Statistics for Business

Statistics for Business is meant as a textbook for students in business, computer science, bioengineering, environmental technology, and mathematics. In recent years, business statistics is used widely for decision making in business endeavours. It emphasizes statistical applications, statistical model building, and determining the manual solution methods. Special Features: This text is prepared based on Read more... Abstract: Statistics for Business is meant as a textbook for students in business, computer science, bioengineering, environmental technology, and mathematics. In recent years, business statistics is used widely for decision making in business endeavours. It emphasizes statistical applications, statistical model building, and determining the manual solution methods. Special Features: This text is prepared based on "self-taught" method. For most of the methods, the required algorithm is clearly explained using flow-charting methodology. More than 200 solved problems provided. More than 175 end-of-chapter exercises with answers are provided. This allows teachers ample flexibility in adopting the textbook to their individual class plans. This textbook is meant to for beginners and advanced learners as a text in Statistics for Business or Applied Statistics for undergraduate and graduate students Cover Half Title Title Page Copyright Page Dedication Table of Contents Foreword Preface Acknowledgements Author 1: Introduction to Statistics and Its Business Applications 1.1 Introduction 1.2 Is Statistics a Science? 1.3 Application of Statistics in Business 1.3.1 The Phases of the Statistical Decision-Making Process 1.3.1.1 Study Design Phase 1.3.1.2 Data Collection 1.3.1.3 Data Analysis 1.3.1.4 Action on Results 1.4 Responsibility of the Decision Maker 1.5 Functions and Limitations of Statistics 1.5.1 Functions of Statistics 1.5.2 Limitations of Statistics 1.6 Distrust of Statistics 1.7 Nature of Statistical Law 1.7.1 Law of Statistical Regularity 1.7.2 Law of Inertia of Large Numbers Exercise 1 2: Data Structures, Data Sources, and Data Collection 2.1 Introduction 2.2 Data Structures 2.2.1 Univariate Data 2.2.2 Bivariate Data 2.2.3 Multivariate Data 2.3 Data Sources 2.3.1 Primary Sources 2.3.2 Secondary Sources 2.3.3 Internal Source 2.3.4 External Source 2.4 Data Collection Inquiries 2.4.1 Survey Design 2.4.1.1 Questionnaire Design 2.4.2 Pilot Survey of the Questionnaire 2.4.3 Editing Primary Data 2.4.4 Possible Errors in Secondary Data 2.4.5 Census and Sampling Methods Exercise 2 3: Data Presentation 3.1 Introduction 3.2 Classification of Data 3.2.1 Types of Classification 3.3 Data Presentation 3.3.1 Textual Form 3.3.2 Tabular Form 3.4 Types of Variables and Data 3.5 Levels of Measurement 3.5.1 Nominal Scale 3.5.2 Ordinal Scale 3.5.3 Interval Scale 3.5.4 Ratio Scale 3.6 Frequency 3.6.1 Frequency Distributions 3.7 Types of Class Interval 3.8 Tally Mark 3.9 Construction of a Discrete Frequency Distribution 3.10 Construction of a Continuous Frequency Distribution 3.11 Cumulative and Relative Frequencies 3.12 Diagrammatic Representation of Data 3.12.1 Advantages and Disadvantages of Diagrammatic Representation 3.12.2 Types of Diagrams 3.12.2.1 Bar Diagram 3.12.2.2 Pie Diagram 3.12.2.3 Histogram, Frequency Polygon, and Frequency Curve 3.12.2.4 Frequency Polygon 3.12.2.5 Frequency Curve 3.12.2.6 Ogive Curve 3.12.2.7 Line Diagram Exercise 3 4: Measures of Central Tendency (MCT) 4.1 Introduction 4.2 MCT 4.2.1 Properties of Best Average 4.3 Arithmetic Mean 4.3.1 Discrete Data 4.3.2 Discrete Data with Frequency 4.3.3 Continuous Data with Frequency 4.4 