Schaum's Outline of Probability and Statistics / Edition 2

Schaum's Outline of Probability and Statistics / Edition 2

by Murray R. Spiegel, John J. Schiller, John Schiller, R. Alu Srinivasan

Master probability and statistics with Schaum's­­the high-performance study guide. It will help you study efficiently, develop problem-solving skills, and achieve your personal best on exams!

Students love Schaum's Outlines because they produce results. Each year, hundreds of thousands of students improve their test scores and final grades with these

See more details below


Master probability and statistics with Schaum's­­the high-performance study guide. It will help you study efficiently, develop problem-solving skills, and achieve your personal best on exams!

Students love Schaum's Outlines because they produce results. Each year, hundreds of thousands of students improve their test scores and final grades with these indispensable study guides.

If you don't have a lot of time but want to excel in class, use this book to:

  • Brush up before tests
  • Find answers fast
  • Study quickly and more effectively
  • Get the big picture without spending hours poring over lengthy textbooks

Schaum's Outlines give you the information your teachers expect you to know in a handy and succinct format­­without overwhelming you with unnecessary detail. You get a complete overview of the subject. Plus, you get plenty of practice exercises to test your skill. Compatible with any classroom text, Schaum's let you study at your own pace and remind you of all the important facts you need to remember­­fast! And Schaum's are so complete, they're perfect for preparing for graduate or professional exams.

Inside you will find:

  • 760 fully-worked problems with step-by-step solutions
  • Hundreds of additional practice problems with answers
  • Coverage of all course fundamentals
  • Easy-to-understand methodology

If you want top grades and a thorough understanding of probability and statistics, this powerful study tool is the best tutor you can have! Chapters include:

  • Basic Probability
  • Random Variables & Probability Distributions
  • Mathematical Expectation
  • Special Probability Distributions
  • Sampling Theory
  • Estimation Theory
  • Tests of Hypotheses & Significance
  • Curve Fitting, Regression, & Correlation
  • Analysis of Variance
  • Nonparametric Tests

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Product Details

McGraw-Hill Companies, The
Publication date:
Schaum Outline Series
Edition description:
Second Edition
Product dimensions:
8.18(w) x 10.84(h) x 0.62(d)

