The residuals and the regression lines are labeled as shown in the diagram above.
When x1 = 0, x2 = 3 and when x1 = 3, x2 =6. Given the positive slope of the line, the intercept has to be positive if we believe (x1 = 0, x2 = 3). Hence, the bold line refers to the regression of x2 on x1.
On the other hand, when x2 = 0, x1 = 1.5 is possible with a possible slope line if the regression is of x1 on x2.
1. The following figure shows three (n = 3) observations of variables X1 and 22 along...
Assume that we have three independent observations: where Xi ~ Binomial(n 7,p) for i E { 1.2.3). The value of p E (0, 1) is not known. When we have observations like this from different, independent ran- dom variables, we can find joint probabilities by multiplying together th ndividual probabilities. For example This should remind you the discussion on statistical independence of random variables that can be found in the course book (see page 22) Answer the following questions a...
1. For each of the following regression models, write down the X matrix and 3 vector. Assume in both cases that there are four observations (a) Y BoB1X1 + B2X1X2 (b) log Y Bo B1XiB2X2+ 2. For each of the following regression models, write down the X matrix and vector. Assume in both cases that there are five observations. (a) YB1XB2X2+BXE (b) VYBoB, X,a +2 log10 X2+E regression model never reduces R2, why 3. If adding predictor variables to a...