Firstly, I picked up three variables (X1: average temperature in January, X2: average temperature in February, and X3: average temperature in March) and set dependant variable Y as number of days after end of February. So, if the blooming day is 03/25, Y equals to 25; and if the day is 04/08, Y becomes 31+8=39. I arranged monthly average air temperature data in 1961 – 2004, ran MS-Excel regression data analysis function and gets the multiple linear regression equation as follows': Y=0.886X1 – 1.910X2– 3.213X3 + 63.069 (R²= 0.81)

This was not the correct quadratic model for the data

You have gathered data from a random sample of fast-food sandwiches in order to better understand how the amount of fat in these sandwiches relates to the amount of carbohydrates in the sandwiches. Your ultimate goal is to construct a regression equation to predict amount of carbohydrates based on amount of fat. If this is your goal, which variable should you put on the vertical axis (or y-axis) of a scatterplot of this data? O When conducting a regression analysis, it makes no difference which variable is on which axis. O Amount of fat, because it is the explanatory variable. O Amount of carbohydrates, because it is the explanatory variable. Amount of carbohydrates, because it is the response variable. O Amount of fat, because it is the response variable.

Jane collects data from 40 elementary school students and finds that the relationship between age (x) and score on a certain test (y) is given by y=3.2x+45. What can she extrapolate about the score a 16-year old will get on the test?