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? Regression Statistics
$$\begin{array} { | l | c | } \hline \text { Multiple R } & 0.993633 \\\hline \text { R Square } & 0.987307 \\\hline \text { Adjusted R Square } & 0.98096 \\\hline \text { Standard Error } & 0.213764 \\\hline \text { Observations } & 10 \\\hline\end{array}$$

A) The probability that the number of eggs is correctly predicted by the amount of scratch, layer pellets, and water consumed is 99.36%.
B) The prediction of the amount of eggs is 98.7% accurate based on the amount of scratch, layer pellets, and water consumed.
C) 98.7% of the variability in egg production is explained by the amount of water, scratch, and layer pellets consumed.
D) The prediction of the amount of eggs is 99.36% accurate based on the amount of scratch, layer pellets, and water consumed.