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Spiegel, Murray and Stephens, Larry. Schaum's Outline of Statistics, 5th Edition. McGraw-Hill, 2014.

Schaum's Outline of Statistics, 5th Edition

Authors: Murray Spiegel and Larry Stephens

Published:  March 2014

eISBN: 9780071822770 0071822771 | ISBN: 9780071822527
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  • Cover
  • Video Content
  • Title Page
  • Copyright Page
  • Contents
  • Chapter 1 Variables and Graphs
  • Statistics
  • Population and Sample; Inductive and Descriptive Statistics
  • Variables: Discrete and Continuous
  • Rounding of Data
  • Scientific Notation
  • Significant Figures
  • Computations
  • Functions
  • Rectangular Coordinates
  • Graphs
  • Equations
  • Inequalities
  • Logarithms
  • Properties of Logarithms
  • Logarithmic Equations
  • Chaptet 2 Frequency Distributions
  • Raw Data
  • Arrays
  • Frequency Distributions
  • Class Intervals and Class Limits
  • Class Boundaries
  • The Size, or Width, of a Class Interval
  • The Class Mark
  • General Rules for Forming Frequency Distributions
  • Histograms and Frequency Polygons
  • Relative-Frequency Distributions
  • Cumulative-Frequency Distributions and Ogives
  • Relative Cumulative-Frequency Distributions and Percentage Ogives
  • Frequency Curves and Smoothed Ogives
  • Types of Frequency Curves
  • Chapter 3 The Mean, Median, Mode, and Other Measures of Central Tendency
  • Index, or Subscript, Notation
  • Summation Notation
  • Averages, or Measures of Central Tendency
  • The Arithmetic Mean
  • The Weighted Arithmetic Mean
  • Properties of the Arithmetic Mean
  • The Arithmetic Mean Computed from Grouped Data
  • The Median
  • The Mode
  • The Empirical Relation Between the Mean, Median, and Mode
  • The Geometric Mean G
  • The Harmonic Mean H
  • The Relation Between the Arithmetic, Geometric, and Harmonic Means
  • The Root Mean Square
  • Quartiles, Deciles, and Percentiles
  • Software and Measures of Central Tendency
  • Chapter 4 The Standard Deviation and Other Measures of Dispersion
  • Dispersion, or Variation
  • The Range
  • The Mean Deviation
  • The Semi-Interquartile Range
  • The 10–90 Percentile Range
  • The Standard Deviation
  • The Variance
  • Short Methods for Computing the Standard Deviation
  • Properties of the Standard Deviation
  • Charlier’s Check
  • Sheppard’s Correction for Variance
  • Empirical Relations Between Measures of Dispersion
  • Absolute and Relative Dispersion; Coe.cient of Variation
  • Standardized Variable; Standard Scores
  • Software and Measures of Dispersion
  • Chapter 5 Moments, Skewness, and Kurtosis
  • Moments
  • Moments for Grouped Data
  • Relations Between Moments
  • Computation of Moments for Grouped Data
  • Charlier’s Check and Sheppard’s Corrections
  • Moments in Dimensionless Form
  • Skewness
  • Kurtosis
  • Population Moments, Skewness, and Kurtosis
  • Software Computation of Skewness and Kurtosis
  • Chapter 6 Elementary Probability Theory
  • Definitions of Probability
  • Conditional Probability; Independent and Dependent Events
  • Mutually Exclusive Events
  • Probability Distributions
  • Mathematical Expectation
  • Relation Between Population, Sample Mean, and Variance
  • Combinatorial Analysis
  • Combinations
  • Stirling’s Approximation to n!
  • Relation of Probability to Point Set Theory
  • Euler or Venn Diagrams and Probability
  • Chapter 7 The Binomial, Normal, and Poisson Distributions
  • The Binomial Distribution
  • The Normal Distribution
  • Relation Between the Binomial and Normal Distributions
  • The Poisson Distribution
  • Relation Between the Binomial and Poisson Distributions
  • The Multinomial Distribution
  • Fitting Theoretical Distributions to Sample Frequency Distributions
  • Chapter 8 Elementary Sampling Theory
  • Sampling Theory
  • Random Samples and Random Numbers
  • Sampling With and Without Replacement
  • Sampling Distributions
  • Sampling Distribution of Means
  • Sampling Distribution of Proportions
  • Sampling Distributions of Differences and Sums
  • Standard Errors
  • Software Demonstration of Elementary Sampling Theory
