Dear Bikram,

please check the software R. It's completely for free, there are tons of codes available for a broad range of analyses, and you have the possibility to program the code by yourself, if you want to.

Besides that, by now there are introduction textbooks available to get into the handling and programming of R. Check:

http://www.r-project.org/

Use R (www.r-project.org) Some time to work yourself into it but very versatile and lots of support and manuals online (e.g. www.statmethods.net, http://cran.r-project.org/manuals.html) as well as in the form of books, papers etc. Would recommend to combine with a nice GUI such as R-Studio (www.rstudio.com). All the best!

I second Rainer and Chrisian: R

Dear Bikram

There are many options you can consider.  R is a very general one, because allow a great choice of packages you can freely install and use.

From the site: http://www.r-project.org/   you can find manuals, contributed documentation, and a lot of material useful. I suggest you to consider the different task views here: http://cran.r-project.org/web/views/ 

On the different task views you can find  also indication on the different packages you can use for every different task you have to perform. 

At the same time you can use various GUI as the R-Studio (www.rstudio.com) but also  R commander http://www.rcommander.com/.

There are also other options on using R. All these options are free:

- PSPP an alternative to IBM SPSS  

http://www.gnu.org/software/pspp/

- PAST for data analysis 

http://folk.uio.no/ohammer/past/

- GNU Octave, a programming language which can be considered very similar to MATLAB

https://www.gnu.org/software/octave/ 

- GRETL for econometric analysis and time series 

http://gretl.sourceforge.net/

- Jmulti for time series analysis

http://www.jmulti.de/

Kind Regards,

Carlo Drago

There is indeed no statistical package that is more powerful than R, and it is free. And indeed in addition to numerous textbooks and reference material, Springer publishes an entire series of monographs/volumes User R! that demonstrates something of the extent to which R is used across the sciences.

That said, especially if your operating system is Unix-based or even Apple's, SageMath combines a large number of free software packages in one (you can use it if your OS is Windows, it's just more of a pain as you have to use an emulator). The list of included packages is in the attached link.

Also note that with the possible exception of R Commander (Rcmdr), the various GUIs that make R easier to use do not necessarily use the most frequent version of R. I found this out the hard way with R Studio and RExcel (the latter being Excel with R as an add-on, making Excel a GUI similar to SPSS but vastly more powerful). I have the advantage that in addition to R I have MATLAB, minitab, SPSS, Mathematica, Maple, & Stata on this computer and some others on my older computer, so I can stick with R Commander and for friendlier GUIs rely mostly on MATLAB for real analysis/models/etc. and Mathematica and Maple for CAS-related problems (mostly graphing/plotting). So after reviewing SageMath for others I deleted it as I DO have windows and 8 unnecessary gigs for a program I'm not going to use seems unnecessary.

I should also point out that, while not required, knowing Python substantially increases the power of SageMath and your scientific computing/data analysis power in general. 

http://www.sagemath.org/links-components.html

You also can try Python with package pandas

R and Python with package panadas. They are freely distributed software. On the other hand, you can also use Microsoft Excel for limited statistical analysis. Tableau Public for producing dashboards.

Only one choice exists, namely R!

But beware... The learning curve is ridiculously steep, however once you have climbed it, you'll be able to se further, standing on the shoulders of R!

http://www.r-project.org/

If I could add a qualifier to an above post, the learning curve for R is relative. For those who are not used to programming and/or are familiar with using Excel or SPSS for statistical analysis, the learning curve can indeed be steep. However, R is significantly simpler (from a programmer's perspective) than Java, C, C++, Perl, and probably Python. It is a scripting language, for one thing. A central advantage to using R over other programming languages with free compilers or environments is that it is wholly built around statistical analysis (actually, it's based upon another language/environment which is, but this amounts to the same). So a knowledge of statistics with some fairly elementary knowledge of programming can significantly flatten the curve.

Dear Sir,

Please visit the following pages. They provide some lists of useful statistical software packages.  You can choose one which is suitable for your requirements.

http://www.statsci.org/free.html

http://statpages.org/javasta2.html

The problem with minitab is that it isn't free. As for a package that is user-friendly, alas this too often means "designed to run statistical analyses with minimal knowledge of statistics; Excel and SPSS are the two programs that most lend themselves both to such usage and to courses designed around this educational approach). Minitab, Stata, STATISTICA, SYSTAT, SAS, MATLAB, Octave, SageMath, SPSS, JMP, Mathemtica, Maple, and other packages all have strengths and weaknesses. They are far, however, from equal even when one is evaluating them in the most general terms. SPSS, for example, is mostly useless for anyone seeking to employ the most recent and powerful statistical analysis, and as its GUI is deliberately modeled on Excel, this makes RExcel slightly less user-friendly but VASTLY more powerful. Python is significantly less user-friendly than minitab, but not only is it powerful in its own right, it is the basis both for a number of free scientific computing packages as well as most of these combined into one. Excel is inferior across the board (unless it is loaded with add-ons).. CASs like Mathematica are superior for graphical models even compared to my personal favorite of all statistical/computational software- MATLAB.

