Hi Steve,

Personally I use Excel, but I only do very simple things like averages and medians etc.  We have a Stats team in-house who do more complicated analyses on our behalf - but I'm not sure which software packages they use (and I suppose they're really the people you want answering this question...).

Phil

Check 1 vote for MS excel!

R and Python.

R for everything going from EDA to Monte Carlo simulations, from cleaning data to web based interfaces (ShinyR), from dynamic plots to technical reports (RMarkdown) etc...

Python to generate/extract data from Monte Carlo codes (MCNPX/Fluka) but also for plotting and machine learning applications.

Almost exclusively R. Sometimes also Mathematica. There is nothing that R can't do nowadays + it is open source. I also use R to perform Bayesian analyses. Of course, Excel is still the medium for data storage and simple analyses.

Dear Philip

The R package is very efficient software but needs training, but for a beginner user in the statistical analysis, the SPSS IBM software ( under a window ) is good and need easy training, for this reason, is widely used in the analysis.

Good Luck

Mostly R with a dash of Python. The Python that I am familiar with is the numPy / openCV / SciKit Learn / Matplotlib modules.

R has some spectacular tools for data visualization and organization (ggplot2, plyr, and reshape). You can find every variety of statistical learning algorithm on CRAN and there are usually multiple packages that do the same thing with slight variations.     

R

Hi Steve,

I mainly use Excel, as I only do basic stats.  But it looks like I should be teaching myself R.

I have been using SAS software for many years.  Recently SAS have provided a new version called SAS university Edition very intuitive and user friendly  

https://www.sas.com/en_us/software/university-edition.html

Anybody who works with lab/analytical measurement using something like Minitab?

Excel is easy to use, but is not built for statistical analyses.  Something like Minitab makes data I/O straightforward (e.g. you can copy and paste in an excel spreadsheet), but gives much greater access to statistical analyses. For example - if you run an ANOVA in Minitab, I bet you get the model diagnostics. In excel you probably have to construct this by hand.

We have developed a new approach to use metrology: it is a software platform able to organize the metrology in different application field, such as an analytical laboratory, etc. Specifically, it permits to organize the calibration of all laboratory instrumentations (e.g. scales, pipettes, thermometers, etc.) and the intermediate checks by the use of control charts, to elaborate data and estimate the uncertainty of measurement with the use of different approaches, to verify during the time the metrological characteristics of the test methods by means different tools that assure the quality. Moreover, the validation protocols of the methods for the measurements can be organized by the use of statistic tests to realize the same protocol, in accordance with the technical sectorial standard.

Please, contact me for questions.

We have developed a new approach to use metrology: it is a software platform able to organize the metrology in different application field, such as an analytical laboratory, etc. Specifically, it permits to organize the calibration of all laboratory instrumentations (e.g. scales, pipettes, thermometers, etc.) and the intermediate checks by the use of control charts, to elaborate data and estimate the uncertainty of measurement with the use of different approaches, to verify during the time the metrological characteristics of the test methods by means different tools that assure the quality. Moreover, the validation protocols of the methods for the measurements can be organized by the use of statistic tests to realize the same protocol, in accordance with the technical sectorial standard.