Statistics and its Applications

ASIS KUMAR CHATTOPADHYAY is professor of statistics at the University of Calcutta, Kolkata, India. He has completed his PhD in Statistics from the University of Calcutta. With over 50 papers in reputed international journals, proceedings and edited volume, he has published three books on statistics including Statistical Methods for Astronomical Data Analysis (Springer). He has successfully guided seven PhD and MPhil students. His main interests are in stochastic modelling, demography, operations research and astrostatistics.GAURANGADEB CHATTOPADHYAY is associate professor of statistics at the University of Calcutta, Kolkata, India. He has completed his PhD in Statistics from the University of Calcutta. He has successfully guided four PhD and MPhil students. An active member of Calcutta Statistical Association, Indian Science Congress Association and Indian Association for Productivity, Quality and Reliability, his main interests are in statistical inference, reliability analysis and survey sampling.

• Chapter 1. Abisa Sinha, Fragmentation of Young Massive Clusters: A Hybrid Monte–Carlo Simulation Study.- Chapter 2. Anamika Dutta and Kishore K. Das, A Study on DNA Sequence of Rice using Scoring Matrix Method and ANOVA Technique.- Chapter 3. Sungsu Kim and Ashis SenGupta, Regressions Involving Circular Variables: An Overview.- Chapter 4. Ramesh M. Mirajkar and Bhausaheb G. Kore, On Construction of Prediction Interval for Weibull Distribution.- Chapter 5. Thorsten Dickhaus, Combining high-Dimensional Classification and Multiple Hypotheses Testing for the Analysis of Big Data in Genetics.- Chapter 6. Tapan Kumar Chakrabarty and Dreamlee Sharma, The Quantile-based Skew Logistic Distribution with Applications.- Chapter 7. Jiming Jiang, A Note on Monte–Carlo Jackknife: McJack and Big Data.- Chapter 8. Jogesh Babu, Introduction to the Detection and Statistical Challenges of Exoplanets.- Chapter 9. Thuan Nguyen and Jiming Jiang, A Connection between the Observed Best Prediction and the Fence Model Selection Method.- Chapter 10. Siegfried Gabler, Matthias Ganninger and Partha Lahiri, A New Approximation to the True Randomization-Based Design Effect.- Chapter 11. Madhura Mandal and Premadhis Das, Confounded Factorial Design with Partial Balance and Orthogonal Sub- Factorial Structure.- Chapter 12. Christian P. Robert, Beyond the Bayes Factor, a New Bayesian Paradigm for Handling Hypothesis Testing.- Chapter 13. Tommy Wright, No Calculation when Observation Can be Made.- Chapter 14. Sumanta Adhya, Debanjan Bhattacharjee and Tathagata Banerjee, Design Weighted Quadratic Inference Function Estimators for Superpopulation Parameters.- Chapter 15. Jyotirmoy Sarkar and Bikas K. Sinha, Detecting a Fake Coin of a Known Type.