Source for Autodidactic Learning of Data Analysis Techniques

[muraii]

I'm looking for a little crowd-sourced shepherding along the road to a more robust grasp of analytical methods for data munging and summarizing. I completed a BA in mathematics but focused on the pure thread, to the degree undergraduates can be said to focus on anyone vein.

I was not a phenomenal student, and eschewed the applied courses as much as I could, so I'm not as strongly familiar with theoretical frameworks nor with cookbook-style production. That is, I know enough to know I don't know enough to deliver to my preferred level of quality as a data analyst. I can grapple with pivot tables pretty fluently, and I know we use arithmetic means as performance indicators without verifying they're appropriate. I am embarking on a basic analysis of the distribution of our data fields, and may begin presuming fit to various distribution models to see if I can fine-tune the analyses, but these amount almost to a random walk through the space of modelling techniques and undergirding theory.

I've tracked down Nelder's text, Generalized Linear Models (3rd Edition), but US$100 is a bit steep and I'm unsure how suitable it is for self-study. I also found Dobson's An Introduction to Generalized Linear Models which is both more affordable and by reviews seems a little gentler for the part-time, lone student. There are a bevy of others in Amazon's recommendations.

I am of course familiar with descriptive statistics, mostly mechanically, and completed a calculus-based statistics course which nevertheless required no integration of CDFs or any other evidence of actual calculus. I'm confident I can grok this stuff and am excited to learn more, both for my current employment but also for my own development. I've considered graduate work as a means of greater access to both the materials and mentors, but there are competing logistics I'd need to consider. Thus I'm looking to learn on my own.

Thanks for your time and brain power.

 

[Jhero]

As you look to build your knowledge of data munging and summarizing, I would suggest looking into courses from sites such as Coursera or EdX. These sites offer a range of classes, from introductory courses to more advanced topics, that can help you deepen your understanding of the subject. Additionally, many courses are offered for free or at a discounted rate, so you can access the material without spending a fortune. I would also recommend looking into books that focus on data science, such as "Data Science for Business" by Foster Provost and Tom Fawcett, as well as online resources like Kaggle and DataCamp. These resources can provide you with real-world examples of how data munging and summarizing are used in different contexts, as well as give you access to tools and tutorials that can help you hone your skills. Finally, it can be beneficial to connect with other professionals in the field, either through local meetups or online forums. This will give you the opportunity to ask questions, get advice, and learn from experienced practitioners. Good luck in your journey to become a better data analyst!