CS513 Assignment 1 Solution Fall 2026

This assignment requires applying data preprocessing and statistical analysis techniques to two distinct datasets. For the retail enterprise scenario, you must perform feature scaling on customer purchase metrics. For the e-commerce fulfillment scenario, you will calculate descriptive statistics and identify anomalies in delivery times. You must provide step-by-step calculations and formatted tables for all transformations and metrics.

1. 1

   Question 1: Data Cleaning, Preprocessing, and Normalization Pipeline

   10 marks

   Task 1.1 requires applying Min-Max Normalization to the Annual Spend column to scale values between 0 and 1, showing all steps and a final table. Task 1.2 requires Z-Score Standardization for the Age column, which involves calculating the mean and standard deviation before computing the standardized scores for each customer.

2. 2

   Question 2: Performance Tracking, KPI Evaluation & Outlier Management

   10 marks

   Task 2.1 asks for the calculation of the mean, median, mode, and range for the provided 10-day fulfillment time dataset, including all basic calculation steps. Task 2.2 requires using the Interquartile Range method to find the first and third quartiles, calculate the IQR, determine the lower and upper bounds, and identify any global outliers.

What to submit

One doc or docx document.

Topics covered

Min-Max Normalization Z-Score Standardization Descriptive Statistics Interquartile Range Outlier Detection Data Preprocessing