Qualification: 
Ph.D, MBA, MPhil, MSc, B.Ed., BSc
m_dhanya@asb.kochi.amrita.edu

Dr. Dhanya Manayath currently serves as an Assistant Professor (Sr. Gr.) at the Department of Management, Kochi. She has more than twelve years of experience in postgraduate teaching, that include coordinating and handling various academic and research activities. She has graduated her Master of Science (M. Sc.) in Statistics and also holds a Master’s degree in Business Administration (MBA). She obtained her UGC-NET in Management and M. Phil. in Statistics.

Dr. Dhanya was awarded her Ph. D. in Statistics on the topic “Estimation of reliability measures of some heavy tailed life time distributions” from Mahatma Gandhi University, Kerala, India. She has attended a number of national and international conferences where she has presented research papers in her area of specialization. She has publications in refereed national and international journals to her credit. Her areas of interest include Business Statistics, Operations Research, Research Methodology, Data Science, Business Analytics and Marketing Research. She is also a member of the Kerala Statistical Association.

Teaching Interest

  • Data Analytics
  • Operations Research
  • Research Methodology
     

Publications

Publication Type: Journal Article

Year of Publication Title

2019

Dr. Dhanya M., .S.R., S., and A., S., “Networking telemedicine through kiosk: a tripartite approach”, Int. J. of Business Excellence, 2019.

2019

Dr. Dhanya M., Raja Sreedharan V., Vimal, K. E. K., and Sreekumar, A., “Understanding the role of logistics in humanitarian operations: key findings and analysis from literature”, Int. J. Logistics Systems and Management, 2019.

2018

Dr. Dhanya M. and Jeevanand, S., “Stress Strength reliability of Power Function Distribution based on Records”, Journal of Statistical Application and Probability, vol. 7, no. 1, pp. 39-48, 2018.[Abstract]


This paper deals with the estimation of Stress Strength reliability, R=P(Y <X) when X and Y are two independent Power function distributions with different shape parameters but having the same scale parameter and the data on strength are record values. The maximum likelihood estimators and the Bayes estimators under squared error loss function and linex loss function of the reliability under stress- strength model for the power function distribution are obtained. Effectiveness of these estimators are evaluated using Monte Carlo simulation study.

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2018

Raja Sreedharan V., R, T., Dr. Dhanya M., and P, A., “Lean Six Sigma Implementation in an OEM: A Case Based Approach”, International Journal of Process Management and Benchmarking (Accepted)., 2018.

2015

Dr. Dhanya M. and S, J. E., “Quasi Bayesian Estimation of Stress Strength Model for the Power Function Distribution”, International Journal of Current Research, vol. 7, no. 11, pp. 22921-22927, 2015.[Abstract]


The reliability of a system is the probability that when operating under stated environmental conditions, the system will perform its intended function adequately. We consider the strength of the system X and the stress Y as random variables. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X>Y. The quasi-likelihood function was introduced by Wedderburn (1974) to be used for estimating the unknown parameters in generalized linear models.

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PDF iconQuasi-Bayesian-Estimation-of-Stress-Strength-Model-for-the-Power-Function-Distribution.pdf

2014

Dr. Dhanya M. and Jeevanand, E. S., “Semi-Parametric Estimation of Pxy(X,Y)/X>Y for the Power Function Distribution”, International Journal of Engineering, Science and Mathematics, vol. 3, pp. 94-101, 2014.

2013

M. Smarty, Dr. Dhanya M., and P, S. K., “A Study on the Conflict Resolution Styles of Generation Y Students in Indian Context”, International Journal of Global Business, pp. 81-90, 2013.[Abstract]


The reliability of a system is the probability that when operating under stated environmental conditions, the system will perform its intended function adequately. We consider the strength of the system X and the stress Y as random variables. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X>Y. The quasi-likelihood function was introduced by Wedderburn (1974) to be used for estimating the unknown parameters in generalized linear models.

More »»
PDF iconA-Study-on-the-Conflict-Resolution-Styles-of-Generation-Y-Students-in-Indian-Context.pdf

Publication Type: Conference Paper

Year of Publication Title

2014

Dr. Dhanya M. and Jeevanand, E. S., “Semi-Parametric Estimation of Pxy(X,Y)/X>Y”, in International Conference on Mathematical Modelling and applications to Industrial Problems, 2014.

2011

Dr. Dhanya M. and Jeevanand, E. S., “Bayes Estimation of Px,Y(X >Y) for the Power function Distribution Based on Records”, in National Seminar on Stochastic Modelling and Analysis, 2011.

Publication Type: Conference Proceedings

Year of Publication Title

2014

Dr. Dhanya M. and Jeevanand, E. S., “Estimation of P (y x) of Power Function Distribution”, International Conference on Mathematics and its Applications. Shanga Verlag, Villupuram, pp. 1716-1730, 2014.

2012

Dr. Dhanya M. and Jeevanand, E. S., “Quasi Bayesian Estimation of Px,y((x,y)/x >y) for the Lomax distribution”, International Conference On Mathematical Modeling And Applied Soft Computing, vol. 1. Shanga Verlag, pp. 1089-1096, 2012.