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E-grāmata: Quantitative Techniques in Business, Management and Finance: A Case-Study Approach

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, (Government Polytechnic, Nagpur, INDIA), (Department of Mathematics & Statistics, MIT WPU Pune)
  • Formāts: 502 pages
  • Izdošanas datums: 25-Nov-2016
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-13: 9781315350073
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Quantitative Techniques in Business, Management and Finance: A Case-Study ApproachPalielināt
  • Formāts: 502 pages
  • Izdošanas datums: 25-Nov-2016
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-13: 9781315350073
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This book is especially relevant to undergraduates, postgraduates and researchers studying quantitative techniques as part of business, management and finance. It is an interdisciplinary book that covers all major topics involved at the interface between business and management on the one hand and mathematics and statistics on the other. Managers and others in industry and commerce who wish to obtain a working knowledge of quantitative techniques will also find this book useful.

Preface xxi
Acknowledgements xxiii
Authors xxv
1 Quantitative Decision Making - An Overview
1(16)
1.1 Introduction
1(1)
1.2 Meaning of Quantitative Techniques
2(1)
1.2.1 Concept of Statistics
2(1)
1.2.2 Concept of Operations Research
2(1)
1.3 Evolution of Quantitative Techniques
2(1)
1.4 Classification of Quantitative Methods
3(1)
1.5 Data Collection
4(1)
1.5.1 Statistical Data
4(1)
1.5.2 Statistical Methods
4(1)
1.5.3 Data Collection
4(1)
1.5.4 Organisation of Data
4(1)
1.6 Characteristics of Data
4(1)
1.7 Types of Statistical Data
5(1)
1.7.1 Arriving at the Solution
5(1)
1.7.2 Presentation
6(1)
1.7.3 Analysis
6(1)
1.7.4 Interpretation
6(1)
1.8 Classification of Quantitative Techniques
6(2)
1.8.1 Descriptive Statistics
7(1)
1.8.2 Inductive Statistics
7(1)
1.8.3 Statistical Decision Theory
7(1)
1.9 Methodology of Quantitative Techniques
8(1)
1.9.1 Steps
8(1)
1.10 Various Statistical Methods
8(3)
1.10.1 Measure of Central Tendency
8(1)
1.10.1.1 Mean
8(1)
1.10.1.2 Median
9(1)
1.10.1.3 Mode
9(1)
1.10.2 Measures of Dispersion
9(1)
1.10.3 Correlation
9(1)
1.10.4 Regression Analysis
9(1)
1.10.5 Time-Series Analysis
9(1)
1.10.6 Index Numbers
10(1)
1.10.7 Sampling and Statistical Inference
10(1)
1.10.7.1 Random Sampling
10(1)
1.10.7.2 Non-Random Sampling
10(1)
1.11 Advantages of Quantitative Methods
11(1)
1.11.1 Definiteness
11(1)
1.11.2 Condensation
11(1)
1.11.3 Comparison
11(1)
1.11.4 Policy Formulation
12(1)
1.11.5 Hypothesis Testing
12(1)
1.11.6 Prediction
12(1)
1.12 Application of Quantitative Techniques in Business Management
12(1)
1.12.1 Management
12(1)
1.12.1.1 Marketing Management
12(1)
1.12.1.2 Production Management
12(1)
1.12.1.3 Finance Management
12(1)
1.12.1.4 Personnel Management
13(1)
1.12.2 Economics
13(1)
