Sandsynlighedsregning og statistik
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Statistics
A Concise Mathematical Introduction for Students, Scientists, and Engineers
Udgivet af John Wiley & Sons Inc
ISBN
9781119675846
Om denne bog
Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programmi…
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Bogdetaljer
Forfatter
David W. Scott
Forlag
John Wiley & Sons Inc
Kategori
Sandsynlighedsregning og statistik
ISBN-13
9781119675846
EAN
9781119675846
Format
Hæftet
Sprog
Engelsk
sider
192
Undertitel
- A Concise Mathematical Introduction for Students, Scientists, and Engineers
Produktbeskrivelse
Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.
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