1.) The vertical distance between y; and is called the ith residual. 2.) Suppose we gather data on 'sconsin bro drinking (Y) and ACT score (X). We then estimate a regression model and obtain the following: Di = 161 -4(ACT,) + ; Bucky Badger got a 27 on the ACT and drank 46 cans of Milwaukee's Best the Beast prior to being arrested for disorderly conduct following an altercation with a random Illinois bro and for plotting to engage in heavy metal poisoning of some gopher in Minnesota with gold. What is the y; associated with Bucky Badger? 3.) With respect to regression, the will increase anytime you increase the number of observations unless each observation has a residual equal to zero. 4.) If we use the method called when we are choosing our betas so as to minimize the sum of the squared residuals. 5.) The covariance by itself is not very useful because 6.) Bo tells us the expected value of the left hand side variable when is equal to zero.7.) If we start with raw data for two variables X and Y. We have nothing else, but want to estimate R- then which of the following numbers do we not need to know? Py OI,y Pr.y PI 8.) The ratio SSR tells us the share of variation in y we have failed to explain using variation in 9.) Who developed/ discovered the method of ordinary least squares?7.) If we start with raw data for two variables X and Y. We have nothing else, but want to estimate R- then which of the following numbers do we not need to know? Py OI,y Pr.y PI 8.) The ratio SSR tells us the share of variation in y we have failed to explain using variation in 9.) Who developed/ discovered the method of ordinary least squares