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MAT 243 Project One Summary Report .docx MAT 243 MAT 243 Project One Summary Report Southern New Hampshire University The purpose of this research is to provide the Timberwolves coaches and management representatives with descriptive statistics and da
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MAT 243 Project One Summary Report .docx MAT 243 MAT 243 Project One Summary Report Southern New Hampshire University The purpose of this research is to provide the Timberwolves coaches and management representatives with descriptive statistics and data visualization charts to identify distribu...
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MAT 243
MAT 243 Project One Summary Report
Southern New Hampshire University
The purpose of this research is to provide the Timberwolves coaches and management
representatives with descriptive statistics and data visualization charts to identify distributions of
key performance metrics per game played (points scored, points scored by opponents, relative
skill, opponent’s relative skill, game location, and game result). This information was provided
to me for analysis from the nbaallelo.csv data set, in order to improve the performance of the
team. Using data visualization, descriptive statistics, and confidence intervals I hope to properly
identify the weaknesses in our current program so that adjustments can be made going forward.
I compared data on the Timberwolves and the teams in the league during the 2013-2015
seasons with that of the assigned team (Bulls) and the teams in the league during the 1996-1998
seasons.
Table 1. Information on the Teams
Name of Team Assigned Years
1. Yours Timberwolves 2013 - 2015
2. Assigned Bulls 1996-1998
This first thing we are going to look at are the visual representations of the points score by
the Timberwolves during their games in the 2013-2015 seasons and the points scored by the
Bulls during their games during the 1996-1998 seasons. The reason we use data visualization
versus data tables in certain situations is because it allows people to better absorb the information
being presented and recognize trends or patterns. We are better able to see the “big picture” and
make more informed decisions based on that data.
, I chose to use a scatterplot to showcase the points scored by the
Timberwolves 2013-2015 because I believe it best shows the points
scored per game for each year of the analysis as well as the central
tendency of the years in totality. This is important because it shows us
the spread of points per game in a single season, as well as the overall
trend of points scored over the three years. The scatterplot above shows
that the Timberwolves’ games concluded in a variety of
scores each season. 2013 seems to be their most consistent year, scoring between approximately
78 and 119 (41 point spread), while during their 2014 year they scored between approximately
82 and 143 (61 point spread). We can still see that overall, the central tendency is moving in a
positive direction, implying that the mean scores per year are improving.
Using a scatterplot to showcase the points scored by the Bulls 1996-1998 because it is easier
to compare visuals that are in the same format. By looking at the scatterplot above, we can see
that the Bulls’ games concluded in a variety of scores each season. The Bulls tend to be
consistent in their scoring range from year to year, with only a few outliers each season that do
, not fit the trend. The major point that I would pull from this information is that while the Bulls
appear to score more points overall in their 3-year period than the Timberwolves, we are seeing
the central tendency moving in a negative direction, which means that the mean score of each
year is getting worse.
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