Other Software Than Stata and SPSS to Use in Research Analysis

A research analysis is the process that reduces datasets into the story and interprets data to drive useful insights. It divides large chunks of data into smaller but meaningful fragments. It is a lengthy process that starts with choosing the right topic, passes through a number of analysis techniques and ends by extracting a logical conclusion. Throughout this process, the most difficult part that often seems daunting to the majority of students is the selection of the right software for data analysis. SPSS and Stata are the most sought-after software, and almost all social sciences students are pretty well aware of them. However, this article will not discuss Stata and SPPS; rather, it will focus on research analysis software R, Python, Minitab, SAS, EXCEL and Matlab. Let us discuss how this software can help you in research analysis:

R

Whenever your research goals or objectives restrict you from using Stata or SPSS, the first name that comes to mind as their alternative is R. R is an open -source programming language software. You can use it for machine learning, statistics and data analysis. It is free, and anyone can install it on their Mac, Windows, and Linux without purchasing a license. Some exciting features of R that may help you decide whether you should select it for your research analysis are as follows:

You can perform all basic statistics, including mean, variance and median at the R platform.
It provides its users with several types of static graphics, such as basic plots and graphics maps.
Research analysis through probability distribution (Beta and Binomial) is the most useful feature of R for the data analyst.

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Minitab:

Minitab is statistical software that allows you to explore data and gain valuable insights. It allows us to enter statistical data and identify the trends and pattern in it. It helps to create a bar chart by using unprocessed data. You do not need to enter calculations on your own. The automated interface of Minitab itself computes and calculates all statistics and makes graphics. Minitab gives an additional feature that other statistical tools such as Excel do not offers.

It can create different worksheets and graphs for different datasets. Its navigator helps us to overcome the issue of unorganised result sheets. Like other quality services, it also offers excellent support services to users by offering a number of diversified statistical analysis options. It makes your research analysis journey hassle-free by getting videos, webinars, FAQs for installation and additional tools for solving all its users’ problems. The following brief list will further sum up the role of Minitab in research analysis:

Summarise data
Access key results
Compare means
Equally important for academic and business research-based data analysis

Matlab:

Matlab is excellent software used for solving mathematical operations such as linear algebra and matrix. This software is not only known as a statistical package, but its services as a numerical computing work are also well-reported. It is an advanced level statistical tool. It does not offer a drag-form-menu-bar application; rather, it only understands a programming language. Thus, if you really need to use Matlab in your research analysis, you must first learn the Matlab programming language. The statistical tasks that you can perform on this software include:

Descriptive statistics (mean, median, mode and variance)
Visualisations
Clustering (used in exploratory analysis)
Probability distribution of data
Hypothesis testing (inferential statistics)
Monte Carlo Simulations

SAS:

SAS is another Statistical Analysis Software that can be the best alternative to SPSS and Stata. Basically, SAS is a group of computer programs that collectively work to store data values, modify them, clean them, organise them, compute them and create reports. It has a suite developed for business intelligence, advanced analytics, data management, and predictive analysis. If you have a large dataset comprised of even millions of entries, SAS works even better than Stata and SPSS. The data splicing or shrinking activities of the SAS are more powerful; thus, it is better capable of dealing with large data sets. Its drag and drop options speed up data entries in its spreadsheet. Concurrently, the data processing speed of SAS software is also faster than SPSS. Consequently, SAS is statistical software that allows us for easy integration of various statistical methods.

Excel:

Microsoft Excel is one of the most popular data analysis software. It is equipped with built-in pivot tables. Its popularity is due to its easy-to-use interface that allows researchers to explore, import, analyse, clean, and visualise data in a fraction of seconds. It is a piece of cake even for the beginner.

Conditional formatting is an amazing feature of excel. It allows researchers to apply special formatting or features to cells that meet certain criteria. It is important to highlight, differentiate and emphasise on some sort of data present in the data sheet.
Pivot tables help recognise and summarise chosen raw and column in a spreadsheet to obtain the desired report.
Paste special is the copy-paste activity that people love to do on Excel. For this, you just need to grab data from one cell and paste it into another cell. It helps sort data more easily.
Easy scalability is the beauty of Excel. It helps research analysts by offering a number of built-in formulae. It can do the right calculation without depending on the size of the dataset.
In terms of visualisation and graphics, Excel’s work is comparable with SPSS and Stata.

Final Thoughts:

SPSS is statistical software that is used by the social sciences research students, market researchers, public and private organisations, and health care service providers. Likewise, Stata is all-in-one statistical software that has all data analysis features for better data management and graphics. Economists, biomedical researchers and political researchers all know Stata very well. Both of these research analysis tools are popular for various exciting features. However, R, Minitab, Matlab, Excel, and SAS are other alternatives to Stata and SPSS. This article discusses all these five research analysis tools that may help you pick the one that best suits your research goals. They all analyse data in a way that is simple, reliable and help you make a better research for drawing a conclusion.