  • Chapter 9 Statistical Estimation Theory
  • Estimation of Parameters
  • Unbiased Estimates
  • Efficient Estimates
  • Point Estimates and Interval Estimates; Their Reliability
  • Confidence-Interval Estimates of Population Parameters
  • Probable Error
  • Chapter 10 Statistical Decision Theory
  • Statistical Decisions
  • Statistical Hypotheses
  • Tests of Hypotheses and Significance, or Decision Rules
  • Type I and Type II Errors
  • Level of Significance
  • Tests Involving Normal Distributions
  • Two-Tailed and One-Tailed Tests
  • Special Tests
  • Operating-Characteristic Curves; the Power of a Test
  • p-Values for Hypotheses Tests
  • Control Charts
  • Tests Involving Sample Differences
  • Tests Involving Binomial Distributions
  • Chapter 11 Small Sampling Theory
  • Small Samples
  • Student’s t Distribution
  • Confidence Intervals
  • Tests of Hypotheses and Significance
  • The Chi-Square Distribution
  • Confidence Intervals for σ
  • Degrees of Freedom
  • The F Distribution
  • Chapter 12 The Chi-Square Test
  • Observed and Theoretical Frequencies
  • Definition of X[sup(2)]
  • Significance Tests
  • The Chi-Square Test for Goodness of Fit
  • Contingency Tables
  • Yates’ Correction for Continuity
  • Simple Formulas for Computing X[sup(2)]
  • Coefficient of Contingency
  • Correlation of Attributes
  • Additive Property of X[sup(2)]
  • Chapter 13 Curve Fitting and the Method of Least Squares
  • Relationship Between Variables
  • Curve Fitting
  • Equations of Approximating Curves
  • Freehand Method of Curve Fitting
  • The Straight Line
  • The Method of Least Squares
  • The Least-Squares Line
  • Nonlinear Relationships
  • The Least-Squares Parabola
  • Regression
  • Applications to Time Series
  • Problems Involving More Than Two Variables
  • Chapter 14 Correlation Theory
  • Correlation and Regression
  • Linear Correlation
  • Measures of Correlation
  • The Least-Squares Regression Lines
  • Standard Error of Estimate
  • Explained and Unexplained Variation
  • Coefficient of Correlation
  • Remarks Concerning the Correlation Coefficient
  • Product-Moment Formula for the Linear Correlation Coefficient
  • Short Computational Formulas
  • Regression Lines and the Linear Correlation Coefficient
  • Correlation of Time Series
  • Correlation of Attributes
  • Sampling Theory of Correlation
  • Sampling Theory of Regression
  • Chapter 15 Multiple and Partial Correlation
  • Multiple Correlation
  • Subscript Notation
  • Regression Equations and Regression Planes
  • Normal Equations for the Least-Squares Regression Plane
  • Regression Planes and Correlation Coefficients
  • Standard Error of Estimate
  • Coefficient of Multiple Correlation
  • Change of Dependent Variable
  • Generalizations to More Than Three Variables
  • Partial Correlation
  • Relationships Between Multiple and Partial Correlation Coefficients
  • Nonlinear Multiple Regression
  • Chapter 16 Analysis of Variance
  • The Purpose of Analysis of Variance
  • One-Way Classification, or One-Factor Experiments
  • Total Variation, Variation Within Treatments, and Variation Between Treatments
  • Shortcut Methods for Obtaining Variations
  • 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 17 Nonparametric tests
  • Introduction
  • 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
  • Chapter 18 Statistical Process Control and Process Capability
  • General Discussion of Control Charts
  • Variables and Attributes Control Charts
  • X-bar and R Charts
  • Tests for Special Causes
  • Process Capability
  • P- and NP-Charts
  • Other Control Charts
  • Answers to Supplementary Problems
  • Appendixes
  • I: Ordinates (Y) of the Standard Normal Curve at z
  • II: Areas Under the Standard Normal Curve from 0 to z
  • III: Percentile Values (t[sub(p)] for Student’s t Distribution with v Degrees of Freedom
  • IV: Percentile Values ( X[sup(2)][(sub(p)] for the Chi-Square Distribution with v Degrees of Freedom
  • V: 95th Percentile Values for the F Distribution
  • VI: 99th Percentile Values for the F Distribution
  • VII: Four-Place Common Logarithms
  • VIII: Values of e[sup(-λ)]
  • IX: Random Numbers
  • Index
  • For Download