Good applied text for linear regression? I have a pure math background and am now studying statistics. For additional study in my linear regression and time series class, my professor suggested a more applied text rather than a higher level text that focused on analyzing real life data sets from business, econ, and the other soft sciences. 
I am beginning to understand the "interpretive" component of statistics, and appreciate the wisdom of this advice. But when I search through the possible texts, I find a ton of them, and I am wondering if anyone could suggest a few they think are especially good in this regard.
 A: For regression, the first half of Gelman and Hill is great. For time series, my recommendation would be Hyndman and Athana­sopou­los. Both use R for the examples.
For econometrics intuition, I really like A Guide to Econometrics by Peter Kennedy.  Each topic starts with a simple explanation, usually with diagrams, followed by technical notes with some math and references. More applied texts on microeconometrics are Cameron and Trivedi's Microeconometrics: Methods and Applications and Microeconometrics Using Stata. The first is geared at the applied researcher with some Stata examples, the second is aimed at the student and has more examples than you can shake a stick at. 
A: Draper and Smith, Applied regression analysis, Wiley 3rd edition 1998 is inevitably dated in some respects but there is a good reason for it to have survived to be still in print almost 50 years after first publication. 
Sheather, A modern approach to regression with R, Springer 2009 is a concise data-oriented coverage. There is Stata code in support as well as R code. 
Fahrmeir, Kneib, Lang and Marx, Regression: Models, methods and applications, Springer 2013 looks pretty solid and covers more than classical linear regression. 
There are some authoritative econometrics texts that do an excellent job in explaining which assumptions are important and which are not, but they are often lousy at looking closely and carefully at datasets and using graphics to their full potential. That was, naturally, a personal opinion. 
A: *

*"Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences" by Cohen and coauthors is a fantastic text that teaches you how to deal with analytic problems common in soft social sciences.

*"An R Companion to Applied Regression" implements many of the techniques mentioned in 1 using R functions. If you use R, this can be a great resource. 

*Though not as applied as the two books above, Seber and Lee's "Linear Regression Analysis" is another great resource for those who are more mathematically inclined. 


References


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*Cohen, J., Cohen, P. C., West, S. G., & Aiken, L. S. (2003). (3rd Ed.) Applied multiple regression/correlation analysis for the behavioral sciences.  Mahwah, NJ.: Lawrence Erlbaum.

*Fox, J. & Weisberg, H. S. (2011). An R Companion to Applied Regression (2nd ed.).
 Thousand Oaks, CA: Sage.

*Seber, G.A., and Lee, A.J. (2003). Linear regression analysis (2nd edition). Wiley Interscience.

