Mountain Empire Warriors football team
... the player the more he weighed. The graph above illustrates this relationship. The Regression Line Equation reads, y = 14.69x – 852.39. The Regression Line, also known as the line of best fit, measures the smallest distances from points to the line. The Correlation Coefficient (r) is .777, which shows that there is a strong positive linear correlation between a football player’s height and their weight. The Correlation Coefficient tells how well the line fits the data. So, by judging from (r), the Regression Line is of superior fit. The Coefficient of determination (r2) is 60.4%. This means that 60.4% of the reason the player’s weight the amount they do is based on their height. 39.6% of the reason the player’s weight the amount they do is based on reasons I didn’t consider. Examples of these reasons are as follows, the amount of food intake one has, the amount of exercise one has on a daily basis, hereditary reasons, and ones body build. For example, muscle weights more than fat, so a person that is short and stocky, may have more muscle and less fat but still weight more. These computations tell me that my hypothesis was correct, based on my sample the taller a player the more they weight. By analyzing the data from my sample, the Mountain Empire Football Team, that represents a subset of the NAFL, I found that the taller the player the more they weighted. I believe that my findings for both questions could represent the population as a whole. Most of the time, by watching football you can see, that the taller a player is the more they weight. I do not believe that there were any factors that could have affected the answers I received for the two questions. They were both pre...