1.12.3 Research and Development
13(1)
1.12.4 Natural Science
13(1)
1.13 Limitations of Quantitative Techniques
13(1)
1.14 Summary
14(3)
2 Arranging Data
17(22)
2.1 Meaning of Data
17(1)
2.2 Types of Data
17(2)
2.2.1 Published Data
17(1)
2.2.1.1 Published Sources
17(1)
2.2.2 Unpublished Data
17(1)
2.2.2.1 Unpublished Sources
18(1)
2.2.3 Primary Data
18(1)
2.2.3.1 Editing Primary Data
18(1)
2.2.4 Secondary Data
19(1)
2.2.4.1 Precautions in the Use of Secondary Data
19(1)
2.3 Primary versus Secondary Data
19(1)
2.4 Classification of Data
20(1)
2.4.1 Methods of Classification
20(1)
2.4.1.1 Geographical Classification
20(1)
2.4.1.2 Chronological Classification
20(1)
2.4.1.3 Qualitative Classification
21(1)
2.4.1.4 Quantitative Classification
21(1)
2.5 Data Collection
21(3)
2.5.1 Population
21(1)
2.5.2 Sample
21(1)
2.5.3 Testing the Validity of Data
21(1)
2.5.4 Complete Enumeration or Census Survey or Census
22(1)
2.5.5 Sample Method
22(1)
2.5.6 Methods of Collecting Primary Data
22(1)
2.5.6.1 Observation Method
22(1)
2.5.6.2 Personal Interviews
22(1)
2.5.6.3 Questionnaire Method
22(2)
2.6 Data Presentation Devices
24(1)
2.6.1 Tables
24(1)
2.6.2 Tabulation
24(1)
2.6.3 Uses of Tabulation
24(1)
2.6.4 Objectives of Tabulation
24(1)
2.6.5 Parts of an Ideal Table
25(1)
2.7 Graphs
25(3)
2.7.1 Types of Graphs or Charts
25(1)
2.7.1.1 Rules for Constructing the Line Graph
25(1)
2.7.1.2 Bar Chart
26(1)
2.7.1.3 Pie Diagram
27(1)
2.8 Frequency Distribution
28(2)
2.8.1 Discrete Frequency Distribution
28(1)
2.8.2 Continuous Frequency Distribution
29(1)
2.8.2.1 Types of Class interval
29(1)
2.8.2.2 Selection of Class Intervals
30(1)
2.8.3 Cumulative Frequencies
30(1)
2.8.4 Relative Frequencies
30(1)
2.9 Histogram
30(2)
2.9.1 Relative Frequency Histogram
31(1)
2.9.2 Absolute Histogram
32(1)
2.9.3 Difference between a Relative Frequency Histogram and an Absolute Histogram
32(1)
2.10 Frequency Polygon
32(1)
2.11 Frequency Curve
33(1)
2.12 Cumulative Frequency Distribution
34(2)
2.12.1 Ogive or Cumulative Frequency Curve
34(1)
2.12.1.1 Less than Ogive
34(1)
2.12.1.2 More than Ogive
35(1)
2.13 Skewness and Kurtosis
36(1)
2.13.1 Skewness
36(1)
2.13.1.1 Symmetrical Curves
36(1)
2.13.1.2 Skewed Curve
36(1)
2.13.1.3 Positively Skewed Curve
37(1)
2.13.1.4 Negatively Skewed Curve
37(1)
2.13.2 Kurtosis
37(1)
2.14 Summary
37(2)
3 Measures of Central Tendency
39(32)
3.1 Introduction
39(1)
3.2 Significance of Measures of Central Tendency
39(1)
3.3 Properties of Good Measures of Central Tendency
40(1)
3.4 Arithmetic Mean
40(10)
3.4.1 Calculating the Mean from Ungrouped Data
40(7)
3.4.2 Mathematical Properties of Arithmetic Mean
47(1)
3.4.3 Weighted Arithmetic Mean
48(2)
3.5 Median
50(6)
3.5.1 Calculating the Median from Ungrouped Data
51(4)
3.5.2 Mathematical Properties of Median
55(1)
3.6 Quantiles
56(2)
3.6.1 Quartiles
56(1)
3.6.2 Deciles
56(1)
3.6.3 Percentiles
56(2)
3.7 Mode
58(3)
3.8 Relationship among Mean, Median and Mode
61(1)
3.9 Comparison of Mean and Median
62(1)
3.10 Geometric Mean
