### Abstract

There are only two kinds of experiments: Random experiments where the outcome of the experiment is not certain and deterministic experiments where outcome of the experiment is certain (for example if we know the pressure P and the volume V, we can predict Temperature T, PV=T). However, in most of the real-life situations we deal with random experiments, and we always calculate the probability of the event in the context of random experiments only. I do not agree with the editor’s example, “the sun will rise tomorrow from the east is certain.” This is a universal truth rather than a random experiment, so we should not calculate the probability!

Original language | English |
---|---|

Pages (from-to) | 3-8 |

Number of pages | 1 |

Journal | Biometric Bulletin |

Volume | 36 |

Issue number | 3 |

Publication status | Published - Oct 2019 |

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*Biometric Bulletin*, vol. 36, no. 3, pp. 3-8.

**Response to the Editor Basic Theme -II.** / Kumar, Kuldeep.

Research output: Contribution to journal › Comment/debate › Research

TY - JOUR

T1 - Response to the Editor Basic Theme -II

AU - Kumar, Kuldeep

PY - 2019/10

Y1 - 2019/10

N2 - In 2016 I had the opportunity to review the book “A Certain Uncertainty: Nature’s Random Ways” by M P. Silverman, 2014 published by Cambridge University Press, for the Journal of the Royal Statistical Society. This is a very interesting book which teaches the application of not only probability but other statistical reasoning by using real life scenarios from stock market, sports and medicine to global climate change. As mentioned in the review, in this book each chapter introduces relevant statistical principles by giving interesting examples either from the real world or by using measurements from some experiment conducted in a laboratory. In this way, the author has discussed some controversial issues including those relating to sample size, p-values, selection of Bayes priors, and the relationship between maximum likelihood and maximum entropy. I personally think all statisticians should read this book and perhaps it will answer some of the questions or concerns raised by the Hon’ble Editor. One of the good examples to explain the editor’s query is to answer the question of whether climate change is there, or earth temperature is rising. There are two schools of thoughts here. One is the view of the climate change activist who analyses the data from 1870 onwards (time since the records are kept) and shows that there is a significant trend in global warming. However, there is another school which thinks earth is billion-year-old and we don’t have data about the global warming before 19th century and this may be just a cycle. This cycle maybe 300-500 years and cycle will be over in a few centuries. Of course, paleobotanists are trying to answer these questions looking at the tree rings.There are only two kinds of experiments: Random experiments where the outcome of the experiment is not certain and deterministic experiments where outcome of the experiment is certain (for example if we know the pressure P and the volume V, we can predict Temperature T, PV=T). However, in most of the real-life situations we deal with random experiments, and we always calculate the probability of the event in the context of random experiments only. I do not agree with the editor’s example, “the sun will rise tomorrow from the east is certain.” This is a universal truth rather than a random experiment, so we should not calculate the probability!

AB - In 2016 I had the opportunity to review the book “A Certain Uncertainty: Nature’s Random Ways” by M P. Silverman, 2014 published by Cambridge University Press, for the Journal of the Royal Statistical Society. This is a very interesting book which teaches the application of not only probability but other statistical reasoning by using real life scenarios from stock market, sports and medicine to global climate change. As mentioned in the review, in this book each chapter introduces relevant statistical principles by giving interesting examples either from the real world or by using measurements from some experiment conducted in a laboratory. In this way, the author has discussed some controversial issues including those relating to sample size, p-values, selection of Bayes priors, and the relationship between maximum likelihood and maximum entropy. I personally think all statisticians should read this book and perhaps it will answer some of the questions or concerns raised by the Hon’ble Editor. One of the good examples to explain the editor’s query is to answer the question of whether climate change is there, or earth temperature is rising. There are two schools of thoughts here. One is the view of the climate change activist who analyses the data from 1870 onwards (time since the records are kept) and shows that there is a significant trend in global warming. However, there is another school which thinks earth is billion-year-old and we don’t have data about the global warming before 19th century and this may be just a cycle. This cycle maybe 300-500 years and cycle will be over in a few centuries. Of course, paleobotanists are trying to answer these questions looking at the tree rings.There are only two kinds of experiments: Random experiments where the outcome of the experiment is not certain and deterministic experiments where outcome of the experiment is certain (for example if we know the pressure P and the volume V, we can predict Temperature T, PV=T). However, in most of the real-life situations we deal with random experiments, and we always calculate the probability of the event in the context of random experiments only. I do not agree with the editor’s example, “the sun will rise tomorrow from the east is certain.” This is a universal truth rather than a random experiment, so we should not calculate the probability!

M3 - Comment/debate

VL - 36

SP - 3

EP - 8

JO - Biometric Bulletin

JF - Biometric Bulletin

SN - 8750-0434

IS - 3

ER -