(Ebook) Schaum s Outline of Statistics 4th Edition by Murray R Spiegel, Larry J Stephens ISBN 9780071594462 0071594469

(Ebook) Schaum s Outline of Statistics 4th Edition by Murray R Spiegel, Larry J Stephens ISBN 9780071594462 0071594469

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ISBN 10: 0071594469
ISBN 13: 9780071594462
Author: Murray R Spiegel, Larry J Stephens

(Ebook) Schaum s Outline of Statistics 4th Edition Table of 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

Chapter 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; Coefficient 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 χ[sup(2)]

Significance Tests

The Chi-Square Test for Goodness of Fit

Contingency Tables

Yates’ Correction for Continuity

Simple Formulas for Computing χ[sup(2)]

Coefficient of Contingency

Correlation of Attributes

Additive Property of χ[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 ν Degrees of Freedom

IV: Percentile Values (χ[sup(2)][sub(p)]) for the Chi-Square Distribution with ν Degrees o

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

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Tags: Murray R Spiegel, Larry J Stephens, Schaum s Outline, Statistics