Statistics : concepts and applications
Pal, Nabendu
Statistics : concepts and applications - Ed.2 - New Delhi Prentice Hall of India Pvt. Ltd. 2009 - xxvi,445p.,CD Rom
CONTENTS List of Figuresxi List of Tablesxv Preface xix Preface to the First Editionxxi Acronyms xxiii Notation xxv 1 BASIC CONCEPTS OF STATISTICAL STUDIES 1-8 1.1 Population.. 1 1.2 Variable and Parameter. 2 1.3 Sample 4 1.4Basic Steps in a Statistical Study . 5 1.5Summary 5 1.6Exercises6 2 ORGANIZING A RAW DATASET9-27 2.1Organizing a Categorical Dataset . . 9 2.2 Organizing a Quantitative Dataset 11 2.3About Outliers14 2.4Summary 15 2.5Use of Technology 15 2.6Exercises. 24 3 PICTORIAL REPRESENTATION OF A DATASET28-54 3.1Bar Diagram or Bar Chart28 3.2 Histogram.30 3.3 Pie Diagram 32 3.4 Stem-Leaf Display33 3.5 Time Plot 34 3.6 Summary35 3.7 Use of Technology35 3.8Exercises. 53 4 SUMMARIZING A RAW DATASET 55-67 4.1 Central Tendency 55 4.2 Variability or Dispersion 57 4.3 Box-Whisker Plot (or Box Plot) 59 4.4 Summary 60 4.5 Use of Technology 61 4.6 Exercises 66 5 SUMMARIZING AN ORGANIZED DATASET 68-79 5.1 Central Tendency 69 5.2 Variability 70 5.3 Summary 72 5.4 Use of Technology .73 5.5 Exercises77 6 CONCEPTS OF PROBABILITY80-92 6.1 Experiment and Sample Space .81 6.2 Events and Operations with Events 81 6.3 Probability of an Event. 82 6.4 Basic Probability Rules 84 6.5 Applications of Probability Rules 85 6.6 Conditional Probability 86 6.7 Summary 90 6.8 Exercises 91 7 RANDOM VARIABLES .93-102 7.1 How Random Variables Arise. .. 93 7.2 Probability Distribution of a Random Variable . 95 7.3 Mean or Expected Value of a Random Variable. 96 7.4 Probability Histogram of a Random Variable. 98 7.5 Variance and Standard Deviation of a Random Variable . 98 7.6 Summary 100 7.7 Exercises 100 8 BINOMIAL EXPERIMENTS103-114 8.1 Structure of a Binomial Experiment 104 8.2 Binomial Probability Distribution 105 8.3 Use of Binomial Probability Table 106 8.4 Summary 108 8.5 Use of Technology 109 8.6 Exercises 112 9 NORMAL CURVE AND NORMAL DISTRIBUTION 115-130 9.1 Motivation Behind a Normal Curve 115 9.2 Properties of a Normal Curve. 116 9.3 Normal Probability Distribution 118 9.4 Areas Under a Normal Curve. 120 9.5 Summary 124 9.6 Use of Technology 124 9.7 Exercises. 128 10 APPLICATIONS OF THE NORMAL DISTRIBUTION 131-143 10.1Approximating a Binomial Probability. 131 10.2The Normal Theorem and the Central Limit Theorem . 135 10.3Summary 138 10.4Use of Technology . 139 10.5 Exercises 142 11ESTIMATION OF POPULATION PARAMETERS 144-175 11.1Parameter and Statistic 144 11.2Point and Interval Estimation 147 11.3Interval Estimation of Three Common Parameters 149 11.3.1 Interval Estimation of a Population Mean 149 11.3.2 Interval Estimation of a Population Standard Deviation 153 11.3.3 Interval Estimation of a Population Proportion. 158 11.4Summary160 11.5Use of Technology 160 11.6 Exercises 173 12HYPOTHESIS TESTING FOR A SINGLE POPULATION.176-208 12.1 Concept of a Hypothesis.176 12.2 Tests Involving a Population Mean .180 12.3 Tests Involving a Population Proportion 184 12.4 Tests Involving a Population Standard Deviation 186 12.5 The Concept of P-value 189 12.6 Verifying Normality For A Given Dataset193 12.7 Summary 195 12.8 Use of Technology 196 12.9 Exercises 206 13HYPOTHESIS TESTING TO COMPARE TWO POPULATIONS 209-240 13.1Comparison of Two Populations 209 13.2Tests for Two Population Means (Independent Samples) 210 13.2.1Population Standard Deviations are Unknown but Equal 211 13.2.2 Population Standard Deviations are Unknown and Unequal 213 13.3Tests for Two Population Means (Dependent Samples) 214 13.4Tests for Two Population Proportions (Independent Samples) 217 13.5Tests for Two Population Variances (Independent Samples) 219 13.6The P-Value Approach 224 13.7Summary 226 13.8Use of Technology 228 13.9 Exercises 237 14BIVARIATE QUANTITATIVE DATA: CORRELATION AND REGRESSION 241-271 14.1Concepts of a Bivariate Dataset 241 14.2Correlation Coefficient. 