant datasets
Stata/IC: Stata for mid-sized data sets
Stata for numeric: Stata for embedded and web applications
Feature of Stata
Stata provides users with the necessary tools they need to perform data science. These includes a broad suite of statistical functions which is not limited to linear models, panel/longitudinal data, statistics analysis, survival analysis, Bayesian analysis, selection models, choice models, extended regression tools and generalized linear models, finite mixture models, spatial autoregressive models, nonlinear regression and more.
Analysis for prediction
Stata assists users anticipate the longer term. It’s lasso tools allow users to predict outcomes, characterize groups and patterns and perform inferential statistics on data analysis.
Users are able to automate reports, which can be created in Word, Excel, PDF and HTML files directly. The design of the reports is mostly customized using Markdown text-formatting language.
Advanced Programming with Reproducibility
Also among the features is the Stata programming languages ado and Mata, users also can incorporate C, C++ and Java plug-ins via a native API. Stata has Python integration included in it, so users can embed and execute coding directly within the program.
Among the features of Stata is integrated versioning, that permits scripts and programs written years ago to still add modern versions of its platform. Created from version 1.0 with reproducible research in mind, scripts written in 1985 will run and produce the same leads to 2020 and 2050 and beyond. Users are freed from the shackles of keeping and maintaining multiple installations of various versions of Stata, because the latest version of Stata will always be ready to understand older code and datasets, eliminating broken scripts so users can easily make changes to operating systems or jump to a version of Stata many versions ahead.
Quality Graphics publication
Stata enables users to get uniquely styled, high-quality graphics in many various styles with point-and-click ease. Users can easily create bar charts, box plots, histograms, spike plots, pie charts, scatterplots, dot charts and more. Users also can write scripts to supply graphs with blocks for reproducible manner. Graphics are mostly exported to a spread of formats: EPS or TIFF for publication, PNG or SVG for online distribution, or PDF for viewing and sending. With a graph editor, users can easily customize how their visualizations look, by adding, moving, modifying or removing elements, with the choice to record changes and apply those edits to other graphs.
Export and Import of Data is easy
Users can easily have access to import and export data from a myriad of formats, including XLS, CSV, spreadsheets, SQL sources, ASCII files, text, etc. Stata also can import files from SAS or SPSS, ensuring its compatibility with other popular statistical software.
Technical Support and Resources
Stata technical support is liberal to registered users, allowing an additional benefit on top of user subscriptions. The features a dedicated group of programmers and statisticians who can answer users’ technical questions, assist in graphics customization and clearly explain the ins and outs of statistical modeling.
It has a Youtube channel filled with free video resources, an informative blog, free webinars including a frequently offered “Ready. Set. and Go stata.” webinar on getting started with Stata, also as a spread of cheap online NetCourses that enable users maximize the return on their investment.
A free trial of Stata is out there for patrons and users and can also contact Stata for an extra price quote.
SPSS Statistics is a statistical software from IBM which quickly crunch large data sets to supply insights for decision-making and research. Consistent with IBM’s website, over 75% of reviewers rank SPSS as an easy to use, making it the best choice for new and inexperience users and also as expert statisticians. It can also estimate and uncover missing values in data sets, allowing more accurate reports.
Scalable and agile, SPSS Statistics is made to figure out large volumes of data with as many user licenses as required, performing anything from descriptive analytics to advanced statistics simulations.
The open-source integration feature allows users to enhance the SPSS syntax with R and Python through a library of over 90 free extensions on the IBM Extension Hub, or they will prefer to build their own programs.
Features of IBM SPSS
Connectivity and Preparation of Data
SPSS Statistics tool easily read and write data from many various file formats and sources, including ASCII text files, spreadsheets and databases like Microsoft Excel and Microsoft Access and people from other statistics packages. Then, it streamlines and automates the information preparation process to spot missing data or invalid values and pack up large data sets in a single step. SPSS Statistics grants permission for greater accuracy in data analysis with its data conditioning workflow.
Comprehensive Statistical Analysis
SPSS by IBM is a robust statistical analysis tool which will perform almost all kinds of functions that includes but not limited to linear and non-linear models, simulation modeling, Bayesian statistics, custom tables, complex sampling, advanced and descriptive statistical models, regression and more. In addition to this, users can automate statistical procedures using SPSS syntax, creating customized data analyses. It can also perform geospatial analysis.
Users of statistical data can dig into their data with customized tables through ad-hoc analysis.
Easy to use
The user-friendly UI, SPSS features a point-and-click interface that works as a drop-down menus and drag-and-drop functionality. It gives users access without coding knowledge to perform data analysis. It features smooth processing, that makes it possible for even users without technical and coding knowledge to perform statistical analysis.
In addition to having the ability to perform predictive analytics, users can tailor the platform to their needs, allowing better predictions over time. Also, the multiple machine learning algorithms and simulators, SPSS uses functions like statistics analysis, forecasting, temporal causal modeling and neural networks to uncover complex possible relationships between variables. It can account for the uncertainty of the longer term with probability distributions and it improves its predictive models with multilayer perception and radial basis function.
Ease of Export
Users can easily export their data to SPSS’ proprietary file format or a spread of widely accessible formats like text, Microsoft Word, PDF, Excel, HTML, XML, XLS and more. Users also can export visualizations to a spread of graphic image formats.
IBM makes provision for its users to have the service to statistically analyze your data at a reasonable rate of $99/once a year/user.
Statwing is majorly built by and for analysts, in order that users can clean data, explore data, and make charts in minutes rather than hours. There’s no quick or more delightful way to work with data, for a user is already an expert with spreadsheets.
The solution for statistical analysis is meant solely for analyzing tables of data, so users finish days of study in minutes. Asking an easy question of a user’s data in a spreadsheet takes just a couple of minutes of shuffling data, creating charts and pivot tables, and writing formulas.
For instance, if a user is analyzing data in a spreadsheet and writing anything that is average, they’re going to get to work much faster in Statwing. Statistical analysis tool was built decades ago for statisticians, so it requires technical expertise to ask even simple questions.
Features of Statwing
An Easy-to-use user interface
Its easy-to-use interface permits new users to get insight from their data. Its state-of-the-art and intuitive interface picks statistical tests on its own within the background then provides leads to understandable and straightforward English.
Statwing also takes under consideration outliers which permit analysts to be confident in their analysis/results.
Data are easily understandable
Stawing also understands analysts’ arrangement in such an easy manner that it automatically creates several sorts of charts like histograms, scatterplots, bar charts etc. these can be easily exported to PowerPoint or Excel spreadsheets.
A free trial of Statwing tool is out there for users. The value of services increases depending on extra features.
This statistical analysis tool includes a quick-view dashboards and model comparison and averages to supply useful information to project managers and executive stakeholders and pick the simplest cross-validation and fitness, respectively.
It makes use of neural networks for straightforward data handling and learns difficult cases. Users can do experiments to realize deeper insights into possible opportunities and execute better forecasting and modeling with its statistics platform.
JMP users also can use interactive HTML to share their analysis with those that don’t have the software.
Features of JMP
- Designing Customized
- Capability and categorical response analysis
- Cause-and-effect diagrams
- Data visualization
- Time Series analysis
- Easy collaboration and internal control
- Risk data attributes
To choose the best statistical analysis tool, it will depend upon the type of data you’re looking to research and the features you need. You ought to even have the technical know-how and drive to realize the deepest insights from your data.
We hope this guide assist you determine the best tools for your statistical analytics needs, and you’re bound to find the proper match for your business here too.