Statistics for Data Science 1 - W3_L4: Describing numerical data - measures of dispersion- range

Welcome to Week 3 Lecture 4 of the course "Statistics for Data Science - I" by Prof. Andrew Thangaraj. Full Course: https://study.iitm.ac.in/ds/course_pages/BSMA1002.html Video Overview This lecture introduces the Measures of Dispersion, which describe how data values spread around the center of a dataset — an important aspect often missed by Measures of Central Tendency (Mean, Median, Mode). You’ll learn about the Range, its simplicity and limitations due to sensitivity to outliers, and why dispersion measures are essential for accurate data interpretation. The session compares datasets with identical means but different distributions to highlight how variability impacts analysis. We then explore Variance and Standard Deviation, understanding their formulas, interpretation, and the difference between population and sample calculations. Practical examples using Google Sheets demonstrate how adding or multiplying constants affects these measures, helping you gain a deeper understanding of data variability. About IIT Madras' online Bachelor of Science programme IIT Madras offers four-year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, Visit: https://www.iitm.ac.in/academics/study-at-iitm/non-campus-bs-programmes #MeasuresOfDispersion #Variance #StandardDeviation #Range #DataSpread #DataVariability #Statistics #DataAnalysis #Mean #Median #Mode #CentralTendency #Outliers #PopulationVariance #SampleVariance #GoogleSheets #DataScience #DataAnalytics #DescriptiveStatistics #IITMadras #OnlineLearning #BSProgramme #Education #StatisticsForDataScience