Statistics for Business

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