Case Study: Analyzing Customer Satisfaction in an E-commerce Business Background: An e-commerce company is interested in evaluating customer satisfaction to improve its services. A survey was conducted, collecting responses from 500 customers. The survey measured customer satisfaction (scale of 1 to 10), delivery time (in days), product quality (scale of 1 to 5), and customer age. Objective: Perform a descriptive summary, visualize the data, and calculate confidence intervals for key metrics. Data: The dataset contains responses from 500 customers. It includes the following columns: Customer_ID: Unique identifier for each customer Satisfaction_Score: Customer satisfaction rating on a scale of 1 to 10 Delivery_Time: Delivery time in days Product_Quality: Product quality rating on a scale of 1 to 5 Customer_Age: Age of the customer A CSV file containing the data can be downloaded in the following file. Tasks: 1. Descriptive Summary: Calculate the mean, median, standard deviation, and interquartile range (IQR) for Satisfaction_Score, Delivery_Time, Product_Quality, and Customer_Age. Identify skewness and kurtosis for each variable. Apply Z-score or IQR methods to detect and analyze the outliers of delivery time or satisfaction score. Discuss the impact of these outliers on the overall analysis