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Scott D.W. Statistics: A Concise Mathematical Introduction for Students, Scientis, and Engineers

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Scott D.W. Statistics: A Concise Mathematical Introduction for Students, Scientis, and Engineers
Wiley, 2020. — 184 p. — ISBN 9781119675846.
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 discreterandom 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.
Data Analysis and Understanding
Classical Probability
Random Variables and Models Derived From Classical Probability and Postulates
Bivariate Random Variables, Transformations, and Simulations
Approximations and Asymptotics
Parameter Estimation
Hypothesis Testing
Confidence Intervals and Other Hypothesis Tests
Topics in Statistics
Appendices
Notation Used in This Book
Common Distributions
Using R and Mathematica For This Text
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