P.C. Mahalanobis: Architect of Statistical Innovation
“Statistics is the foundation of meaningful insights in data science — unappreciated in abundance, sorely missed in scarcity”
Before the advent of modern computers, large calculations were handled by employing individuals known as ‘human computers.’ These people manually performed computations that were essential for various scientific and statistical studies. One notable figure who utilized human computers in his work was Prasanta Chandra Mahalanobis, a pioneering Indian statistician of the early 20th century.
P.C. Mahalanobis was born on June 29, 1893, in Calcutta (now Kolkata), India, into an academically inclined family. He received his Bachelor of Science degree from Presidency College in Calcutta, studying under renowned scientists like Jagadish Chandra Bose and Prafulla Chandra Ray. His contemporaries included Meghnad Saha and Subhash Chandra Bose. In 1913, Mahalanobis traveled to England to study at King’s College, Cambridge, where he met mathematical prodigy Srinivasa Ramanujan and discovered the journal Biometrika. This journal ignited his interest in statistical models that could analyze large-scale and complex phenomena.Upon returning to India, Mahalanobis took a temporary position teaching physics at Presidency College, eventually becoming a professor of physics in 1922. His journey into statistics began in 1917 when Sir Brajendra Nath Seal asked him to analyze exam records of Calcutta University. Three years later, N. Annandale of the Zoological and Anthropological Survey of India provided him with anthropometric data, leading to his significant research on the Mahalanobis distance, a measure used in multivariate analysis.During the 1920s, Mahalanobis tackled substantial datasets, including analyzing decades of rainfall and flood data in Odisha and Bengal. His findings led to the construction of major infrastructure projects like the Hirakud Dam and the Durgapur Barrage. In the 1930s, he conducted a large-scale survey on Bengal’s jute cultivation, demonstrating the accuracy and reliability of his statistical methods over complete enumeration.
Mahalanobis founded the Indian Statistical Institute (ISI) in 1931, significantly advancing the field of statistics in India. The ISI became a global hub for statistical research and education. He also played a crucial role in establishing the statistics department at Calcutta University in 1941, the first in Asia to offer a postgraduate degree in statistics. In 1938, he organized India’s first statistics conference, presided over by R.A. Fisher, a leading statistician of the time. He also launched Sankhyā: The Indian Journal of Statistics in 1933.
Post-independence, Mahalanobis contributed significantly to India’s national planning. Appointed to the Planning Commission by Prime Minister Jawaharlal Nehru in 1955, he was instrumental in designing the Second Five-Year Plan (1956–61), known as the Mahalanobis Plan, which emphasized industrialization and economic development. His expertise in survey methodologies helped establish the National Sample Survey Office (NSSO), which conducted vital surveys to understand poverty and inequality in India.
In today’s context, data science, artificial intelligence (AI), machine learning (ML), and Big Data have revolutionized various fields, including policymaking. However, the core principles of statistics remain indispensable. Statistics provide the frameworks and methodologies to extract meaningful insights from data, enabling informed decision-making across domains. Data scientists leverage statistical techniques for exploration, cleaning, interpretation, and predictive modeling, essential for developing accurate AI and ML models.
Mahalanobis’s legacy underscores the enduring relevance of statistics in the age of AI. As Geoffrey Hinton, a pioneer in AI, has rightly said “ To get machines to do the kind of things that humans are good at, like vision, language, and motor control, we need to understand statistics ”.
As statisticians, it is incumbent upon us to emphasize the pivotal role of statistical knowledge in data science. Amidst the excitement surrounding AI and Big Data, statistical rigor ensures that data-driven decisions are reliable and beneficial for society at large. Mahalanobis’s vision — that statistics serve both scientific advancement and societal welfare — remains a guiding principle, ensuring that data analytics continue to drive innovation responsibly and ethically.
Mahalanobis’s life and work serve as an enduring testament to the transformative power of statistical science, from his foundational contributions to India’s statistical landscape to his lasting impact on global statistical theory and practice.
Today, on the 29th of June, India observes National Statistics Day to honor the remarkable contributions of the late Professor Prasanta Chandra Mahalanobis in the fields of statistics and economic planning. His pioneering work laid the foundation for modern statistical methods and their application in various sectors.
As statisticians, let us carry forward his legacy by leveraging data to enhance human welfare and support nation-building efforts. By utilizing statistical tools and techniques, we can address critical issues such as health, education, poverty alleviation, and sustainable development. Through accurate data analysis and evidence-based decision-making, we can contribute significantly to the progress and well-being of our society.