26.  How many air sacs to most birds have?

2.  Which of the following often provides the most information about a lizard patient’s condition when presented for an examination?

7.  Instead of neutrophils, birds have:

Determine whether the following inference form is valid or invalid. MC 4.2b Question 5.png

You fit an AR(1) model to T=48 months of data (2008.m1-2011.m12) on housing starts, i.e., how many new, private, residential housing units began construction in a particular month t.  You are planning to use it to forecast next month’s housing starts given this month’s value.  This

You have a cross-sectional dataset from 2014 with one observation per country.  The Y variable is annual GDP growth (%), and the X variable is a measure of democracy, where 1=most democratic and 0=least democratic.  You are interested in the slope coefficient in the linear projection of Y onto (1,X), i.e., the parameter b in LP(Y | 1,X) = a + bX.  You’ve heard rumors that the less-democratic countries sometimes intentionally report GDP growth that is better than reality, but you have no way to actually test that hypothesis because in your dataset you only observe the GDP growth reported by each country, not the true GDP growth (unless they are identical).  Let Y* be the true annual GDP growth, Y the observed/reported value, and  M = Y – Y*  the measurement error.  If the rumor is true, then the OLS slope estimator has _______ asymptotic bias.  (Hint: draw a picture.)

You have the time series data Yt of your company’s sales (in millions of dollars) in each year t.  You want to model the sales growth rate.  You should model

Which of the following does NOT raise concern about a threat to external validity? The goal is to learn the effects on employment of a job training program targeting all unemployed adults in Missouri.

Because the linear projection slope coefficient can be written as Cov(X,Y)/Var(X), it cannot be

Let Y be hourly wage ($/hr) and X=years of experience.  You want to estimate a statistical relationship between wage and experience, not worrying about causality.  You’ve heard that initially more experience is associated with higher wage, but that at very large values of experience, more experience is actually associated with lower wage.  You’ve also heard that each year of experience is associated with a percentage change in wage.  Given all this, the best model to try first would be