MAT 243 Project One Summary
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Southern New Hampshire University *
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122
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Mathematics
Date
Feb 20, 2024
Type
docx
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6
Uploaded by CoachWater19984
MAT 243 Project One Summary Report
Damien Holmes
Damien.Holmes@snhu.edu
Southern New Hampshire University
1.
Introduction: Problem Statement
I will be writing a summary report in an attempt to assist the coach and management of The Sixers basketball team in decision-making to improve the team’s performance using statistics and data visualization. I will be using both points scored for and against the team per game. The
two teams stats I will be comparing are the 1996-1998 Chicago Bulls, and the 2013-2015 Philadelphia Sixers
2.
Introduction: Your Team and the Assigned Team
The team I picked was the 2013-2015 Sixers, the team I was assigned to use for comparison wa
Table 1. Information on the Teams
Name of Team
Assigned Years
1. Yours
Sixers
2013 - 2015
2. Assigned
Bulls
1996-1998
3.
Data Visualization: Points Scored by Your Team
We use data visualization to show gathered information in an organized format like tables, charts, and graphs. When displaying data this way it allows for an easier and faster understanding and interpretation. I chose to go with the histogram to represent my data because for me it’s the easiest to interpret
the data given. By looking at the graph I can determine that the Sixers scored 90 points at a frequency of over 30
4.
Data Visualization: Points Scored by the Assigned Team
I also chose the histogram for the Bulls scores for the same reason, the graph is simple to read and interpret and breaks down the data better than the scatter plot graph did for me. By looking at this graph we can determine that the bulls scored 105 with a frequency of about 35.
5.
Data Visualization: Comparing the Two Teams
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Data visualization can be used to compare two different data distributions by either having them side by side for comparison or having them overlap each other to see how they compare. I chose the histogram to compare the two team's points because its easier to see where the two teams are similar and where they are different with the two different sets of data on top of each other. With this histogram I can see that the Bulls have a higher score rate and frequency of those higher
scores than the Sixers.
6.
Descriptive Statistics: Points Scored By Your Team in Home Games
In the Python script, you calculated descriptive statistics on the points scored by your team in games played at home venue. These included the mean, median, variance, and standard deviation for the relative skill of your team. See Step 6 in the Python script to address the following items:
●
Summarize all
statistics in a formatted table as shown below. Use one row for each statistic. You will need to add rows to the table in order to include all of your statistics.
Table 2. Descriptive Statistics for Points Scored by Your Team in Home Games
-
Value
Mean
96.74
Median
95.0
Variance 105.05
Standard Deviation 10.25
We use the measures of central tendency and variability to summarize the data distribution. We used the mean to find the average data set for the Sixers at home which was 96.74, the median gives up the middle of the data set for the Sixers at home which was 95.0. The standard deviation for the Sixers at home is 10.25 giving the data distribution a bell-shape
7.
Descriptive Statistics: Points Scored By Your Team in Away Games
In the Python script, you calculated descriptive statistics on the points scored by your team in games played at opponent’s venue (away). These included the mean, median, variance, and standard deviation for the relative skill of the assigned team.
See Step 7 in the Python script to address the following items:
●
Summarize all statistics in a formatted table as shown below. Use one row for each statistic. You will need to add rows to the table in order to include all of your statistics.
Table 3. Descriptive Statistics for Points Scored by Your Team in Away Games
Statistic Name
Value
Mean
92
.99
Median
93.0
Variance 123.65
Standard Deviation 11.12
Over the past three years the Sixers had an average(mean) score of 92.99 at away games, they had a median score of 93.0 at away games, the variance in away games for the Sixers is 123.65 and the standard deviation of the Sixers away games is 11.12 again giving a bell-shaped. The mean of the home games is higher than the mean of the away games indicating that the Sixers score more points while playing home games. The standard deviation is lower in home games than away games indicating that the Sixers away games are less predictable and more spread out than the scores of the home games. This all being said we can determine that the Sixers play
better during home games.
8.
Confidence Intervals for the Average Relative Skill of All Teams in Your Team’s Years
In the Python script, you calculated a 95% confidence interval for the average relative skill of all teams in the league during the years of your team. Additionally, you calculated the probability that a given team in the league has a relative skill level less than that of the team that you picked. See Step 8 in the Python script to address the following items:
●
Report the confidence interval in a formatted table as shown below. Table 4. Confidence Interval for Average Relative Skill of Teams in Your Team’s Years
Confidence Level (%)
Confidence Interval
95%
( 1502.02 , 1507.18 )
●
Describe how confidence intervals are generally used in estimating the measures of central tendency for a population. ●
Provide a detailed interpretation of the confidence interval in terms of the average relative skill of teams in the range of years that you picked. ●
How would your interval be different if you had used a different confidence level?
●
What is the probability that a given team in the league has a relative skill level less than that of the team that you picked? Is it unusual that a team has a skill level less than your team?
Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report. 9.
Confidence Intervals for the Average Relative Skill of All Teams in the Assigned Team’s Years
In the Python script, you calculated a 95% confidence interval for the average relative skill of all teams in the league during the years of the assigned team. Additionally, you calculated the probability that a given team in the league has a relative skill level less than that of the assigned team. See Step 9 in the Python script to address the following items:
●
Report the confidence interval in a formatted table as shown below. Table 5. Confidence Interval for Average Relative Skill of Teams in Assigned Team’s Years
Confidence Level (%)
Confidence Interval
95%
1487.66 , 1493.65 )
●
Provide a detailed interpretation of the confidence interval in terms of the average relative skill of teams in the assigned team’s range of years. ●
Discuss how your interval would be different if you had used a different confidence level. ●
How does this confidence interval compare with the previous one? What does this signify in terms of the average relative skill of teams in the range of years that you picked versus the average relative skill of teams in the assigned team’s range of years? Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include Python code in your report.
10. Conclusion
Describe the results of your statistical analyses clearly, using proper descriptions of statistical terms and concepts. ●
What is the practical importance of the analyses that were performed?
●
Describe what these results mean for the scenario.
Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include Python code in your report.
11. Citations
You were not
required to use external resources for this report. If you did not use any resources, you should remove this entire section. However, if you did use any resources to help you with your interpretation, you must
cite them. Use proper APA format for citations.
Insert references here in the following format:
Author's Last Name, First Initial. Middle Initial. (Year of Publication). Title of book: Subtitle of book, edition. Place of Publication: Publisher.
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