Context: Mahalanobis is perhaps more relevant today when the accuracy of different sorts of data — from economic data to COVID-19 data — is under the scanner.
Data collection methodology by Mahalanobis
- Starting from the first area sample in the whole world for jute forecast in 1934, Mahalanobis built up a strong and trustworthy statistical heritage in India.
- Mahalanobis envisaged large-scale sample surveys as statistical engineering rather than pure theory of sampling.
Survey of Bengal famine by Mahalanobis
- Mahalanobis also known as India’s ‘Plan Man’, conducted a large-scale sample survey of Bengal’s famine-ravaged villages.
- The period of analysis was between July 1944 and February 1945 for causal analysis, and to assess the extent of the disaster and an estimate of the number of people affected.
- Key findings of the survey
- It showed that one-fourth of the number of families (1.5 million people) who had owned rice land before the famine had either sold in full or in part their rice land or had mortgaged it.
- The survey also showed that the economic position of nearly four million people deteriorated during the famine.
- Economic disparities became further accentuated during the famine.
Relevance of such data in the content of COVID-19 pandemic
- Mahalanobis is certainly more relevant today when the accuracy of different sorts of data from economic data to COVID-19 data is the need of the hour.
- Bengal’s famine survey reminds us that we need estimates of the millions who will lose jobs or livelihoods and of the hundreds of millions whose economic conditions will deteriorate in today’s COVID-19-hit India.
- Use of technology:
- It is clear that given the spread and nature of pandemic, conducting household surveys with no error margin will be a difficult task. However, various technological tools can be helpful in this area
- Even Mahalanobis never shied away from technology, whether in bringing statistical technology through volumes of Biometrika in his voyage from England, or even bringing computers to India.
- The Mahalanobis-led Indian Statistical Institute procured India’s first computer in 1956 and the second in 1959.
- Minimizing the errors in data collection
- Cross-checking by an independent set of agents for data collection can be done so that more accurate data can be collected.
- System of data-based policymaking
- According to Mahalanobis “Statistics are a minor detail, but they do help.” This is an eternal truth.
- Therefore the need of the hour is listening to the heartbeats of data and for framing data-based policy decisions for human welfare and national development.
Contributions of Prof. PC Mahalanobis
- Prof. PC Mahalanobis is known for his invaluable contribution
- In the fields of economic planning and statistical development in the post-independent era
- And in establishing the National Statistical System.
- Father of Indian Statistics: He became the 1st Indian statistician to receive world recognition and is called as Father of Indian Statistics.
- Laid the foundation of the Indian Statistical Institute (ISI): At Kolkata in 1931, which was declared an autonomous “Institute of National Importance” through an act of Parliament in 1959. ISI celebrates 29th June as the Worker Day.
- Mahalanobis distance: In 1936, Mahanalobis introduced a statistical measure called Mahalanobis distance, widely used in cluster analysis and classification techniques for which he is widely known.
- He was instrumental in establishing the National Sample Survey (NSS) in 1950 and the Central Statistical Organization in 1951.
- He was also instrumental in formulating India’s second five-year-plan (1956-1961), which laid the blueprint for industrialisation and development in India.
- Mahalanobis’ birth anniversary is celebrated as the National Statistics Day.
- Interpenetrating Network of Subsamples: The desire to have built-in cross-checks and to get an estimate of errors in sampling led him to introduce the Inter-Penetrating Network of Subsamples, which is now considered as the curtain-raiser for re-sampling procedures like Bootstrap, a revolutionary concept of statistics indeed.
Image Source: TH