Which is the most important part of a research? Yes, it is ‘designing your experiments correctly’. Next comes ‘interpreting’ your results. Research in Biotechnology and other life sciences can produce a lot of quantitative data which needs to be analyzed for statistical significance. Many graduates know to use Word, Powerpoint and Excel to a certain level. However, many new emerging job opportunities in modern biology requires skill to deal with quantitative data.
Below, I’ve mentioned 7 free online tools to take care of statistical needs ranging from T-tests, multiple regressions to Cluster Analysis, Bootstrapping etc.
1. SISA (Simple Interactive Statistical Analysis)
Conduct your statistical analysis directly online, no need to download anything. Click SISA for more details. You can also study the given guides to determine the appropriate procedure for your research problem.2. Open Epi
Open Epi is a free software program designed to cater for statistical needs in epidemiology. It can run from a web server or can also be downloaded and run without a web connection. You can also operate this program from your android or iphone.3. Scistat Calc
This is actually a blog ( running on blogspot). It has online calculators for common probability functions and significance tests and also explanation of concepts and formulas behind each test. Please go through Scistat Calc, it’s a really useful blog.4. Rice Virtual Lab in Statistics
It contains online statistics book, simulations, case studies and other resources for statistical analysis. You can access it here.5. WINPEPI
This is a free software available only for Windows users. WINPEPI has many programs ranging from comparing any 2 independent samples to multiple poisson regression, for more details visit WINPEPI6. Online Graph generators
Popular free online graph tools for producing neat scatter plots are Meta-calculator and Online Curve fitting. These are worth a try.7. R ( Open Source Statistical software)
Most of the bachelors and masters students use MS Excel for their statistical needs. Excel can be used to calculate t-tests and other co-relations decently. But, when you are handling a lot of data and need to do something more, then Excel may not be the right choice.R is more than a software. It is a language for statistical computing and graphics. It caters for a very wide variety of statistical analysis and the speciality of R language is that it produces quality graphs fit for publication (including mathematical symbols and formulae). It runs on Windows, Linux and also Mac. Moreover, it is free !!
Like any language it takes time to learn, but it has TONS of benefits. R language is widely used by statisticians and many commercial firms for data mining and analysis. To put it in very simple terms, it is comparable to MATLAB, but it is free. Download R language at https://www.r-project.org/
Details regarding Documentation can be found at R – documentation. Free online courses about how to use R can be found at Datacamp and Coursera (At coursera, the next session is from August 3 to August 30; 2015). R is actually one computer language which will always be useful for researchers and it is being constantly updated. Hence, it won’t be outdated soon. So why not invest your spare time to learn this useful language?