243 14.3 Inferences on a Population Correlation Coefficient. 250 14.4 The Regression Line.253 14.5 Inferences on the Population Regression Line..256 14.6 Summary . 260 14.7 Use of Technology . 261 14.8 Exercises. 269 15BIVARIATE CATEGORICAL DATA: CONTINGENCY TABLES 272-288 15.1 Concepts of a Contingency Table 272 15.2Testing Independence of Two Categorical Variables. 274 15.3Summary 281 15.4Use of Technology 282 15.5Exercises .286 16MULTINOMIAL EXPERIMENTS: GOODNESS OF FIT TEST 289-306 16.1 Structure of a Multinomial Experiment 289 16.2 Multinomial Probability Distribution (MPD) 291 16.3 Goodness of Fit Test of MPD for a Given Dataset 293 16.4 Summary 298 16.5 Use of Technology 299 16.6 Exercises. 303 17 HYPOTHESIS TESTING TO COMPARE MULTIPLE POPULATIONS . 307-330 17.1Comparing Multiple Populations 307 17.2Comparing Multiple Population Variances. 311 17.3 Comparing Multiple Population Means 313 17.3.1 Data from Unrestricted (independent) Samples (One-way ANOVA) . 314 17.3.2 Data from Block Restricted Samples (Two-way ANOVA) 316 17.4 Summary 321 17.5 Use of Technology 321 17.6 Exercises.327 18 QUALITY MANAGEMENT USING STATISTICS 331-356 18.1Concept of Statistical Quality Control.331 18.2 Principles of Statistical Process Control 332 18.3 Control Charts and Hypothesis Testing 334 18.4 Control Charts for Quantitative Data. 334 18.4.1The X-chart.335 18.4.2 The fl-chart 337 18.4.3 The s-chart 340 18.5 Control Chart for Categorical Data: p-chart 343 18.6 Summary 346 18.7 Use of Technolog. 346 18.8Exercises 352 Appendix A Statistical Tables357-376 Appendix B Question Bank 377-415 Appendix C Multiple-Choice Questions (with Answers) 416-424 Appendix D Answers to Chapter Exercises425-442 Index443-445
8120334450
519 / PAL
Statistics : concepts and applications - Ed.2 - New Delhi Prentice Hall of India Pvt. Ltd. 2009 - xxvi,445p.,CD Rom
CONTENTS List of Figuresxi List of Tablesxv Preface xix Preface to the First Editionxxi Acronyms xxiii Notation xxv 1 BASIC CONCEPTS OF STATISTICAL STUDIES 1-8 1.1 Population.. 1 1.2 Variable and Parameter. 2 1.3 Sample 4 1.4Basic Steps in a Statistical Study . 5 1.5Summary 5 1.6Exercises6 2 ORGANIZING A RAW DATASET9-27 2.1Organizing a Categorical Dataset . . 9 2.2 Organizing a Quantitative Dataset 11 2.3About Outliers14 2.4Summary 15 2.5Use of Technology 15 2.6Exercises. 24 3 PICTORIAL REPRESENTATION OF A DATASET28-54 3.1Bar Diagram or Bar Chart28 3.2 Histogram.30 3.3 Pie Diagram 32 3.4 Stem-Leaf Display33 3.5 Time Plot 34 3.6 Summary35 3.7 Use of Technology35 3.8Exercises. 53 4 SUMMARIZING A RAW DATASET 55-67 4.1 Central Tendency 55 4.2 Variability or Dispersion 57 4.3 Box-Whisker Plot (or Box Plot) 59 4.4 Summary 60 4.5 Use of Technology 61 4.6 Exercises 66 5 SUMMARIZING AN ORGANIZED DATASET 68-79 5.1 Central Tendency 69 5.2 Variability 70 5.3 Summary 72 5.4 Use of Technology .73 5.5 Exercises77 6 CONCEPTS OF PROBABILITY80-92 6.1 Experiment and Sample Space .81 6.2 Events and Operations with Events 81 6.3 Probability of an Event. 82 6.4 Basic Probability Rules 84 6.5 Applications of Probability Rules 85 6.6 Conditional Probability 86 6.7 Summary 90 6.8 Exercises 91 7 RANDOM VARIABLES .93-102 7.1 How Random Variables Arise. .. 93 7.2 Probability Distribution of a Random Variable . 95 7.3 Mean or Expected Value of a Random Variable. 96 7.4 Probability Histogram of a Random Variable. 98 7.5 Variance and Standard Deviation of a Random Variable . 