6 essential statistical software tools to strengthen your CV after graduation

Massive volumes of data are created every moment in today's corporate world. Having access to such large datasets opens up a plethora of commercial prospects. The only difficulty is how to turn data into action? Statistical software packages are the answer to this question. Prior knowledge of these software tools will give your resume a huge boost in the job market, especially if you hold a graduate/postgraduate degree in Statistics, Economics, Mathematics or Management.

More on statistical software

Planning, designing, collection of data, analysis, drawing meaningful interpretations and publishing research findings are all performed by these statistical tools. They perform complex tasks related to statistical methodologies like Regression Analysis and Time Series Analysis. By gathering data and turning them into valuable pieces of information for business action, these tools add value to the business.

Some popular statistical tools in use:

R

It is a widely used free statistical software suite in both human behaviour research and other domains. Its toolboxes and plugins are available for a wide range of applications in data processing. You need some basic coding knowledge to master this statistical tool. It comes with a vibrant community dedicated to developing and improving R and its plugins, ensuring that help is never far away. It is a GNU project that is similar to the S language and environment established by John Chambers and colleagues at Bell Laboratories (previously AT&T, now Lucent Technologies).

MATLAB

Engineers and scientists frequently utilise MatLab as an analytical platform and programming language. The learning curve is steep and you'll have to write your own code. There are numerous toolboxes accessible to assist you in answering your research queries, such as EEGLab for analysing EEG data. While MatLab might be challenging for beginners, it provides a huge lot of versatility in terms of what you can accomplish with it — as long as you know how to code (or at least operate the toolbox you require).

SAS (Statistical Analysis Software)

It is a statistical analysis tool that allows users to conduct analyses using the GUI or by writing scripts. A high-end solution, SAS is frequently used in industries including business, healthcare and behavioural research. Advanced analysis and publication-ready graphics and charts are conceivable, albeit the coding can be challenging for individuals unfamiliar with this method. It's a CSS plugin that lets you use variables, nested rules, inline imports, and other features. It also aids organisation and allows you to produce style sheets more quickly. All versions of CSS are supported by Sass.

Microsoft Excel

While not a cutting-edge solution for statistical analysis, MS Excel does provide a large range of data visualisation and rudimentary statistics capabilities. It's easy to create summary metrics and customise graphics and figures with its help. That’s why it is a useful tool for many people who only need to see the basics of their data. Excel is an accessible alternative for anyone wishing to get started with Statistics because so many people and corporations own it and know how to use it.

SPSS (Statistical Package for Social Sciences) by IBM

It is the most extensively used statistical software package in human behaviour research. Through the graphical user interface, SPSS allows you to quickly build descriptive statistics, parametric and non-parametric analyses, and graphical representations of results (GUI). It also allows you to write scripts to automate analysis or perform more advanced statistical analysis. This tool has been designed by IBM to solve business and research problems using ad hoc analysis, hypothesis testing, geospatial analysis and predictive analytics.

GraphPad Prism

GraphPad Prism is a premium software package that is used mainly in Biological Statistics, although it has a wide range of capabilities that may be applied to a variety of fields. Scripting tools are provided, similar to SPSS, to automate analyses or perform more advanced statistical computations. However, the GUI can handle most of the work. Scientific graphing, thorough curve fitting (nonlinear regression), intelligible statistics and data organising are all included in this package. While it won't replace a full-fledged statistics tool, Prism is handy for doing statistical tests for laboratory and clinical researchers.