A Poultry Farmer That Dabbles in Statistics Is Interested in Exploring

Multiple Choice

A poultry farmer that dabbles in statistics is interested in exploring the relationship between two types of feed (layer pellets and scratch) , water, and the output of his laying hens. For ten days he records the number of ounces of layer pellets and scratch the hens consume and the number of fluid ounces of water and tracks the number of eggs that are produced. After running a multiple regression model, he obtains the following report. What is the best interpretation of these statistics? $$\begin{array} { | l | c | c | c | c | } \hline & \text { Coefficients } & \text { Std Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 1.256 & 1.249 & 1.006 & 0.353 \\\hline \text { Scratch } & 0.185 & 0.032 & 5.714 & 0.001 \\\hline \text { Layer Pellets } & 0.295 & 0.026 & 11.539 & 0.000 \\\hline \text { Water } & 0.149 & 0.041 & 3.587 & 0.012 \\\hline\end{array}$$

A) For every egg produced, about 0.185 ounces of scratch must be consumed.
B) The standard error for the model intercept is as large as the coefficient, thus the intercept is the most important predictor of egg production.
C) Layer pellets are not good predictors of egg production because the p-value is 0.
D) For every ounce of water consumed, the chickens produce 0.15 eggs, holding all other independent variables constant.