Mathematical Properties of Arithmetic Mean 4.5 Median 4.5.1 Discrete Data 4.5.2 Discrete Data with Frequency 4.5.3 Continuous Data with Frequency 4.5.3.1 Relative Advantages 4.5.3.2 Relative Disadvantages 4.5.3.3 Property of Median 4.5.4 Graphical Method to Find the Median 4.6 Quartiles, Deciles and Percentiles 4.7 Mode 4.7.1 Discrete Data 4.7.2 Discrete Data with Frequency 4.7.3 Continuous Data with Frequency 4.7.4 A Graphical Method to Evaluate the Mode 4.8 Comparison of Mean, Median, and Mode 4.9 Weighted Arithmetic Mean 4.9.1 Advantages of the Weighted Mean 4.10 Geometric Mean 4.11 Harmonic Mean Exercise 4 5: Dispersion 5.1 Introduction 5.2 Range 5.3 Quartile Deviation (QD) 5.4 Coefficient of Quartile Deviation 5.5 Mean Deviation 5.6 Standard Deviation (SD) 5.7 Relative Measures of Dispersion Exercise 5 6: Skewness, Moments, and Kurtosis 6.1 Introduction 6.2 Dispersion and Skewness 6.3 Moments 6.4 Kurtosis Exercise 6 7: Correlation and Regression Analysis 7.1 Introduction 7.2 Correlation 7.2.1 Simple Correlation or Correlation 7.2.2 Rank Correlation 7.2.3 Group Correlation 7.2.4 Assumptions for Karl Pearson’s Coefficient of Correlation 7.2.5 Limitations 7.2.6 Properties 7.2.7 Scatter Diagram 7.3 Karl Pearson Coefficient of Correlation 7.4 Coefficient of Correlation of a Grouped Data 7.5 Probable Error of the Coefficient of Correlation 7.6 Rank Correlation 7.7 Regression Equations Exercise 7 8: Probability 8.1 Introduction 8.2 Definitions for Certain Key Terms 8.2.1 Experiment 8.2.2 Sample Space 8.2.3 Event 8.2.4 Equally Likely Events 8.2.5 Mutually Exclusive Events 8.2.6 Outcome 8.3 Meaning of Probability 8.3.1 The Classical Approach 8.3.2 The Relative Frequency Approach 8.3.3 Notation 8.3.4 Addition Rules for Probability 8.3.5 Multiplication Rule on Probability When Events Are Independent 8.3.6 Compound Probability or Conditional Probability 8.4 Bayes’ Theorem Exercise 8 9: Random Variables and Expectation 9.1 Introduction 9.2 Random Variable 9.2.1 Discrete Random Variable 9.2.2 Continuous Random Variable 9.3 Probability Distribution 9.3.1 Discrete Probability Distribution 9.3.2 Characteristics of a Discrete Distribution 9.3.3 Probability Function 9.4 Mathematical Expectation Exercise 9 10: Discrete Probability Distribution: Binomial and Poisson Distributions 10.1 Introduction 10.2 Binomial Distribution 10.2.1 Characteristics of a Bernoulli Process 10.2.2 Definition of Binomial Distribution 10.2.3 Conditions of Binomial Distribution 10.2.4 Properties of Binomial Distributions 10.2.5 Mean of Binomial Distribution 10.2.6 Variance of Binomial Distribution 10.3 Poisson Distribution 10.3.1 Definition of Poisson Distribution 10.3.2 Properties of Poisson Distribution 10.3.3 Mean of the Poisson Distribution 10.3.4 Variance of the Poisson Distribution Exercise 10 11: Continuous Probability Distribution: Normal Distribution 11.1 Introduction 11.2 Definition of Normal Distribution 11.3 Standard Normal Distribution 11.4 Properties of Normal Distribution Exercise 11 12: Theory of Sampling 12.1 Introduction 12.2 Why Sample? 12.3 How to Choose It? 12.4 Sample Design 12.5 Keywords and Notations 12.6 Advantages and Disadvantages of Sampling 12.7 Nonrandom Errors and Non-sampling Errors 12.8 Random Errors and Sampling Errors 12.9 Types of Samples 12.9.1 Probability Sample 12.9.2 Nonprobability Sample 12.10 Random Sampling 12.10.1 Systematic Sampling 12.10.2 Stratified Sampling (P, N) 12.10.3 Multistage Sampling 12.11 Nonrandom Sampling Methods 12.11.1 Convenience Sampling 12.11.2 Purposive Sampling 12.11.3 Quota Sampling 12.11.4 Cluster Sampling 12.11.5 Sequential Sampling 12.12 Sampling