Example of STATA's Analytical and Graphing Power

I really wanted to combine many graphs into one using STATA statistical software when I saw the graph below. However, even if you look at a really large version of this 6x5 graph, you won't be able to see the details unless you have 20+/20+ eyesight, which most of us don't.

After looking at some STATA manuals I came up with this graph below. I think it is really neat how you can write a simple piece of code in STATA to merge as many graphs as you want. Here is the simple piece of code I used to make the graphs happen:

twoway scatter   npl2000 hrs_82
graph save g1.gph, replace
twoway (scatter meanhs8 hrs_82) (lfit meanhs8 hrs_82), ytitle(mean housing prices in 1980)
graph save g2.gph, replace
gr combine g1.gph g2.gph

And here is the actual explanation of what the graphs mean:

3b)  From the graph on the left below we can observe that an HRS score higher than 28.5 accounts for some but not all the variation for determining whether or not a census tract contains a hazardous waste site listed on the NPL by year 2000.

3c) The graph on the right gives a linear regression estimate, showing a mildly positive relationship between the HRS score in 1982 and mean housing prices in 1980. Additionally, from this graph we can conclude that HRS score in 1982 serves as a good predictor for housing values in 1980.

And here is the graph: 

The Power of Web Analytics

Web analytics is a field that has the potential to experience exponential growth in the near future. Why? Because an increasingly large number of people use the internet to carry out more and more transactions (aka purchases). Just think about Amazon.com and Borders. Amazon is doing great because people choose to purchase books online instead of going to a traditional establishment like Borders, which results in traditional establishments like Borders going out of business. The bottom line is that businesses need to adapt to this new environment and web analytics is an excellent tool as it dissects  key metrics about what is going on in the internet. Here is the snapshot of one of the slides of a presentation I put together recently.

Welcome!

Hi Everyone,

Welcome and thank you for taking the time to check out my blog. This is a space to share my ideas, thoughts, and interesting content with the world.

The table below shows you regression results the way they are presented in an academic economics journal. Columns 1-4 present 4 specifications of an Ordinary Least Squares with Fixed Effects Model and columns 5-8 also present an Ordinary Least Squares Model but using Sponsorship Eligibility as an Instrumental Variable.

This is the way researchers attempt to identify a cause and effect relationship. The asterisks to the right of some of the coefficients indicate these coefficients help explain variation in your "Y" variable of interest....... 

Oh, and by the way, I am proud to announce that I did put together this table myself.