Data Science

Best Statistical Analysis Software

Statistical software is a specialized computer program which helps you to collect, organize, analyze, interpret and statistically design data. There are two main statistical techniques which help in statistical data analysis: descriptive statistics and inferential statistics.

Descriptive statistics organize data from a sample using indexes. Inferential statistics draw a conclusion from data that is a random variant. Statistics are crucial for organizations. They provide factual data which is critical in detecting trends in the marketplace so that businesses can compare their performance against their competitors. These are the best statistical analysis software:

1. SPSS (IBM)

SPSS, (Statistical Package for the Social Sciences) is perhaps the most widely used statistical software package in human behaviour research. SPSS offers the ability to easily compile descriptive statistics, parametric and non-parametric analyses, as well as graphical depictions of results through the graphical user interface (GUI). It also includes the option to create scripts to automate analysis or to carry out more advanced statistical processing.

2.RStudio

The primary mission of RStudio is to build a sustainable open-source business that creates software for data science and statistical computing. You may have already heard of some of our work, such as the RStudio IDE, Rmark down, shiny, and many packages in the tidy verse. Our open-source projects are supported by our commercial products that help teams of R users work together effectively, share computing resources, and publish their results to decision-makers within the organization. 

3. Stata

Stata: Software for Statistics and Data Science

Stata puts hundreds of statistical tools at your fingertips. For data management, statistical analysis, and publication-quality graphics, Stata has you covered.

4. OriginPro

Origin is a user-friendly and easy-to-learn software application that provides data analysis and publication-quality graphing capabilities tailored to the needs of scientists and engineers. OriginPro offers extended analysis tools for Peak Fitting, Surface Fitting, Statistics, Signal Processing and Image Handling. Users can customize operations such as importing, graphing and analysis, all from the GUI. Graphs, analysis results and reports update automatically when data or parameters change. 

5. Microsoft Excel

microsoft excel

While not a cutting-edge solution for statistical analysis, MS Excel does offer a wide variety of tools for data visualization and simple statistics. It’s simple to generate summary metrics and customizable graphics and figures, making it a useful tool for many who want to see the basics of their data. As many individuals and companies both own and know how to use Excel, it also makes it an accessible option for those looking to get started with statistics.

Have you read this: Data Science: Free Online Courses For 2020

6. SAS Base

SAS BASE

SAS Base is a programming language software that provides a 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.

7. MATLAB

Matlab

MatLab is an analytical platform and programming language that is widely used by engineers and scientists. As with R, the learning path is steep, and you will be required to create your own code at some point. A plentiful amount of toolboxes are also available to help answer your research questions (such as EEGLab for analysing EEG data). While MatLab can be difficult to use for novices, it offers a massive amount of flexibility in terms of what you want to do as long as you can code it.

8. Analyse-it

Analyse-it

Analyse-it is a statistical analysis software that includes hypothesis testing, model fitting, ANOVA, PCA, statistical process control (SPC) and quality improvement, and analytical and diagnostic method validation for laboratories to meet regulatory compliance.

9. GraphPad Prism

GraphPad Prism

GraphPad Prism is premium software primarily used within statistics related to biology but offers a range of capabilities that can be used across various fields. Similar to SPSS, scripting options are available to automate analyses, or carry out more complex statistical calculations, but the majority of the work can be completed through the GUI.

10. Minitab

Minitab

The Minitab software offers a range of both basic and fairly advanced statistical tools for data analysis. Similar to GraphPad Prism, commands can be executed through both the GUI and scripted commands, making it accessible to novices as well as users looking to carry out more complex analyses.

The skills required for the digital economy

We are living in a digital economy. Business executives around the world worry about the future of jobs and the welfare of their employees as technology automated processes and make sections of staff redundant. According to a recent PwC study, almost half 46 per cent of CEOs globally said significant retraining is the most important initiative to close a potential skills gap, against just 18 per cent who said they would be hiring from outside their industry.

Tech companies, and indeed all organizations in the digital economy, are coming to realise that digital skills are vital for employees in the digital era. It is more important than ever that new employees are cross-disciplined and have both hard and soft skills.  Whatever the specific job you are interviewing for, recruiters will be looking out for a wider skill set and broader experience in their new hires.

This list covers the top skills employers are looking for today and in the coming years. 

1. Human skills

Human skills include communication, creativity, critical thinking, collaboration, and analytical skills. Since an analysis of job descriptions highlighted human skills as a must-have, they didn’t seem to warrant a premium in salary. However, the reality is that although hard to judge in an interview, lacking any of these skills might cause candidates to be deemed unsuitable for certain jobs.

An interesting thing in an analysis of human skills was the fact that collaboration, as a skill, is becoming increasingly important in the work environment.

2. Programming, Web and App Development

At the heart of any tech product or digital service is coding. The core languages that most programming and web and app development positions need include Bootstrap, jQuery, Angular, Code Igniter, PHP/JavaScript, Python and MySQL. These skills are listed regularly in the top 10 most in-demand by employers on LinkedIn. Having a portfolio of projects demonstrating your coding skills can also help to validate your knowledge and expertise and help you land your dream role. Examples of mobile and responsive web development experience will give you an edge over other candidates.

Coding is also vital for emerging technologies such as augmented reality (AR) and virtual reality (VR). Coding will provide AR and VR Developers with the foundation skills needed to develop the next generation of AR and VR technologies. 

3. Digital Business Analysis

Digital Business Analysis helps organizations to make the right choices by providing an independent and objective mindset and applying a range of proven analysis techniques to make a convincing business case for investment in a digital solution.  As digital transformation is central to all organizations in the digital economy, digital business analysis skills have become the hottest skills to have on your CV in the 21st Century. Digital Business Analysts are at the epicentre of digital transformation projects. They help organisations develop a digital ecosystem of technologies that will help drive digital transformation and business growth. Much needed skill for the digital economy.

4. Data Design and Data Visualization

Websites, Apps and Digital Services have one thing in common; a user interface. Any designer with experience creating effective, dynamic user experiences will be in high demand with most tech companies.

Designers can also visualize complex data to help management make vital business decisions. This skill is called data visualization. Data visualization is useful for senior leaders to gain valuable insights from data. Tools such as Tableau and Power BI are used by designers to analyse and visualize data.

5. Digital Product Management

Another skill that is not unique to software development but one that is particularly valuable nonetheless is Digital Product Management. Software services in particular need to have a lifecycle management plan put in place. The continued growth of Software as a Service will make Product Management ever more integral to the tech sector.

6. Digital Marketing

To promote their products and services tech companies will look to digital marketing. Understanding of how to get the most value for money out of the broadest range of networks will be key here. In-demand skills for Digital Marketers include: 

  • Digital marketing tools 
  • Analytics tools
  • Social media marketing 
  • Content marketing 
  • SEO 
  • UX (User Experience Design)

7. Social Media

Some of the best PR today is carried out almost exclusively through social media. Twitter, Facebook, Reddit, Instagram and countless other platforms give tech companies direct access to customers, thought leaders and evangelists. The best Tech PR managers are Social Media managers.

8. Data Science and Data Analytics

Companies gather huge amounts of data that can be immensely valuable to them if they have a Big Data Analyst who can make sense of it all. Data Scientists are in-demand by employers across the world. Glassdoor constantly features Data Scientists in their Best Jobs Listing. Not only is Data Science an excellent career path for professionals in the digital age, but demand far outweighs supply, making Data Scientists highly employable. A recent McKinsey report showed that “The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers with skills to make decisions based on the analysis of big data.” As data science becomes a minimum requirement for more and more manager-level jobs, learning data science will help you position yourself ahead of the curve.