Data analysis is an exciting field of mathematics that uses similar tools! This is where it gets really exciting! By proving the correctness of a procedure analytically under some set of assumptions, such as the asymptotic behavior of some distributions, we can be absolutely certain that our results are accurate. If we don't know whether these assumptions hold, we can use empirical methods to test whether the analysis works as expected — and that's an exciting opportunity! Verification is a great way to make sure that your methods are working as they should, even when you're dealing with smaller sample sizes or more complex models.
The best analysis is like a treasure hunt, searching through data to find the information hidden within. The exciting field of experimental design is all about finding ways to make the most of data before it's even collected. It's a fascinating area of research that unlocks the potential to optimize the insights from the data, even before it's gathered. This is great news for you because it means you can get more "bang for your buck" – more results (and more papers) at lower cost and with fewer resources spent in your study...
All models based on normal distributions can be represented as Structural Equation Models (SEMs). Ωnyx is a program to generate SEMs as graphical path diagrams. The path diagram can be fitted to data directly in Ωnyx, or quickly translated into a script to run in different systems like OpenMx, lavaan, or MPlusor as a java program using the Ωnyx package. Ωnyx uses a unique multi-agent optimization approach that, unlike most other SEM programs, continues to estimate even after it has converged on a solution. This increases both the chances of finding a global optimum and not getting stuck in a local optimum, and results in a fit that is largely independent of initial values. Both Bayesian and frequentist tests can be run in Ωnyx.
We encounter amazing artificial intelligence (AI) all around us! Sometimes AI is easy to recognize, as in chatbots, which are pretty cool. But sometimes AI is hidden in the classifiers that guess which movie we might want to see, which is pretty amazing too! Both variants of AI are great for making data analysis more efficient in the empirical sciences! At the Thomas Bayes Institute, we're thrilled to be researching how all kinds of AI can assist data analysis!