Scenario You are a data analyst for a basketball team. You have found a large set of historical data , and are working to analyze and find patterns in the data set. The coach of the team and your management have requested that you use descriptive statistics and data visualization techniques to study distributions of Ioey variables associated with the performance of different teams .Data -driven analytics will help the management make decisions to further improve your team's performance. You will use the Python programming language to perform your statistical analysis. You will also need to present a report ofyour ndings to the team's management .Since the managers are not data analysts ,you will need to interpret your ndings and describe their practical implications .The managers will use your report to find areas where the team can improve its performance Directions For this project ,you will submit the Python script you used to make your calculations and a summary report explaining your findings 1. Python Script :To complete the tasks listed below, open the Project One Jupyter Notebook link in the Assignment information module. Your project contains the NBA data set and aJupyter Notebook with your Python scripts .ln the notebook ,you will find step -by step instructions and code blocks that will help you complete the following tasks .' o Choose and create adata Visualization o Calculate descriptive statistics including mean ,median ,min. max , variance , and standard deviation o Construct condence intervals for a population proportion and a population mean . 2. Summary Report :Once you have completed all the steps in your Python script ,you will create a summary report to present your ndings Use the provided template to create your report. You must complete each of the following sections o Introduction :Set the context for your scenario and the analyses you will be performing o Data Visualization .' Identifyr and interpret your chosen data visualization o Descriptive Statistics : identify and interpret measures of central tendency and variability