98 7.6 Summary 100 7.7 Exercises 100 8 BINOMIAL EXPERIMENTS103-114 8.1 Structure of a Binomial Experiment 104 8.2 Binomial Probability Distribution 105 8.3 Use of Binomial Probability Table 106 8.4 Summary 108 8.5 Use of Technology 109 8.6 Exercises 112 9 NORMAL CURVE AND NORMAL DISTRIBUTION 115-130 9.1 Motivation Behind a Normal Curve 115 9.2 Properties of a Normal Curve. 116 9.3 Normal Probability Distribution 118 9.4 Areas Under a Normal Curve. 120 9.5 Summary 124 9.6 Use of Technology 124 9.7 Exercises. 128 10 APPLICATIONS OF THE NORMAL DISTRIBUTION 131-143 10.1Approximating a Binomial Probability. 131 10.2The Normal Theorem and the Central Limit Theorem . 135 10.3Summary 138 10.4Use of Technology . 139 10.5 Exercises 142 11ESTIMATION OF POPULATION PARAMETERS 144-175 11.1Parameter and Statistic 144 11.2Point and Interval Estimation 147 11.3Interval Estimation of Three Common Parameters 149 11.3.1 Interval Estimation of a Population Mean 149 11.3.2 Interval Estimation of a Population Standard Deviation 153 11.3.3 Interval Estimation of a Population Proportion. 158 11.4Summary160 11.5Use of Technology 160 11.6 Exercises 173 12HYPOTHESIS TESTING FOR A SINGLE POPULATION.176-208 12.1 Concept of a Hypothesis.176 12.2 Tests Involving a Population Mean .180 12.3 Tests Involving a Population Proportion 184 12.4 Tests Involving a Population Standard Deviation 186 12.5 The Concept of P-value 189 12.6 Verifying Normality For A Given Dataset193 12.7 Summary 195 12.8 Use of Technology 196 12.9 Exercises 206 13HYPOTHESIS TESTING TO COMPARE TWO POPULATIONS 209-240 13.1Comparison of Two Populations 209 13.2Tests for Two Population Means (Independent Samples) 210 13.2.1Population Standard Deviations are Unknown but Equal 211 13.2.2 Population Standard Deviations are Unknown and Unequal 213 13.3Tests for Two Population Means (Dependent Samples) 214 13.4Tests for Two Population Proportions (Independent Samples) 217 13.5Tests for Two Population Variances (Independent Samples) 219 13.6The P-Value Approach 224 13.7Summary 226 13.8Use of Technology 228 13.9 Exercises 237 14BIVARIATE QUANTITATIVE DATA: CORRELATION AND REGRESSION 241-271 14.1Concepts of a Bivariate Dataset 241 14.2Correlation Coefficient. 243 14.3 Inferences on a Population Correlation Coefficient. 250 14.4 The Regression Line.253 14.5 Inferences on the Population Regression Line..256 14.6 Summary . 260 14.7 Use of Technology . 261 14.8 Exercises. 269 15BIVARIATE CATEGORICAL DATA: CONTINGENCY TABLES 272-288 15.1 Concepts of a Contingency Table 272 15.2Testing Independence of Two Categorical Variables. 274 15.3Summary 281 15.4Use of Technology 282 15.5Exercises .286 16MULTINOMIAL EXPERIMENTS: GOODNESS OF FIT TEST 289-306 16.1 Structure of a Multinomial Experiment 289 16.2 Multinomial Probability Distribution (MPD) 291 16.3 Goodness of Fit Test of MPD for a Given Dataset 293 16.4 Summary 298 16.5 Use of Technology 299 16.6 Exercises. 303 17 HYPOTHESIS TESTING TO COMPARE MULTIPLE POPULATIONS . 307-330 17.1Comparing Multiple Populations 307 17.2Comparing Multiple Population Variances. 311 17.3 Comparing Multiple Population Means 313 17.3.1 Data from Unrestricted (independent) Samples (One-way ANOVA) . 314 17.3.2 Data from Block Restricted Samples (Two-way ANOVA) 316 17.4 Summary 321 17.5 Use of Technology 321 17.6 Exercises.327 18 QUALITY MANAGEMENT USING STATISTICS 331-356 18.1Concept of Statistical Quality Control.331 18.2 Principles of Statistical Process Control 332 18.3 Control Charts and Hypothesis Testing 334 18.4 Control Charts for Quantitative Data. 334 18.4.1The X-chart.335 18.4.2 The fl-chart 337 18.4.3 The s-chart 340 18.5 Control Chart for Categorical Data: p-chart 343 18.6 Summary 346 18.7 Use of Technolog. 346 18.8Exercises 352 Appendix A Statistical Tables357-376 Appendix B Question Bank 377-415 Appendix C Multiple-Choice Questions (with Answers) 416-424 Appendix D Answers to Chapter Exercises425-442 Index443-445
8120334450
519 / PAL