Project One Summary Report (Data Science)

1. Introduction: Problem Statement The report is built after gathering a broad set of historical data from the NBA data set in which the analysis using descriptive statistics and data visualization techniques. The primary objective of the report is to analyze the performance patterns of the basketball teams. All the conclusions produced on the report would be based on the result obtained after using descriptive statistics and data visualization techniques in python programming. The study is using NBA data to establish, primarily focusing on four variables: Point scored by the team in a game The comparative ability level of the team in the league Year when the team played the games Name of the team The statistical technique used to analyze all data visualization, confidence intervals, and descriptive statistics by using mean, median, min, max, variance, and standard deviation. 2. Introduction: Your Team and the Assigned Team Table 1. Information on the Teams 1. Yours 2. Assigned Name of Team Jazz Chicago Bulls Assigned Years 2013 - 2015 1996-1998 In the study, the Jazz team is selected, and the year to analyze the year 2013 to 2015. The team assigned is the Chicago Bulls from the years 1996 to 1998. 3. Data Visualization: Points Scored by Jazz Team Data visualization is a procedure to embody the data and information graphically. It can be thru graphical element as graph, charts, and maps. The primary purpose of the data visualization tool provides an appropriate way to understand data trends, outliers, and patterns. The project would provide visual shows to distribute the Jazz team's point scores from 2013 to 2015. For this situation, there would have two alternatives to elect for data visualization like histogram and scatterplot. In the study presented here, the scatterplot would provide the best visual for the distribution of the points by the Jazz team. As the scatterplot is a suitable way to see the connection between year played and scores and the report would be more values for individual data points and patterns as the data would be taken as a whole and recognizing the inclinations. In the scatterplot below would be demonstrations of the point scored by the Jazz team from 2013 to 2015. The Jazz team in 2013 had a range from 70 to 140, with approximately an average of 102 as well as a few outliers, also, in 2014, it ranged from 75 to 136 with an average of 100. Again, in 2015, the averages from 67 to 120 with an approximation of 98 as an outlier. By looking at the negative slope trend line, the performance is decreasing very slowly every year. 4. Data Visualization: Points Scored by the Chicago Bulls team The scatterplot was selected here to visualize the relationship between the point score and the year played. It would show the points scored by the Chicago Bulls team from 1996 to 1998. It is useful to report the individual data value, identifying trends, and outliers. So, the point of the Chicago Bull team in 1996 range from 71 to 136 with an outliner around 110. Similarly, in 1997 the scores range from 78 to 149 with an outline of 104, as in 1998, the range from 73 to 135 with an outliner around 100. The outlier is gradually decreasing in a significant way every year. 5. Data Visualization: Comparing the Two Teams Visualization would convert the raw data into a visual form to understand and interpret it by the readers through different tools like line charts, scatterplots, box plots, and histograms. Using these tools would compare the mean, median, max, min, and the outlier of the unalike data set and variety of decisions. The boxplot would be handy as a comparison of the two data distributions between the Jazz and Chicago Bull team in the study. It would summarize a large amount of the two data distribution in the study between the two teams based on min, max, median, quartiles, and range. It would provide an approximation suggestion of data skewness and symmetry. Viewing the two boxplots, Bull's team is higher than the Jazz team. So, the Jazz team's median is around 95, and the Bull team is around 105. As the boxplot shows, the Bulls team did a lot better than the Jazz team in a significant way. 6. Descriptive Statistics: Relative Skill of Jazz Team Table 2. Descriptive Statistics for Relative Skill of Your Team Statistic Name Mean Median Variance Standard Deviation Value 1462.85 1455.42 3920.12 62.61 Overall, the measure of a central tendency states the mean, median, mode. The mode has variability know as variance and standard deviation. It also indicates where is the central location of the distribution. The variability refers to how the data set to spread out. It permits us to compare how one data set vary from additional exhausting statistics. The Jazz team means it is 1,462.85. It would signify the Jazz team's average score, which is calculated by summing up all the scores and dividing them by the scores count. The median of the Jazz team is 1455.42, which characterizes the mid-value score of the team. The variance is 3920.12 representing the average of the square difference from the means as the standard deviation is 62.61 in which the square root of variance. The data tell us how it is spread out from the average value. As in the study, the mean is slightly higher than the median value, which suggests the distribution is positively skewed. 