Statistics- Concept and Applications

Title
STATISTICSConcepts and Applications, Second Edition
Dedication
Contents
List of Figures
List of Tables
Preface
Preface to the First Edition
Acronyms
Notation
1 BASIC CONCEPTS OF STATISTICAL STUDIES
	1.1 Population
	1.2 Variable and Parameter
	1.3 Sample
	1.4 Basic Steps in a Statistical Study
	1.5 Summary
	1.6 Exercises
2 ORGANIZING A RAW DATASET
	2.1 Organizing a Categorical Dataset
	2.2 Organizing a Quantitative Dataset
	2.3 About Outliers
	2.4 Summary
	2.5 Use of Technology
	2.6 Exercises
3 PICTORIAL REPRESENTATION OF A DATASET
	3.1 Bar Diagram or Bar Chart
	3.2 Histogram
	3.3 Pie Diagram
	3.4 Stem-Leaf Display
	3.5 Time Plot
	3.6 Summary
	3.7 Use of Technology
	3.8 Exercises
4 SUMMARIZING A RAW DATASET
	4.1 Central Tendency
	4.2 Variability or Dispersion
	4.3 Box-Whisker Plot (or Box Plot
	4.4 Summary
	4.5 Use of Technology
	4.6 Exercises
5 SUMMARIZING AN ORGANIZED DATASET
	5.1 Central Tendency
	5.2 Variability
	5.3 Summary
	5.4 Use of Technology
	5.5 Exercises
6 CONCEPTS OF PROBABILITY
	6.1 Experiment and Sample Space
	6.2 Events and Operations with Events
	6.3 Probability of an Event
	6.4 Basic Probability Rules
	6.5 Applications of Probability Rules
	6.6 Conditional Probability
	6.7 Summary
	6.8 Exercises
7 RANDOM VARIABLES
	7.1 How Random Variables Arise
	7.2 Probability Distribution of a Random Variable
	7.3 Mean or Expected Value of a Random Variable
	7.4 Probability Histogram of a Random Variable
	7.5 Variance and Standard Deviation of a Random Variable
	7.6 Summary
	7.7 Exercises
8 BINOMIAL EXPERIMENTS
	8.1 Structure of a Binomial Experiment
	8.2 Binomial Probability Distribution
	8.3 Use of Binomial Probability Table
	8.4 Summary
	8.5 Use of Technology
	8.6 Exercises
9 NORMAL CURVE AND NORMAL DISTRIBUTION
	9.1 Motivation Behind a Normal Curve
	9.2 Properties of a Normal Curve
	9.3 Normal Probability Distribution
	9.4 Areas Under a Normal Curve
	9.5 Summary
	9.6 Use of Technology
	9.7 Exercises
10 APPLICATIONS OF THE NORMAL DISTRIBUTION
	10.1 Approximating a Binomial Probability
	10.2 The Normal Theorem and the Central Limit Theorem
	10.3 Summary
	10.4 Use of Technology
	10.5 Exercises
11 ESTIMATION OF POPULATION PARAMETERS
	11.1 Parameter and Statistic
	11.2 Point and Interval Estimation
	11.3 Interval Estimation of Three Common Parameters
	11.3.1 Interval Estimation of a Population Mean
	11.3.2 Interval Estimation of a Population Standard Deviation
	11.3.3 Interval Estimation of a Population Proportion
	11.4 Summary
	11.5 Use of Technology
	11.6 Exercises
12 HYPOTHESIS TESTING FOR A SINGLE POPULATION
	12.1 Concept of a Hypothesis
	12.2 Tests Involving a Population Mean
	12.3 Tests Involving a Population Proportion
	12.4 Tests Involving a Population Standard Deviation
	12.5 The Concept of P-value
	12.6 Verifying Normality For A Given Dataset
	12.7 Summary
	12.8 Use of Technology
	12.9 Exercises
13 HYPOTHESIS TESTING TO COMPARE TWO POPULATIONS
	13.1 Comparison of Two Populations
	13.2 Tests for Two Population Means (Independent Samples
	13.2.1 Population Standard Deviations are Unknown but Equal
	13.2.2 Population Standard Deviations are Unknown and Unequal
	13.3 Tests for Two Population Means (Dependent Samples
	13.4 Tests for Two Population Proportions (Independent Samples
	13.5 Tests for Two Population Variances (Independent Samples
	13.6 The P-Value Approach
	13.7 Summary
	13.8 Use of Technology
	13.9 Exercises
14 BIVARIATE QUANTITATIVE DATA: CORRELATION AND
 REGRESSION
	14.1 Concepts of a Bivariate Dataset
	14.2 Correlation Coefficient
	14.3 Inferences on a Population Correlation Coefficient
	14.4 The Regression Line
	14.5 Inferences on the Population Regression Line
	14.6 Summary
	14.7 Use of Technology
	14.8 Exercises
15 BIVARIATE CATEGORICAL DATA: CONTINGENCY TABLES
	15.1 Concepts of a Contingency Table
	15.2 Testing Independence of Two Categorical Variables
	15.3 Summary
	15.4 Use of Technology
	15.5 Exercises
16 MULTINOMIAL EXPERIMENTS: GOODNESS OF FIT TEST
	16.1 Structure of a Multinomial Experiment
	16.2 Multinomial Probability Distribution (MPD
	16.3 Goodness of Fit Test of MPD for a Given Dataset
	16.4 Summary
	16.5 Use of Technology
	16.6 Exercises
17 HYPOTHESIS TESTING TO COMPARE MULTIPLE POPULATIONS
	17.1 Comparing Multiple Populations
	17.2 Comparing Multiple Population Variances
	17.3 Comparing Multiple Population Means
	17.3.1 Data from Unrestricted (independent) Samples
 (One-way ANOVA
	17.3.2 Data from Block Restricted Samples
 (Two-way ANOVA
	17.4 Summary
	17.5 Use of Technology
	17.6 Exercises
18 QUALITY MANAGEMENT USING STATISTICS
	18.1 Concept of Statistical Quality Control
	18.2 Principles of Statistical Process Control
	18.3 Control Charts and Hypothesis Testing
	18.4 Control Charts for Quantitative Data
	18.4.1 The X-chart
	18.4.2 The R-chart
	18.4.3 The s-chart
	18.5 Control Chart for Categorical Data: p-chart
	18.6 Summary
	18.7 Use of Technology
	18.8 Exercises
Appendix A Statistical Tables
Appendix B Question Bank
Appendix C Multiple-Choice Questions (with Answers
Appendix D Answers to Chapter Exercises
Index
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