Authors of our textbook, Kiran Pandya, Prashant Joshi and Smruti Bulsari talk about how their title Statistical Analysis in Simple Steps using R, opens the gateway for research numerical analysis and big data.
Why R?
R is command-driven and hence offers a wide flexibility over other software. The advantage of using R is that you can download it absolutely free from the CRAN website and still you would be using a genuine open general licensed version; R is free and open-source (FOSS). R is lightweight; the software doesn’t occupy more than a few megabytes on your hard disk. Unlike proprietary software which requires you to pre-decide the purchase of modules, in R you may install a module (called libraries) when you need and uninstall when you don’t, which helps you manage the memory of your hard disk. This flexibility of uninstalling a module is not available with the proprietary software. Moreover, all the allied modules of R are also free. It is possible to work with R studio, a very user-friendly environment, which is also available for free. A large number of universities, research institutes and industries across the world is turning towards the use of FOSS in general and R in particular.
R for Statistical Analysis
Almost all quantitative research requires the use of statistics, be it a description of data, representing data in the form of graphs, discerning patterns (descriptive statistics), be it comparison of two or more groups, examining association between two entities, examining the cause-effect relation (hypothesis testing and regression analysis) or be it classification (Factor and Cluster analysis) or analysing the trend (time-series analysis). This requires a basic understanding of the statistical technique and the use of software to undertake the analysis. Books on statistics provide a limited discussion on the use of software and books on the use of software have limited discussion on statistical techniques. The authors have experience of guiding students in social sciences, medical sciences, education etc. who come to them with a plethora of difficulties related to both – using the right statistical technique and also the use of appropriate software.The book Statistical Analysis in Simple Steps in R is a step-by-step approach to the understanding of statistical techniques, the R code for statistical analysis and interpreting the results.
Like it or not, statistical analysis will be indispensable in the time to come!
Why R?
R is command-driven and hence offers a wide flexibility over other software. The advantage of using R is that you can download it absolutely free from the CRAN website and still you would be using a genuine open general licensed version; R is free and open-source (FOSS). R is lightweight; the software doesn’t occupy more than a few megabytes on your hard disk. Unlike proprietary software which requires you to pre-decide the purchase of modules, in R you may install a module (called libraries) when you need and uninstall when you don’t, which helps you manage the memory of your hard disk. This flexibility of uninstalling a module is not available with the proprietary software. Moreover, all the allied modules of R are also free. It is possible to work with R studio, a very user-friendly environment, which is also available for free. A large number of universities, research institutes and industries across the world is turning towards the use of FOSS in general and R in particular.
R for Statistical Analysis
Almost all quantitative research requires the use of statistics, be it a description of data, representing data in the form of graphs, discerning patterns (descriptive statistics), be it comparison of two or more groups, examining association between two entities, examining the cause-effect relation (hypothesis testing and regression analysis) or be it classification (Factor and Cluster analysis) or analysing the trend (time-series analysis). This requires a basic understanding of the statistical technique and the use of software to undertake the analysis. Books on statistics provide a limited discussion on the use of software and books on the use of software have limited discussion on statistical techniques. The authors have experience of guiding students in social sciences, medical sciences, education etc. who come to them with a plethora of difficulties related to both – using the right statistical technique and also the use of appropriate software.The book Statistical Analysis in Simple Steps in R is a step-by-step approach to the understanding of statistical techniques, the R code for statistical analysis and interpreting the results.
Like it or not, statistical analysis will be indispensable in the time to come!
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