Distributions 12.13 Need for Sampling Distribution 12.14 Standard Error for Different Situations 12.14.1 When the Population Size Is Infinite 12.14.2 When the Population Is Finite 12.14.3 Sampling Distribution Based on Sample Means 12.15 Point and Internal Estimation 12.15.1 Point Estimate 12.15.2 Properties of Good Point Estimators 12.16 Interval Estimate 12.17 Confidence Interval Estimation for Large Samples 12.18 Confidence Intervals for Difference between Means 12.19 Estimating a Population Proportion 12.20 Estimating the Interval Based on the Difference between Two Proportions 12.21 Confidence Interval Estimation for Small Sample 12.22 Determining the Sample Size Exercise 12 13: Hypothesis Testing, Parametric Tests, Distribution Tests, and Tests of Significance 13.1 Introduction 13.2 Null Hypothesis (H0) 13.3 Alternative Hypothesis (H1) 13.4 Type I and Type II Errors 13.5 Meaning of Parametric and Nonparametric Test 13.5.1 Parametric Test 13.5.2 Nonparametric Test 13.6 Selection of Appropriate Test Statistic 13.7 Methodology of Statistical Testing 13.8 Test for a Specified Mean: Large Sample 13.9 Test for Equality of Two Populations: Large Sample 13.10 Test for Population Proportion: Large Sample 13.11 Test for Equality of Two Proportions: Large Samples 13.12 Test for Equality of Two Standard Deviations: Large Samples 13.13 Student’s t-Distribution 13.14 Properties of t-Distribution 13.15 Test for the Specified Mean: Small Sample 13.16 Test for Equality of Two Population Means: Small Samples 13.17 Paired t-Test for Difference of Mean 13.18 Chi-square Distribution 13.18.1 Properties of Chi-square Distribution 13.18.2 Chi-square Test 13.18.3 Test for Goodness of Fit 13.18.4 Tests for Independence of Attributes 13.18.5 Whenever the Expected Frequencies of the Cell Entries Are Less Than 5 13.18.6 Test for a Specified Population Variance 13.19 Snedecor’s F-Distribution 13.19.1 Properties of F-Distribution 13.19.2 Test for Difference of Two Populations’ Variances 13.20 Analysis of Variance (ANOVA) 13.20.1 One-Way Classification 13.20.2 Two-Way Classification Exercise 13 Appendix A: Answers to Exercise Problems Exercise 4 Exercise 5 Exercise 6 Exercise 7 Exercise 8 Exercise 9 Exercise 10 Exercise 11 Exercise 12 Exercise 13 Appendix B: ST Statistical Tables Index Statistics For Business Is Meant As A Textbook For Students In Business, Computer Science, Bioengineering, Environmental Technology, And Mathematics. In Recent Years, Business Statistics Is Used Widely For Decision Making In Business Endeavours. It Emphasizes Statistical Applications, Statistical Model Building, And Determining The Manual Solution Methods. Special Features: This Text Is Prepared Based On Self-taught Method. For Most Of The Methods, The Required Algorithm Is Clearly Explained Using Flow-charting Methodology. More Than 200 Solved Problems Provided. More Than 175 End-of-chapter Exercises With Answers Are Provided. This Allows Teachers Ample Flexibility In Adopting The Textbook To Their Individual Class Plans. This Textbook Is Meant To For Beginners And Advanced Learners As A Text In Statistics For Business Or Applied Statistics For Undergraduate And Graduate Students. T;/ul> This Textbook Is Meant To For Beginners And Advanced Learners As A Text In Statistics For Business Or Applied Statistics For Undergraduate And Graduate Students. This Business Statistics book has been contrived to serve as a textbook for students in business, computer science, bio-engineering, environmental technology and mathematics. It emphasizes statistical applications, statistical model building and determining manual methods of solution.