Minitab isn't as bad as SPSS. However, it isn't a very good choice if one had unlimited funds, and free packages are available that are more powerful than minitab and at least as or almost as user-friendly.

"If proper source of information/package is available for use I shall be thankful for the purpose."

There is no statistical software package in existence that has such open access to to source code, a community of programmers, vast numbers of easily obtained custom scripts, huge numbers of free online guides, references, even courses (most of which are free; I was told Coursera had a course on R but I don't recall if I confirmed it; however, YouTube and iTunes have lecture series and more for free). There are hundreds of free R tutorials, e-books, guides, etc., available online and for free (legally).

I never like to use a single tool, and would recommend SageMath and learning Python, but R is certainly the best if you wish to use only one statistical software package and you really do mean statistical (i.e., designed for statistical models/methods not computational sciences or related uses).

Origin Lab.....

http://www.originlab.com/index.aspx?go=Products/Origin

@Ashish, Viswanath: Minitab is an expensive software and has only limited abilities. If one thinks about using a costly software like Minitab, I would rather recommend to use Mathematica (minitab is developed further using Mathematica and Mathematica is unbeatable when it comes to Mathematics). For example, if you do nonlinear regerssion, minitab only provides local minima. There is no way to find a global optima using it! You need to break your head and use other things to integrate it in Minitab. So, I will not recommend such a software! R is the ultimate one meant for Statistics. As name implies, it is just a "mini tab" . Matlab and Mathematica are far superior to Minitab.

Try this one. Simple and free!!

http://www.real-statistics.com/

R Statististics is the program you are looking for. There are plenty of good textbooks around that will explain the basics and the not-so-basics of the program. You will be scared off at first by its command-line interface, but the R language has a very steep learning curve, because it is kind of intuitive. Its possibilities are virtually limitless. http://www.r-project.org/. 

I want to suggest R, which  is a free software. However, you need to learn how to run the program first. It's not difficult, you can just copy some codes from textbook and practice.

R is a free statistical software . You can download and use it .

Dear All,                                          Dated April 3rd,2015

Thank you all for your excellent suggestions particularly young and energetic scholars. Most of you have argued in favour of R statistics.

Now I need your help to know: (i) published aid material and help page for step by step guidance may be in power point, (ii) expert personnel in India for physical guidance on 'R' statistics irrespective of age and position, (iii) about the difference, if  any between ADE-4 and 'R' statistics, (iv) how to obtain full package of Excel for bivariate and multivariate analyses.

Thanks and all the best for interaction through ResearchGate which is opening a humanistic gate for an integral approach to knowledge and seekers of knowledge.

B.K.Senapati 

 I suggest two books may suitable for you, Cookbook for R (http://www.cookbook-r.com/ ) and R for Beginners (http://159.226.251.229/videoplayer/Paradis-rdebuts_en.pdf?ich_u_r_i=6717bd9a11087beb17e530f6126d5bc0&ich_s_t_a_r_t=0&ich_e_n_d=0&ich_k_e_y=1545048903752363012499&ich_t_y_p_e=1&ich_d_i_s_k_i_d=5&ich_u_n_i_t=1). You can also find some  bivariate and multivariate statistic codes in these two books.

But I like and love SPSS! It is a nice software to use it in health research!  Though  I have to learn it from an expert as I failed to learn it by self but since than I am enjoying it! Thanks!

Some statistical software are free and can be downloaded online such as R and AMOS. Better still, you can activate the excel ADDIN function and use it for analysis.

I would recommend MyStat, the free student version of SYSTAT. It is limited to 100 variables. It covers mostly routines, is very good in graphics. SYSTAT itself has a modest lifetime price. www.systat.com

They use menus but can also be run through a BASIC-like language. 

it is better to use R-package for free of charge, if you find to write R codes difficult NCSS package is cheaper  than other professional statistical packages such as SPSS, SAS, MINITAB ect

SAS have now an academic version free of charge, you can download it from http://www.sas.com/en_us/software/university-edition.html. Most of the tasks can be run with menus, but you must program if you wish exploit full capabilities of SAS.

An Excel Add-in very complete is XLSTAT, but only a trial version that can be used for 30 days is available for download for free (http://www.xlstat.com/en/download.html).

Dear Bikram:

If you need something simple and easy to use to perform ecological bivariate and multivariate statistics, you can use PAST software. It's free and works with most of Mac and Windows versions. You can download it from http://folk.uio.no/ohammer/past/

Nice to hear about you after so many years.

Kindly regards

Carlos