Base SAS
Stata
EViews
IBM SPSS Statistics
RStudio
NumXL
JMP
SAS/STAT
StackTips 2.0
StackTips 2.0No features have been listed yet.
Based on our record, StackTips 2.0 seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Originally published at http://stacktips.com. - Source: dev.to / over 2 years ago
Today, I am excited to take a giant leap forward in my journey by open-source the codebase of my blog stacktips is now available on GitHub. - Source: dev.to / almost 3 years ago
Now I am running this blog stacktips.com. It is a custom-built site, using Python, Django, and VueJS. - Source: dev.to / almost 3 years ago
Prefix="og: https://ogp.me/ns#"> StackTips - Resources for Developers property="og:url" content="https://stacktips.com"> property="og:type" content="website"> property="og:title" content="StackTips- Resources for Developers"> property="og:description" content="StackTips provides developer friendly ways to learn programming. We aim to teach developers in the most efficient ways... - Source: dev.to / almost 3 years ago
Stata - Stata is a software that combines hundreds of different statistical tools into one user interface. Everything from data management to statistical analysis to publication-quality graphics is supported by Stata. Read more about Stata.
EViews - EViews (Econometric Views) is a statistical package for Windows, used mainly for time-series...
IBM SPSS Statistics - IBM SPSS Statistics is software that provides detailed analysis of statistical data. The company behind the product practically needs no introduction, as it's been a staple of the technology industry for over 100 years.
RStudio - RStudioโข is a new integrated development environment (IDE) for R.
NumXL - NumXL is a Microsoft Excel time series software add-in.
JMP - JMP is a data representation tool that empowers the engineers, mathematicians and scientists to explore the any of data visually.