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Schaum's Outlines (/ ʃ ɔː m /) is a series of supplementary texts for American high school, AP, and college-level courses, currently published by McGraw-Hill Education Professional, a subsidiary of McGraw-Hill Education.
This book was written before computer programmes were available, so it gives the detail needed to make the calculations manually.Cited in more than 1,381 publications between 1961 and 1975. [6] Importance: Influence. Biometry: The Principles and Practices of Statistics in Biological Research . Authors: Robert R. Sokal; F. J. Rohlf
Seymour Saul Lipschutz (born 1931 died March 2018) was an author of technical books on pure mathematics and probability, including a collection of Schaum's Outlines. [1] Lipschutz received his Ph.D. in 1960 from New York University's Courant Institute. [2] He received his BA and MA degrees in Mathematics at Brooklyn College.
This is a list of probability topics. It overlaps with the (alphabetical) list of statistical topics. There are also the outline of probability and catalog of articles in probability theory. For distributions, see List of probability distributions. For journals, see list of probability journals.
Much research involving probability is done under the auspices of applied probability.However, while such research is motivated (to some degree) by applied problems, it is usually the mathematical aspects of the problems that are of most interest to researchers (as is typical of applied mathematics in general).
Statistics is a field of inquiry that studies the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines , from the physical and social sciences to the humanities ; it is also used and misused for making informed decisions in all areas of business and government .
This is called the addition law of probability, or the sum rule. That is, the probability that an event in A or B will happen is the sum of the probability of an event in A and the probability of an event in B, minus the probability of an event that is in both A and B. The proof of this is as follows: Firstly,