Tuesday, May 5, 2020

Math Studies Ia free essay sample

What is the Relationship between Points per Game Scored and the Height of the Players in the NBA? Introduction: The NBA is one of the United States’ favorite sports leagues, with each team averaging 100 million dollars of income each year before expenses. Quite a bit of money is spent gambling, funding, and keep the public entertained with this sport. To keep this system working, and to get a fair share, all the coaches must attempt to keep their team on par with the others if not above their competitors. Knowing this, having any type of advantage could be quite profitable for a team. If there was a known way to give your team an advantage it would be utilized and be quite profitable. Height happens to be a physical characteristic that may play in role in having an advantage. If being taller does in fact give a player an advantage, then why not just hire the tallest players you can in order to get the biggest advantage? I chose this topic help determine whether or not this is a viable strategy for coaches. Although I would like to determine this and wish it to be true, I hypothesize that the points per game scored of the player will not drastically, if at all, depend of their player’s heights due to a multitude of other factors including, but not limited to, skill, practice, position, teams, plays, penalties, and the list goes on! Task: The main purpose of this investigation is to determine whether or not there is a relationship between the height of the players in the NBA and the amount of points they will score on average per game. The type of data that will be collected is the height of the players and their points per game on average for the most recent (complete) season. The points per game are used to determine how well the player performs (on average), and the height to determine the possible physical advantage that players can have over each other. The data was used to break down the average points per game scored for the heights of 64 different players and comparing them to see how it bodes. Plan of Investigation: I am investigating the relationship of points per game scored and height of players in the NBA. I have collected the data on the heights and points per game scored of 64 different players in the NBA from the previous season using the NBA’s official online database. With the collection of data that I have acquired I will use a number of mathematical processes to analyze the data: a calculation of the least squares regression line displayed in a scatter plot to visualize the relationship, and an r-correlation coefficient test to see the relationship’s strength and direction. Lastly, an X^2 test will be performed on the data to prove or disprove my null hypothesis. Following this, I will check my validity of the testing, and come to an ultimate conclusion as to whether or not I can back up my hypothesis or negate it. Discussion/Validity Limitations Throughout the investigation of the relationship between the points per game scored and the height of the players in the NBA, various limitations may have affected the outcome of the results. One limitation of the data collected could be that it reflects a random grouping of players from the mid-Atlantic region teams (Boston Celtics, Brooklyn Nets, Philadelphia 76ers, New York Knicks, and Toronto Raptors). Players from different regions/teams could cause a difference. Another limitation is that I did not include players with an average PPG below 2. These players were not included because they were all point guards whose goal, rather than to score points, is to prevent the other team from scoring. Another limitation is that not all players play the same position. The goals of different positions vary from scoring, defending, passing and many others. There are point guards, shooting guards, small forwards, power forwards, and centers. Not to mention that strategies involving these positions have specific players take shots rather than everyone attempting to. Adding on that, there might be a limitation to the amount of data that was collected. Only having collected 64 pieces it would have been better to collect all players from the NBA to better reflect the full span of players. Lastly, one reason for a lower PPG is the coach’s decisions or being suspended. Benching a player (sitting them out) would cause them less game time for the season and thus reduce their average. Conclusion In spite of the aforementioned limitations, the project was done according to plan and it was found that the chi squared calculation value of 0. 242226345, which is less than the chi squared critical value of 3. 841, thus accepts the null hypothesis that points scored are independent values to their players height. By analyzing this categorical data it helps disprove that if you expect points to be higher with height you will be wrong. Furthermore, the investigation clearly shows that there is almost no correlation between points scored and height by looking at the r-correlation coefficient. The r-correlation coefficient comes out to be -0. 048247472 which is so minimal that it basically states (in layman’s terms) that there is correlation between the PPG and the height at all. This is even visualized with the graph that barely moves from the midline! Using this data we can determine it is essentially impossible to determine someone’s estimated PPG just by having their height. Bibliography MLA Formatted Citations * NBA. com, Official Site of the National Basketball Association. Â  Players. N. p. , n. d. Web. 5 Nov. 2012. lt;http://www. nba. com/players/gt;. * Players. Â  Players in the NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://espn. go. com/nba/playersgt;. * Boston Celctics Roster 2012Â  Players in the NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://espn. go. com/nba/team/roster/_/name/bos/boston-celticsgt;. * Brooklyn Nets Roster 2012Â  Players in the NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://espn. go. com/nba/team/roster/_/name/bkn/brookly n-netsgt;. * Toronto Raptors Roster 2012Â  Players in the NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://espn. go. com/nba/team/roster/_/name/bkn/tornto-raptorsgt;. * New York Knicks Roster 2012Â  Players in the NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://espn. go. com/nba/team/roster/_/name/bkn/new-york-knicksgt;. * Philadelphia 76’ers Roster 2012Â  Players in the NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://espn. go. com/nba/team/roster/_/name/bkn/philly-76ersgt;. * Players. Â  NBA. N. p. , n. d. Web. 25 Nov. 2012. lt;http://sports. yahoo. com/nba/playersgt;.

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