PC Mahalanobis' birth anniversary observed as National Statistics Day in India
The National Statistics Day to commemorate the birth anniversary of PC Mahalanobis, often referred to as the 'father of Indian statistics', is being marked today. On June 29, 2006, the first Statistics Day was observed.
"Good Health and Well Being and Gender Equality", is the theme for National Statistics Day 2020, tweeted Union Minister for Environment, Prakash Javadekar. "Tribute to Prof PC Mahalanobis for the notable contribution made by him in the field of economic planning and statistical development on his birth anniversary," Mr Javadekaer wrote on social media.
Lok Sabha Speaker Om Birla also paid his respect to PC Mahalanobis, highlighting the importance of statistics in India's battle against coronavirus. He wrote, "Tributes to renowned statistician, Padma Vibhushan Prof Prashant Chandra Mahalanobis on his birth anniversary, celebrated as the National Statistics Day. Equipped with profound knowledge of statistical tools, his social-economic plans and policies, propelled India's development." The Speaker underscored the significance of statistics in every field and in everyday life. "...in wake of COVID-19 pandemic, data is being analysed to develop a treatment. This gives a glimpse of importance of statistics in our lives," the Speaker said.
Rajasthan Chief Minister Ashok Gehlot said, "On Statistics Day, my tribute to great Indian scientist and statistician Prof PC Mahalanobis on his birth anniversary. He founded Indian Statistical Institute and played a key role in the field of economic planning and statistical development in country...."
This year, National Statistics Day is being observed through a series of virtual events due to the COVID-19 pandemic. The day is dedicated to statistics in daily life and creating awareness among people on how statistics helps in framing policies.
The key contribution of PC Mahalanobis is known as "Mahalanobis distance'. The formula is used to find the distance between a point and a distribution, based on measurements in multiple dimensions. It is widely used in the field of cluster analysis and classification.