Pravallika Dharanikota Statistics Data Analysis Word

Divya Nimmala , Pravallika Dharanikota, Sai Balaji Nagi Rew DATA ANALYSIS PROJECT

1. Purpose: The individuals listed in the Excel file are basketball players. Each player is identified by their name and assigned a Position (POS), such as Point guard (PG), Shooting guard (SG), Small forward (SF), Power forward (PF), or Center (C), College, Age, Height in Inches, Weight in LBS, Salary. a. Who? Divya Nimmala (R01403110) - Presentation and Visualization Pravallika Dharanikota (R01404120) - Analysis and Content Creation Sai Balaji NagiReddy (R01401716) - Collection and Cleaning of Data b. What? The data includes both qualitative and quantitative variables. Qualitative variables include: Name : Names of the basketball players. POS : Positions played by the players. College : The colleges from which the players graduated or attended. Quantitative variables include: AGE : Age of the players. Height : Height of the players, typically measured in feet and inches. Weight : Weight of the players, usually measured in pounds. Salary : Annual salary of the players, expressed in dollars. c . When? The age of the players is provided, indicating their current ages at the time the data was collected. d. Why? The purpose of this data could be to analyze and compare various attributes of basketball players, such as their positions, physical characteristics (age, height, weight), college affiliations, and salaries. This analysis could be useful for team management, scouting, contract negotiations, and various other purposes related to basketball operations.

3. VISUALIZATION TOOL: MINI TAB Minitab is primarily a statistical analysis software rather than a visualization tool. While Minitab does offer some basic data visualization capabilities, it is widely utilized in statistical analysis. However, Minitab does provide various graphs and charts for visualizing data distributions, trends, relationships, and quality control analysis. These include histograms, scatterplots, boxplots, among others. While Minitab’s visualization features can be useful for exploratory data analysis, they may not be as extensive or customizable as those found in dedicated visualization tools like tableau or excel. Its main value lies in its ability to provide powerful statistical tools in a user-friendly interface, allowing users to:

Name POS College AGE Heigh t in inche s Weig ht in LBS Salary Keita Bates- Diop13 SF Ohio State 28 80 229 $2,364,61 4 Mikal Bridges1 SF Villanova 27 78 209 $21,700,0 00 Nic Claxton33 C Georgia 24 83 215 $9,625,00 0 Noah Clowney21 F Alabama 19 81 210 $3,089,52 0 Dorian Finney- Smith28 PF Florida 30 79 220 $13,932,0 08 Cameron Johnson2 SF North Carolina 28 80 210 $25,679,3 48 Keon Johnson45 G Tennesse e 22 77 185 $2,808,72 0 Day'Ron Sharpe20 C North Carolina 22 81 265 $2,210,04 0 Ben Simmons10 PG LSU 27 82 240 $37,893,4 08 Dennis Smith Jr.4 PG NC State 26 75 205 $2,019,70 6 Cam Thomas24 SG LSU 22 75 210 $2,240,16 0 Lonnie Walker IV8 G Miami 25 76 204 $2,019,70 6 Trendon Watford9 PF LSU 23 80 237 $2,019,70 6 Dariq Whitehead0 F Duke 19 78 220 $2,966,04 0 Jalen Wilson22 F Kansas 23 78 220 $850,000 Steven Adams12 C Pittsburg h 30 83 265 $12,600,0 00 Dillon Brooks9 SF Oregon 28 78 225 $22,627,6 71 Reggie Bullock Jr.25 SF North Carolina 33 78 205 $2,019,70 6 Tari Eason17 F LSU 22 80 215 $3,527,16 0 Jeff Green32 PF Georgeto wn 37 80 235 $9,600,00 0 Aaron Holiday0 G UCLA 27 72 185 $2,019,70 6 Jock Landale2 C Saint Mary's 28 83 255 $8,000,00 0 Jabari Smith Jr.10 PF Auburn 20 83 220 $9,326,52 0 Jae'Sean Tate8 SF Ohio 28 76 230 $6,500,00

5. Histogram of Salary Histogram of salary provides a visual representation of the distribution of overall salary. It displays the frequency of ratings within different salaries.

Descriptive Statistics: Salary Skewness 1.71 in this case, it indicates that the distribution is skewed to the right which means there are more potentially more extreme values on the higher end of the salary range. Resistant statistics: median=3372660 IQR= 10770546

6. Boxplot of Salary and POS:

BOX PLOT OF SALARY AND POS REPRESENTS THE HIGHEST AND LOWEST SALARY RANGES AS PER THE POS. Descriptive Statistics: Salary

14100000 2240160 IQR 8198720 1464640 789014 9002597 38786594 21112203 7. Scatterplot of AGE vs Weight in LBS

Resistant Data sets are. Median and the IQR from the above statistics Correlation Coefficient r is 0.095642.