Efnisyfirlit

• PREFACE
  • THE NATURE OF THE BOOK
  • ORIENTATION
  • SPECIAL FEATURES
  • ABOUT THE EIGHTH EDITION
  • ORGANIZATION
  • SUPPLEMENTS
  • ACKNOWLEDGMENTS
• 1 INTRODUCTION TO STATISTICS
  • 1. THE SUBJECT AND SCOPE OF STATISTICS
  • 2. STATISTICS IN AID OF SCIENTIFIC INQUIRY
  • 3. TWO BASIC CONCEPTS—POPULATION AND SAMPLE
  • 4. THE PURPOSEFUL COLLECTION OF DATA
  • 5. OBJECTIVES OF STATISTICS
• 2 ORGANIZATION AND DESCRIPTION OF DATA
  • 1. MAIN TYPES OF DATA
  • 2. DESCRIBING DATA BY TABLES AND GRAPHS
  • 3. MEASURES OF CENTER
  • 4. MEASURES OF VARIATION
  • 5. CHECKING THE STABILITY OF THE OBSERVATIONS OVER TIME
  • 6. MORE ON GRAPHICS
• 3 DESCRIPTIVE STUDY OF BIVARIATE DATA
  • 1. SUMMARIZATION OF BIVARIATE CATEGORICAL DATA
  • 2. A DESIGNED EXPERIMENT FOR MAKING A COMPARISON
  • 3. SCATTER DIAGRAM OF BIVARIATE MEASUREMENT DATA
  • 4. THE CORRELATION COEFFICIENT—A MEASURE OF LINEAR RELATION
  • 5. PREDICTION OF ONE VARIABLE FROM ANOTHER (LINEAR REGRESSION)
• 4 PROBABILITY
  • 1. PROBABILITY OF AN EVENT
  • 2. METHODS OF ASSIGNING PROBABILITY
  • 3. EVENT OPERATIONS AND TWO LAWS OF PROBABILITY
  • 4. CONDITIONAL PROBABILITY AND INDEPENDENCE
  • 5. BAYES' THEOREM
  • 6. RANDOM SAMPLING FROM A FINITE POPULATION
• 5 PROBABILITY DISTRIBUTIONS
  • 1 RANDOM VARIABLES
  • 2 PROBABILITY DISTRIBUTION OF A DISCRETE RANDOM VARIABLE
  • 3 MEAN (EXPECTED VALUE) AND STANDARD DEVIATION OF A PROBABILITY DISTRIBUTION
  • 4 SUCCESSES AND FAILURES—BERNOULLI TRIALS
  • 5 THE BINOMIAL DISTRIBUTION
  • 6 THE POISSON DISTRIBUTION AND RARE EVENTS
• 6 THE NORMAL DISTRIBUTION
  • 1. PROBABILITY MODEL FOR A CONTINUOUS RANDOM VARIABLE
  • 2. THE NORMAL DISTRIBUTION—ITS GENERAL FEATURES
  • 3. THE STANDARD NORMAL DISTRIBUTION
  • 4. PROBABILITY CALCULATIONS WITH NORMAL DISTRIBUTIONS
  • 5. THE NORMAL APPROXIMATION TO THE BINOMIAL
  • *6. CHECKING THE PLAUSIBILITY OF A NORMAL MODEL
  • *7. TRANSFORMING OBSERVATIONS TO ATTAIN NEAR NORMALITY
• 7 VARIATION IN REPEATED SAMPLES—SAMPLING DISTRIBUTIONS
  • 1. THE SAMPLING DISTRIBUTION OF A STATISTIC
  • 2. DISTRIBUTION OF THE SAMPLE MEAN AND THE CENTRAL LIMIT THEOREM
• 8 DRAWING INFERENCES FROM LARGE SAMPLES
  • 1. TWO TYPES OF STATISTICAL INFERENCE: ESTIMATION AND TESTING
  • 2. POINT ESTIMATION OF A POPULATION MEAN
  • 3. CONFIDENCE INTERVAL ESTIMATION OF A POPULATION MEAN
  • 4. TESTING HYPOTHESES ABOUT A POPULATION MEAN
  • 5. INFERENCES ABOUT A POPULATION PROPORTION
• 9 SMALL SAMPLE INFERENCES FOR NORMAL POPULATIONS
  • 1. STUDENT'S t DISTRIBUTION
  • 2. INFERENCES ABOUT μ—SMALL SAMPLE SIZE
  • 3. RELATIONSHIP BETWEEN TESTS AND CONFIDENCE INTERVALS
