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E-BOOK
Title Basic Statistical Methods and Models for the Sciences / Judah Rosenblatt.
Imprint Chapman and Hall/CRC, 2017.

Copies/Volumes

LOCATION CALL # STATUS
 Internet  Electronic Book    AVAILABLE
Description 1 online resource (296 pages)
Bibliog. Includes bibliographical references and index.
Note Available only to authorized UTEP users.
Subject Science -- Statistical methods.
Statistics.
Statistics
Science -- statistics & numerical data.
Genre Statistics.
Statistics.
Einf├╝hrung.
Contents Cover; Title Page; Half Title; Copyright Page; Preface; Table of Contents; Chapter 1 Introduction; Section 1.1 Scientific Method; Section 1.2 The Aims of Medicine, Science, and Engineering; Section 1.3 The Roles of Models and Data; Section 1.4 Deterministic and Statistical Models; Definition Deterministic models; Definition Statistical models; Section 1.5 Probability Theory and Computer Simulation; Definition Monte Carlo simulation; Chapter 2 Classes of Models and Statistical Inference; Section 2.1 Statistical Models -- the Frequency Interpretation; Definition The frequency interpretation.
Section 2.2 Some Useful Statistical ModelsTopic Normal (Gaussian) distributions; Topic Binomial distributions; Topic Poisson distributions; Topic Uniform distributions; Topic Exponential distributions; Topic Weibull distributions; Topic Gamma distributions; Topic Negative binomial distributions; Topic Hypergeometric distributions; Section 2.3 Narrowing Down the Class of Potential Models; Topic Distinguishing characteristics of statistics; Chapter 3 Sampling and Descriptive Statistics; Section 3.1 Representative and Random Samples; Definition Representative sample.
Definition Random sampling from a finite population without replacementDefinition Random sampling from a finite population with replacement; Assertion The importance of random sampling; Topic Sampling from a theoretical population; Topic Random sampling from a finite population; Section 3.2 Descriptive Statistics of Location; Topic Long-run usual (and unusual) behavior of successive means; Section 3.3 Descriptive Statistics of Variability; Definition Population and sample standard deviations; Topic The two-sigma rule-of-thumb; Section 3.4 Other Descriptive Statistics; Topic Time series plots.
Topic Scatter plotsTopic The Correlation Coefficient; Definition Sample Correlation Coefficient; Topic The empirical cumulative distribution function (EDF); Chapter 4 Survey of Basic Probability; Section 4.1 Introduction; Section 4.2 Probability and its Basic Rules; Definition Sample space; Definition Event, occurrence of a given event; Topic Formation of events from other events; Definitions Formation of events from other events; Definition Probability Measure; Theorem Bonferroni Inequalities; Section 4.3 Discrete Uniform Models and Counting; Topic Systematic counting methods.
Theorem Counting sequencesTheorem Corollary to Theorem 4.11, ordered sampling; Definition Symbols for j-factorial and the binomial coefficient; Theorem Corollary to Theorems 4.11 and 4.12; Section 4.4 Conditional Probability; Definition Conditional probability of A given B; Theorem The stratified sampling theorem; Topic Relation between random sample and random sampling one at a time without replacement; Theorem Probability of intersection and conditional probability; Section 4.5 Statistical Independence; Definition Statistical independence of events A and B.
Summary The use of statistics in biology, medicine, engineering, and the sciences has grown dramatically in recent years and having a basic background in the subject has become a near necessity for students and researchers in these fields. Although many introductory statistics books already exist, too often their focus leans towards theory and few help readers gain effective experience in using a standard statistical software package. Designed to be used in a first course for graduate or upper-level undergraduate students, Basic Statistical Methods and Models builds a practical foundation in the use of statistical tools and imparts a clear understanding of their underlying assumptions and limitations. Without getting bogged down in proofs and derivations, thorough discussions help readers understand why the stated methods and results are reasonable. The use of the statistical software Minitab is integrated throughout the book, giving readers valuable experience with computer simulation and problem-solving techniques. The author focuses on applications and the models appropriate to each problem while emphasizing Monte Carlo methods, the Central Limit Theorem, confidence intervals, and power functions. The text assumes that readers have some degree of maturity in mathematics, but it does not require the use of calculus. This, along with its very clear explanations, generous number of exercises, and demonstrations of the extensive uses of statistics in diverse areas applications make Basic Statistical Methods and Models highly accessible to students in a wide range of disciplines.
Other Title Print version: 9781584881476