Ph.D. Statistics is a mathematical science that’s concerned with the interpretation, presentation, analysis, collection, and explanation of data. It is a branch of Mathematics, which has a broad spectrum of academic disciplines ranging from humanities to physical and social sciences.
The study of Statistics deals with mathematical as well as Applied Statistics. Applied Statistics is further studied under two divisions, namely Descriptive Statistics and Inferential Statistics.
Institutes offering Ph.D. Statistics programme require students to involve in the cutting-edge interdisciplinary research in a wide variety of fields. Statistics has become a core component of research in the physical, biological, and social sciences, as well as in traditional computer science domains such as artificial intelligence and machine learning. There is a massive increase in the data acquired, through a scientific measurement, as well as, through the web-based collection. It makes the development of statistical analysis and prediction methodologies more relevant than ever.
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Duration |
2 years |
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Type |
Degree |
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Level |
Doctorate |
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Eligibility |
Post-Graduation |
Students pursuing Ph.D. Statistics must have a strong undergraduate background in Mathematics. The knowledge of linear algebra and advanced calculus is required, and experience with the real analysis is helpful. Although some exposure to undergraduate probability and statistics is expected, skills in Mathematics and Computer Science are more important.
The major areas of departmental research include analysis of observational studies; Bayesian inference, bioinformatics; information theory; decision theory; game theory; high dimensional inference; machine learning; model selection; nonparametric function estimation; and time series analysis.
Students are required to complete a dissertation in some area of theoretical statistics, applied statistics, or probability that is an original contribution of publishable quality and must successfully defend the dissertation in an oral presentation conducted by an institute/university.
Here’s a list of top institutes in India offering Ph.D. Statistics course for eligible candidates:
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S.No. |
University/College |
City |
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1 |
Allahabad University |
Allahabad, Uttar Pradesh |
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2 |
Banaras Hindu University |
Varanasi, Uttar Pradesh |
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3 |
CBM College of Arts and Science |
Coimbatore, Tamil Nadu |
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4 |
Central University of Rajasthan |
Ajmer, Rajasthan |
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5 |
Cochin University of Science and Technology |
Kochi, Kerela |
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6 |
Farook College |
Kozhikode, Kerela |
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7 |
Dibrugarh University |
Dibrugarh, Assam |
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8 |
Chaudhary Charan Singh Haryana Agriculture University |
Hisar, Haryana |
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9 |
Bhavnagar University |
Bhavnagar, Gujarat |
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10 |
Banasthali University |
Tonk, Rajasthan |
This field offers great job opportunities in India and abroad. Statisticians and their analytic skills are highly in demand in today’s job market. Statistics is required in various fields such as business, agriculture, government, private, computer science, scientific, health sciences and other disciplines.
There are immense job opportunities for Ph.D. Statistics scholars. The candidate can work in a wide range of industries. One can become a psychometrist, investment analyst, cryptologist, commodities traders, information scientist etc. One can even get into the field of education and become a professor. The scope of research is also very wide.
Ph.D. Statistics Skills Required
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Job Title |
Description |
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Statistician |
They usually work with theoretical or Applied Statistics. The profession exists in both the private and public sectors. It is common to combine statistical knowledge with expertise in other subjects. Statisticians may even work as employees or as statistical consultants. |
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Business Analyst |
As the name suggests, they analyse an organization or business domain (real or hypothetical) and documents its business, processes, or systems, assessing the business model or its integration with technology. |
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Professor |
Besides teaching, they have to keep updated with current advances in both research and pedagogy. They have to prepare lectures, supervise teaching assistants, and even check grading system. |
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Risk Analyst |
Risk Analysts have to examine a company's investment portfolios, including overseas investments, and analyse the risk involved in associated decisions. They use their analytical skills to project potential losses and make recommendations to limit risk through diversification, currency exchanges and other investment strategies. |
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Data Analyst |
Data Analysts translate numbers into plain English. Every business collects data, whether it's sales figures, logistics, market research, or transportation costs. A data analyst's job is to take that data and use it to help companies make better business decisions. |
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Content Analyst |
They have to lead and handle regular project meetings, assess and make strategies to manage digital assets and platform functions on given projects. They handle project schedules, milestones and records for associated groups. They deliver content to downstream partners, create content and data targets with key internal and external stakeholders. Moreover, they have to coordinate with online product development team to maintain quality deliverables. Other responsibilities of content analysis include developing project plans and supervise tasks. Plus, coordinating content update and changes within overall product management process. |
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Statistic Trainer |
Just like teachers, they must be able to speak in front of a crowd, produce and understand training materials, work closely with individuals and evaluate how well employees have learned. Trainers might work manually with written materials or use the educational and testing software as part of the training process. Statistic trainers must be able to develop and maintain a budget for their work. |
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Data Scientist |
Data Scientist’s duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems. They should also be able to perform statistical analysis. |
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Biostatistician |
They use or apply Mathematics and Statistics to varying categories in Biology. They design biological experiments primarily in the field of agriculture and medicine; they collect, dissect, and summarize the data, and release information based on the findings of that data. |
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Econometrician |
An Econometrician is a type of economist who integrates Statistics and Mathematics into Economic analysis. They use highly specialized Math and Statistics to generate quantifiable results for a company’s benefit. |
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Job Areas |
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Recruiters |
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Duties of a Statistician |
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Salary |
In India, the average salary of a statistician can be expected between Rs. 2.5 to 3.5 lacs per year. With experience over the years, they can earn more than Rs. 4.5 lacs per year. |
a) GATE Qualification
b) UGC/CSIR NET qualified or NBHM or equivalent qualification
c) DST-INSPIRE Fellowship
Ph.D is a research program in Statistics. The Ph.D. Statistics is of two-year duration. There are four areas of specialization. These are Biostatistics, Mathematical/ Probability Statistics, Statistical Modelling, and Actuarial Science/ Financial Mathematics. Thesis work has to be submitted by the candidate after completion of 12 months of study of the subject. A final PhD exam has to be cleared by the candidate to get the degree.
Biostatistics - It is the application of Statistics to a wide range of topics in Biology. The Science of Biostatistics encompasses the design of biological experiments, especially in medicine, pharmacy, agriculture and fishery. A major branch of this is medical biostatistics is exclusively concerned with medicine and health.
Mathematical/Probability Statistics – in Ph.D. Statistics, this branch of Mathematics is about probability distributions, and the two topics are often studied together. However, probability theory contains much that is mostly of mathematical interest and not directly relevant to Statistics. Moreover, many topics in Statistics are independent of probability theory.
Statistical Modelling - It is a class of mathematical model, which embodies a set of assumptions concerning the generation of some sample data, and similar data from a larger population. A statistical model represents, often in considerably idealized form, the data-generating process.
Financial Mathematics - It is also known as the study of quantitative finance. In Ph.D. Statistics, this is a field of Applied Mathematics, concerned with financial markets. Generally, Financial Mathematics will derive and extend the mathematical or numerical models without necessarily establishing a link to financial theory, and includes observed market prices as input as well.