  • 4. INFERENCES ABOUT THE STANDARD DEVIATION σ (THE CHI‐SQUARE DISTRIBUTION)
  • 5. ROBUSTNESS OF INFERENCE PROCEDURES
• 10 COMPARING TWO TREATMENTS
  • 1. TWO DESIGNS: INDEPENDENT SAMPLES AND MATCHED PAIRS SAMPLE
  • 2. INFERENCES ABOUT THE DIFFERENCE OF MEANS—INDEPENDENT LARGE SAMPLES
  • 3. INFERENCES ABOUT THE DIFFERENCE OF MEANS—INDEPENDENT SMALL SAMPLES FROM NORMAL POPULATIONS
  • 4. RANDOMIZATION AND ITS ROLE IN INFERENCE
  • 5. MATCHED PAIRS COMPARISONS
  • 6. CHOOSING BETWEEN INDEPENDENT SAMPLES AND A MATCHED PAIRS SAMPLE
  • 7. COMPARING TWO POPULATION PROPORTIONS
• 11 REGRESSION ANALYSIS I SIMPLE LINEAR REGRESSION
  • 1. REGRESSION WITH A SINGLE PREDICTOR
  • 2. A STRAIGHT LINE REGRESSION MODEL
  • 3. THE METHOD OF LEAST SQUARES
  • 4. THE SAMPLING VARIABILITY OF THE LEAST SQUARES ESTIMATORS—TOOLS FOR INFERENCE
  • 5. IMPORTANT INFERENCE PROBLEMS
  • 6. THE STRENGTH OF A LINEAR RELATION
  • 7. REMARKS ABOUT THE STRAIGHT LINE MODEL ASSUMPTIONS
• 12 REGRESSION ANALYSIS II MULTIPLE LINEAR REGRESSION AND OTHER TOPICS
  • 1. NONLINEAR RELATIONS AND LINEARIZING TRANSFORMATIONS
  • 2. MULTIPLE LINEAR REGRESSION
  • 3. RESIDUAL PLOTS TO CHECK THE ADEQUACY OF A STATISTICAL MODEL
• 13 ANALYSIS OF CATEGORICAL DATA
  • 1. FORMULATING TESTING PROBLEMS CONCERNING CATEGORICAL DATA
  • 2. PEARSON'S χ TEST FOR GOODNESS OF FIT
  • 3. CONTINGENCY TABLE WITH ONE MARGIN FIXED (TEST OF HOMOGENEITY)
  • 4. CONTINGENCY TABLE WITH NEITHER MARGIN FIXED (TEST OF INDEPENDENCE)
• 14 ANALYSIS OF VARIANCE (ANOVA)
  • 1. COMPARISON OF SEVERAL TREATMENTS—ONE‐WAY ANALYSIS OF VARIANCE
  • 2. POPULATION MODEL AND INFERENCES FOR A ONE‐WAY ANALYSIS OF VARIANCE
  • 3. SIMULTANEOUS CONFIDENCE INTERVALS
  • 4. GRAPHICAL DIAGNOSTICS AND DISPLAYS TO SUPPLEMENT ANOVA
  • 5. RANDOMIZED BLOCK EXPERIMENTS FOR COMPARING TREATMENTS
• 15 NONPARAMETRIC INFERENCE
  • 1. THE WILCOXON RANK‐SUM TEST FOR COMPARING TWO TREATMENTS
  • 2. MATCHED PAIRS COMPARISONS
  • 3. MEASURE OF CORRELATION BASED ON RANKS
  • 4. CONCLUDING REMARKS
• APPENDIX A1: SUMMATION NOTATION
  • A1.1 SUMMATION AND ITS PROPERTIES
  • A1.2 SOME BASIC USES OF Σ IN STATISTICS
• APPENDIX A2: RULES FOR COUNTING
• APPENDIX A3: EXPECTATION AND STANDARD DEVIATION—PROPERTIES
  • A3.1 EXPECTED VALUE AND STANDARD DEVIATION OF cX + b
  • A3.2 ALTERNATIVE FORMULA FOR σ
  • A3.3 PROPERTIES OF EXPECTED VALUE FOR TWO RANDOM VARIABLES
  • A3.4 PROPERTIES OF EXPECTED VALUE FOR SEVERAL RANDOM VARIABLES
• APPENDIX A4: THE EXPECTED VALUE AND STANDARD DEVIATION OF X¯
• APPENDIX B: TABLES
  • SUMMARY OF FORMULAS USEFUL FOR EXAMS
• DATA BANK
• INDEX
• END USER LICENSE AGREEMENT

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