Statistics for the Sciences

ISBN-10: 0534387748

ISBN-13: 9780534387747

Edition: 2005

List price: $199.95
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Description:

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.
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Book details

List price: $199.95
Copyright year: 2005
Publisher: Brooks/Cole
Publication date: 1/8/2004
Binding: Hardcover
Pages: 552
Size: 8.00" wide x 9.50" long x 1.00" tall
Weight: 2.662
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
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