I’m writing this blog post atop a hill overseeing the amazing Pacific Ocean, with deep blue ocean waves crashing onto the sands below and splattering into white foam. I love Southern California!
I have been browsing through data charts from the Google’s public data explorer this afternoon, thanks to one of my coworkers who stumbled upon it last week. It is quite a nice resource, hosting links and visuals to many public databases, from the U.S. Bureau of Labor Statistics to World Development Indicator to IFs forecast. There’s lots of good stats and data visualization using Google’s chart tools. I highly recommend it and hope to pass this site onto all my blog readers.
This week, my statistics class covered multiple regression and confidence intervals. It is pretty amazing how in business often times we just use point estimates from sample statistics, while confidence intervals can significantly increase the accuracy level of the data reported. But as the professor pointed out in the lecture, confidence intervals can sometimes be embarrassingly large due to the nature of sample statistics. I plotted scatterplots with confidence intervals, and compared a few regression models and learned to examine which types of models provide more probabilistically accurately data analysis. I’m definitely interested in applying it in my future work related to data analysis.