Project Data Exploration and Analysis Plan

I uploaded an updated project plan - use economic data and other factors to predict treasury yields. I'm also interested in exploring which response variable has the greatest effect on the yields (see pdf)

I've finished collecting data this week and uploaded them to github. 
-csv files: each csv file contains the historical yield information for a benchmark treasury security
    -this is my 'target'; haven't decided if i'm going to use all of them, or just the most popular ones (i.e. 10 year, 13 week, etc)
-excel files: each file contains the historical information on a key response variable
    -CPI - inflation (source: Federal Reserve)
    -debt limit (source: White House)
    -deficit (source: White House)
    -outstanding (source: Treasury)
    -real GDP (source: Federal Reserve)
    -unemployment (source: Federal Reserve)

What steps have you taken to explore the data? Which areas of the data have you cleaned, and which areas still need cleaning? 
-I noticed that some data has regular time intervals (monthly, quarterly) and others have irregular time intervals
     -solution: I will map everything to a monthly time series
-There's possible collinearity - i.e. GDP correlates to CPI and unemployment rate
    -solution: use correlation matrix and variance inflation factor to identify those variables
    -solution: either drop those response variables, or create cross terms in the model

What insights have you gained from your exploration? 
-From simple plotting, I noticed that yields tend to be higher during the 2008 housing bubble crisis (markets were crashing)

Will you be able to answer your question with this data, or do you need to gather more data (or adjust your question)? 
-Initial plots indicate that the market prefer bonds over stocks during economic turmoil. 
-However, I am more interested in whether other factors (bills outstanding, proximity to debt ceiling, which party is in control) play an important role in affecting the yield in a relatively stable/normal economy. 
-I think I have the right data for this problem

How might you use modeling to answer your question?
-Definitely want to separate data into training vs. test
-Need to use a linear regression to fit the model? Not really sure what to use right now