Statistics for the Sciences

Name: Statistics for the Sciences
Price: 33.98 USD
Availability: InStock
ISBN: 9780534387747

ISBN-10: 0534387748

ISBN-13: 9780534387747

Edition: 2005

Authors: Martin Buntinas, Gerald M. Funk

List price: $199.95

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Addressing a growing need in the statistics marketplace, this new text is the only introductory statistics book designed specifically for students majoring in the sciences. STATISTICS FOR THE SCIENCES lets students see the beauty of statistics using calculus, and contains applications directly tied to natural and physical sciences. No longer will science majors have to learn from texts with applications that are not relevant to their studies. In STATISTICS FOR THE SCIENCES, the math is at the right level, and the exercises and examples appeal to students majoring in natural and physical sciences.

Book details

List price: $199.95
Copyright year: 2005
Publisher: Brooks/Cole
Publication date: 1/8/2004
Binding: Hardcover
Pages: 564
Size: 8.00" wide x 9.50" long x 1.00" tall
Weight: 2.552
Language: English

Martin Buntinas holds a Ph. D. in mathematics from Illinois Institute of Technology. In addition to serving as department chair at Loyola University from 1992 to 1998, he has been a Senior Fulbright Scholar. His research interests include approximation theory, Fourier series, topological sequence spaces, and functional analysis.

Gerald Funk received his Ph. D. in statistics from Michigan State University. Before joining the faculty at Loyola University, Gerry taught at Michigan State University, Purdue University, Oklahoma State University, and Northern Illinois University. He is widely published in statistics research journals and extremely active in the Chicago chapter of the ASA. His research interests include statistics, applied probability, and computer simulation.



Preface 1


Introduction


What is Statistics? Sampling and Estimation


Precision Versus Confidence


Hypothesis Testing


Preview


Review Exercises



Description of data


Introduction


Categorical Data


Ordinal Data


Ratio Data


Frequency Tables and Histograms


Grouped Data and Sturge+s Rule


Stem and Leaf Plot


Five-number Summary


Box Plot


The Mean


Variance and Standard Deviation


Ogives and Quantiles


Exploratory Data Analysis


Formulas for Histograms (optional)


Review Exercises



Probability theory


Overview


Definitions


Probabilities of Events


Rules of Probability


Three Diagrams


Bayes+ Formula


Review Exercises



Discrete random variables


Introduction


Basic Properties of Discrete Random Variables


Probability Histograms


Expected Value or Mean of a Random Variable


Functions of Random Variables


Variance and Standard Deviation of a Random Variable


Law of Large Numbers (optional)


Review Exercises



Continuous random variables


Continuous Random Variables


Basic Properties


Percentiles and Modes


Expected Value or Mean


Functions of Random Variables


Variance and Standard Deviation


Chebyshev+s Inequality


Review Exercises



Special discrete random variables


Discrete Uniform Random Variables


Bernoulli Random Variables


Binomial Random Variables


Hypergeometric Random Variables


Review Exercises



Hypothesis testing


Introduction


Two Types of Errors


The Sign Test


Binomial Exact Test


Fisher+s Exact Test


Trivial Effect Can be Significant


Review Exercises



Normal random variables


Introduction


Normal Approximation of Binomial


Continuity Correction


Central Limit Theorem


Processes that Follow the Normal Curve


Review Exercises



Waiting time random variables Geometric Random Variables


Exponential Random Variables


Poisson Random Variables


Poisson Approximation Binomial for Rare Events


Poisson Random Variable as Inverse Exponential


Review Exercises



Multivariate random variables


Joint Densities


Independence of Random Variables


Expectation, Covariance, and Correlation


Linear Combinations of Random Variables


Review Exercises



Sampling theory


Population and Parameters


Samples and Statistics


Law of Averages for the Sample Count


Law of Averages for Sample Proportion


Law of Averages for the Sample Sum


Law of Averages for the Sample Mean


The z Statistic


The t Statistic


Estimators of Parameters


Review Exercises



THE Z AND T TESTS OF HYPOTHESES


The z Test


Two-Sided z Test


Bootstrapping and the t Test


Which is the Null Hypothesis? Review Exercises



Interval estimation


Difference Between Confidence and Probability


Two-sided Confidence Intervals


One-sided Confidence Intervals


Bootstrapping and the t curves


Margin of Error


Interval Estimation of Proportion Pi


Small Sample Interval Estimates of Proportions


Review Exercises



Two sample inference


Matched Pair Samples


Independent Samples


Welch+s Formula


Independent Samples with Equal Variances


Resampling Methods


Review Exercises



Correlation and regression


Introduction


Scatter Plots


The Correlation Coefficient


Fitting a Scatter Plot by Eyes


The Regression Line


Estimation with Regression


The Regression Paradox


Testing for Correlation


Correlation is Not Causation


Review Exercises



Inference with categorical data


Introduction / Comments on the Definition of x2


Testing Goodness-of-Fit


Contingency Table Tests


One-Sided Chi-Square Test for the 2 x 2 Contingency Table


Compound Hypotheses


Review Exercises


Statistical Tables


Answers to Selected Odd-numbered Exercises


Indices