Our goal is to make statistics open and accessible to everyone
statscloud was designed to make statistical tests easy to run, understand, and available for everyone on any device at any time.
A stats package for everyone
Statistics software is typically made by expert statisticians for other expert statisticians. Because of this, it assumes people open the software fully knowledgable on every test available, always choose the most appropriate test, and know how to interpret everything in the output.
In reality, that's just not the case. Many people open statistics software at different levels, including those who are just entering the field (students of psychology and other social sciences) and those who have stepped away from statistics for a while and require a little guidance.
statscloud was created to address this issue. It aims to make statistics much more accessible to newcomers to statistics and also provide a more fluid user-experience for existing, professional statisticians.
Making stats available on any device, any time
With touch devices and web applications becoming more and more popular, a modern statistics app should be developed with these users in mind.
Designed for touch devices
It's not enough for an app simply to work on touch devices; a modern stats app should be designed for them. statscloud was built with a responsive design so that usability remains high on the most popular devices.
Lightweight and easy to install
Stats software is typically very large so it's not practical or possible to install on Chromebooks or touch devices. In contrast, statscloud has it's own lightweight statistics package built into it and the whole app can be installed on any device with a single click / tap.
Available anywhere at any time
Cloud-based statistics apps can be complicated, expensive, and unreliable. However, we've been smart about how we use the cloud and have ensured that the app can always function offline when it needs to so it can operate fully on any device at no cost.
Helping people run reliable tests
statscloud helps to ensure people always run the most appropriate analysis by highlighting any issues with their results and suggesting alternative tests.
When running statistical analysis, it's important to make sure the test you have chosen is appropriate and all of its assumptions are met. To help with this, statscloud has some unique features to ensure your analyses are accurate and reliable.
Data cleaning is an important part of data analysis, but easy to overlook. To help you understand your data, statscloud provides a data summary for you which can alert you to any issues with your data before you start to run any analyses.
It's important for researchers to know when a test they've run is unreliable too, so statscloud produces a reliability report automatically with every analysis and suggests an alternative test if one is available.
Teaching people how to code
No stats app can replace a programming language, so statscloud doesn't try to. Instead, it shows people how to write code so they can do so themselves.
It's no secret that the best tool to use for statistical analysis is a programming language (e.g., R, Python, Julia). Statistics packages with a point-and-click user-interface can distract people from learning how to use one.
Teaching a programming language at undergraduate level isn't always practical though because many students won't be interested in becoming computer programmers and may be put off degrees that require them to.
statscloud offers a comprise by offering a clear user-interface and showing the code for your project alongside it as you work. It annotates all of the code too so you can learn what is does you go along and migrate to a programming language whenever you're ready to.
Providing a range of analyses
statscloud already provides a range of statistical analyses to cover the needs of statistics courses, though we will continue to add more tests as required.
differences
- Single-samples z-test
- Single-samples t-test
- Independent-samples t-test
- Mann-Whitney U
- Paired-samples t-test
- Wilcoxon
- Independent-samples one-way ANOVA
- Kruskal-Wallis
- Related-samples one-way ANOVA
- Friedman's ANOVA
- ANOVA
- Independent-samples t-test (TOST)
- Paired-samples t-test (TOST)
relationships
- Pearsons's R
- Spearman's Rho
- Kendall's Tau
- Linear regression
- Correlation (TOST)
associations
- Chi-Square (Goodness of fit)
- McNemar
- Chi-Square
- Likelihood Ratio
- Cochran's Q
- Two proportions (TOST)
scales
- Principal Components Analysis
- Cronbach's Alpha
- Spearman-Brown
Working with the community
We're working with social scientists and statisticians to make the app extensible and ensure it has all the functionality you need.
The most important people influencing the development of statscloud are the people using it, so we will be inviting our users to create the functions you'd like to see in the app and share these with the broader scientific community.
Our intention is to create a public cloud-based library of functions that can be submitted and shared with the scientific community to ensure the app always provides a full-suite of features for social scientists.