Data Science Assignment 1 – Full Solutions (Q1 to Q19) This video covers the complete step-by-step solutions for the Internal Test / Assignment 1 of the Data Science subject. Includes full theory + formulas + numerical solutions of: ✔ Part A – Statistical Characterisation Mean, Median, SD, Quartiles, Boxplots, Grouped Median, Correlation, Productivity Analysis ✔ Part B – Similarity & Dissimilarity Euclidean, Manhattan, Minkowski, Supremum, Jaccard, Cosine, Normalization-based similarity ✔ Part C – Data Preprocessing Data quality, missing value handling, smoothing, outlier detection, normalization methods (Min–Max, Z-score, MAD, Decimal Scaling), data integration ✔ Part D – Collaboration Analytics Matching skills, constructing contingency tables, computing dissimilarity, best pairing selection All solutions match the exact question paper, making it perfect for: • MCA students • BCA students • Data Science beginners • University exam preparation • Internal assessments • Practical viva and external viva data science assignment 1 data science internal test solutions data science q1 to q19 statistics for data science similarity and dissimilarity measures mca data science assignment bca data science notes mean median mode quartiles boxplot grouped median euclidean distance manhattan distance minkowski distance supremum jaccard coefficient explained data preprocessing MCA data cleaning methods missing value handling normalization techniques minmax zscore correlation and covariance compatibility analytics student collaboration dataset machine learning basics mca notes bca notes assignment solutions data science #DataScience #Assignment