Table of Contents

Part IProbability1
Chapter 1Basic Probability3
Random Experiments
Sample Spaces
The Concept of Probability
The Axioms of Probability
Some Important Theorems on Probability
Assignment of Probabilities
Conditional Probability
Theorems on Conditional Probability
Independent Events
Bayes' Theorem or Rule
Combinatorial Analysis
Fundamental Principle of Counting
Tree Diagrams
Binomial Coefficients
Stirling's Approximation to n!
Chapter 2Random Variables and Probability Distributions36
Random Variables
Discrete Probability Distributions
Distribution Functions for Random Variables
Distribution Functions for Discete Random Variables
Continuous Random Variables
Graphical Intepretations
Joint Distributions
Independent Random Variables
Change of Variables
Probability Distributions of Functions of Random Variables
Conditional Distributions
Applications to Geometric Probability
Chapter 3Mathematical Expectation78
Definition of Mathematical Expectation
Functions of Randem Variables
Some Theorems on Expectation
The Variance and Standard Deviation
Some Theorems on Variance
Standardized Random Variables
Moment Generating Functions
Some Theorems on Moment Generating Functions
Characteristics Functions
Variance for Joint Distributions
Correlation Coefficient
Conditional Expectation, Variance, and Moments
Chebyshev's Inequality
Law of Large Numbers
Other Measures of Central Tendency
Other Measures of Dispersion
Skewness and Kurtosis
Chapter 4Special Probability Distributions113
The Binomial Distribution
Some Properties of the Binomial Distribution
The Law of Large Numbers for Bernoulli Trials
The Normal Distribution
Some Properties of the Normal Distribution
Relation Between Binomial and Normal Distributions
The Poisson Distribution
Some Properties of the Poisson Distribution
Relation Between the Binomial and Poisson Distribution
Relation Between the Poisson and Normal Distributions
The Central Limit Theorem
The Multinomial Distribution
The Hypergeometric Distribution
The Uniform Distribution
The Cauchy Distribution
The Gamma Distribution
The Beta Distribution
The Chi-Square Distribution
Student's t Distribution
The F Distribution
Relationships Among Chi-Square, t, and F Distributions
The Bivariate Normal Distribution
Miscellaneous Distributions
Part IIStatistics159
Chapter 5Sampling Theory161
Population and Sample
Statistical Interference
Sampling With and Without Replacement
Random Samples
Random Numbers
Population Parameters
Sample Statistics
Sampling Distributions
The Sample Mean
Sampling Distribution of Means
Sampling Distribution of Proportions
Sampling Distribution of Differences and Sums
The Sample Variance
Sampling Distribution of Variances
Case where Population Variance Is Unknown
Sampling Distribution of Ratios of Variances
Other Statistics
Frequency Distributions
Relative Frequency Distributions
Computation of Mean, Variance, and Moments for Grouped Data
Chapter 6Estimation Theory205
Unbiased Estimates and Efficient Estimates
Point Estimates and Interval Estimates
Confidence Interval Estimates of Population Parameters
Confidence Intervals for Means
Confidence Intervals for Proportions
Confidence Intervals for Differences and Sums
Confidence Intervals for the Variance of a Normal Distribution
Confidence Intervals for Variance Ratios
Maximum Likelihood Estimates
Chapter 7Tests of Hypotheses and Significance224
Statistical Decisions
Statistical Hypotheses
Null Hypotheses
Tests of Hypotheses and Significance
Type I and Type II Errors
Level of Significance
Tests Involving the Normal Distribution
One-Tailed and Two-Tailed Tests
P Value
Special Tests of Significance for Large Samples
Special Tests of Significance for Small Samples
Relationship Between Estimation Theory and Hypothesis Testing
Operating Characteristic Curves
Power of a Test
Quality Control Charts
Fitting Theoretical Distributions to Sample Frequency Distributions
The Chi-Square Test for Goodness of Fit
Contingency Tables
Yates' Correction for Continuity
Coefficient of Contingency
Chapter 8Curve Fitting, Regression, and Correlation278
Curve Fitting
The Method of Least Squares
The Least-Squares Line
The Least-Squares Line in Terms of Sample Variances and Covariance
The Least-Squares Parabola
Multiple Regression
Standard Error of Estimate
The Linear Correlation Coefficient
Generalized Correlation Coefficient
Rank Correlation
Probability Interpretation of Regression
Probability Interpretation of Correlation
Sampling Theory of Regression
Sampling Theory of Correlation
Correlation and Dependence
Chapter 9Analysis of Variance328
The Purpose of Analysis of Variance
One-Way Classification or One-Factor Experiments
Total Variation
Variation Within Treatments
Variation Between Treatments
Shortcut Methods for Obtaining Variations
Linear Mathematical Model for Analysis of Variance
Expected Values of the Variations
Distributions of the Variations
The F Test for the Null Hypothesis of Equal Means
Analysis of Variance Tables
Modifications for Unequal Numbers of Observations
Two-Way Classification or Two-Factor Experiments
Notation for Two-Factor Experiments
Variations for Two-Factor Experiments
Analysis of Variance for Two-Factor Experiments
Two-Factor Experiments with Replication
Experimental Design
Chapter 10Nonparametric Tests363
The Sign Test
The Mann-Whitney U Test
The Kruskal-Wallis H Test
The H Test Corrected for Ties
The Runs Test for Randomness
Further Applications of the Runs Test
Spearman's Rank Correlation
Appendix AMathematical Topics389
Appendix BOrdinates (y) of the Standard Normal Curve at z392
Appendix CAreas under the Standard Normal Curve from 0 to z393
Appendix DPercentile Values t[subscript p] for Student's t Distribution with v Degrees of Freedom394
Appendix EPercentile Values [characters not reproducible] for the Chi-Square Distribution with v Degrees of Freedom395
Appendix F95th and 99th Percentile Values for the F Distribution with v[subscript 1], v[subscript 2] Degrees of Freedom396
Appendix GValues of e[superscript - lambda]398
Appendix HRandom Numbers399
Subject Index401
Index for Solved Problems407

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