7. Descriptive Statistics: Relative Skill of the Chicago Bull Team In the Python script, you calculated descriptive statistics on the relative skill of the assigned team. 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: Table 3. Descriptive Statistics for Relative Skill of the Assigned Team Statistic Name Mean Median Variance Standard Deviation Value 1739.80 1751.23 2651.55 51.49 As seem in table 3, the result of the central tendency and variability of the Chicago Bull team. The calculation would be performed in Codio by using Python programming languages. Based on the table outcome presented in the table, the mean of the Chicago Bull team is 1739.80, epitomizing the average score. The median is 1751.23, which represent the mid-value of the team. Variance is 2651.55 embody the average of the square difference from the mean as the standard deviation is the square root of the variance that is 51.49. The difference between the median and mean is 11.49, which implies that the data skewed is skewed to the left. Since the data is to the left, the median would be the best central tendency to denote the focus of the distribution for fewer affected by skewed and outlier values. Also, looking at the variance of the Chicago Bull team and the Jazz team, the Jazz team has a higher variance than Chicago Bull. Likewise, the standard deviation of Jazz is 62.61, and Chicago Bull is 51.49, which the difference between is 11.12 (62.61 - 51.49). The lowest standard deviation between them was Chicago Bull, which implies that the distribution of the relative skill is dependable liken to the Jazz team. 8. Confidence Intervals for the Average Relative Skill of All Teams in the year 2013 to 2015 Table 4. Confidence Interval for Average Relative Skill of Teams in Your Team’s Years Confidence Level (%) 95% Confidence Interval 1502.02, 1507.18 The confidence interval is a range of values around the statistics with a certain probability. Sampling simulated data over and over with or without population means depending on the variables. The skillset drops and rises in the middle then drop toward the end, mean the middle is the more substantial ranking among skill set. It is calculated using the formula of the confidence interval like point estimate minor margin of error, point estimate + margin of error. The margin of error would be referent as the standard error of the average value as the ration of the standard deviation to the square foot of the number of samples and then multiply by the appropriate zscore. The confidence interval level would give the probability of using the determine the interval as shown in the study( e.g., 90%, 95% & 99%). Like the table above, it shows that 95% of the confidence interval has the average relative skill of teams from 2013 to 2015. it exists at the ranges 1,502.02 to 1,507.18, which the Chicago Bull team(1,739.80) did not contain the average relative skill. Nevertheless, if anybody uses a different confidence level, the confidence interval can change as the probability would give the Jazz team a relative skill in between the range. 9. Confidence Intervals for the Average Relative Skill of All Teams in the Assigned Team’s Years 1996 to 1998. Table 5. Confidence Interval for Average Relative Skill of Teams in Assigned Team’s Years 1996 to 1998. Confidence Level (%) 95% Confidence Interval 1,487.66 , 1,493.65 Table 5 shows 95% of the two teams' confidence intervals between 1996 to 1998, which are 1487.66 to1493.65; however, it does not contain the average relative skill of the Chicago Bull team. The average skill is below the target. On the other hand, the confidence interval does not overlap, which means that the statically had a significant difference between the average relative skill of the teams . 10. Conclusion Using the program to analyze both team skills would promote better performance, growth, and rectify mistakes. Both teams show great achievement and downs falls that would be starting point to analyze to improve. The result would produce a skilled process to the team's pros and cons in which the computing massive of data in quickly readable documents. More or less, it would suggest making better performance as it uses visualization, the measure of central tendency, and variability. So, analyze the overall data; it seems the performance of both teams decreased year by year.