62(3)
3.11 Harmonic Mean
65(3)
3.12 Summary
68(3)
4 Measures of Variation and Skewness
71(32)
4.1 Introduction
71(1)
4.1.1 Significance of Measuring Variation
71(1)
4.1.2 Absolute versus Relative Measures of Variation
71(1)
4.2 Range
72(7)
4.2.1 For Ungrouped Data
72(1)
4.2.2 For Grouped Data
72(1)
4.2.3 Coefficient of Range
73(1)
4.2.4 Interquartile Range
74(1)
4.2.4.1 Need for Interquartile Range
74(1)
4.2.4.2 Definition of Interquartile Range
74(1)
4.2.5 Semi-Interquartile Range or Quartile Deviation
74(1)
4.2.5.1 For Ungrouped Data
75(1)
4.2.5.2 For Grouped Data
75(1)
4.2.5.3 Coefficient of Quartile Deviation
76(3)
4.3 Mean Deviation or Average Deviation
79(8)
4.3.1 Discrete Series
80(2)
4.3.2 Continuous Series
82(5)
4.4 Standard Deviation
87(4)
4.4.1 Individual Series
87(1)
4.4.2 Discrete Series
88(1)
4.4.3 Step Deviation Method
89(1)
4.4.4 Continuous Series
90(1)
4.5 Variance
91(1)
4.5.1 For Grouped and Ungrouped Data
91(1)
4.6 Coefficient of Variation
92(4)
4.7 Bienayme--Chebyshev Rule
96(1)
4.7.1 Statement of the Bienayme--Chebyshev Rule
96(1)
4.7.2 Application
96(1)
4.8 Skewness
97(2)
4.8.1 Relative Skewness
98(1)
4.9 Summary
99(4)
5 Probability Theory
103(40)
5.1 Introduction
103(1)
5.2 Basic Concepts
104(2)
5.2.1 Experiment
104(1)
5.2.2 Random Experiment
104(1)
5.2.3 Outcome
104(1)
5.2.4 Sample Space
104(1)
5.2.5 Event
104(1)
5.2.6 Certain Event
104(1)
5.2.7 Impossible Event
105(1)
5.2.8 Compound Event
105(1)
5.2.9 Complement of an Event
105(1)
5.2.10 Mutually Exclusive Events
105(1)
5.2.11 Independent Events
105(1)
5.2.12 Dependent Events
106(1)
5.2.13 Exhaustive Events
106(1)
5.2.14 Favourable Event
106(1)
5.2.15 Equally Likely Event
106(1)
5.2.16 Sample Spaces
106(1)
5.3 Probability
106(4)
5.3.1 Classical Probability
107(1)
5.3.1.1 Definition of Classical Probability
107(1)
5.3.2 Relative Frequency
108(1)
5.3.2.1 Relative Frequency of Occurrence Approach
108(1)
5.3.3 Limitation of the Classical Approach
109(1)
5.3.3.1 Limitations of Classical Approach to Probability
109(1)
5.3.4 Subjective Probability
110(1)
5.3.5 Marginal or Unconditional Probability
110(1)
5.3.6 Empirical Probability
110(1)
5.4 Probability Rules
110(6)
5.4.1 Additional Rule (Mutually Exhaustive Events)
112(1)
5.4.1.1 Addition Theorem
112(1)
5.4.1.2 Sample Space
112(1)
5.4.2 Additional Rule (Not Mutually Exhaustive Events)
113(1)
5.4.2.1 Multiplication Theorem
113(1)
5.4.3 Multiplication Rule (Independent Events)
114(1)
5.4.4 Multiplication Rule (Dependent Events)
114(1)
5.4.5 Axioms to Probability
115(1)
5.4.6 Addition Theorem
115(1)
5.4.7 Multiplication Theorem
115(1)
5.5 Conditional Probability
116(7)
5.5.1 Dependent Events
117(1)
5.5.2 A Priori or Prior Probability
118(1)
5.5.3 Posterior or Revised Probability
118(1)
5.5.4 Bayes' Theorem
118(1)
5.5.5 Application of Bayes' Theorem
119(4)
5.6 Set Theory
123(2)
5.6.1 Power of Set
123(1)
5.6.2 Elementary Concepts of Set
123(1)
5.6.2.1 Universal Set
123(1)
5.6.2.2 Subset of a Set
123(1)
5.6.2.3 Equality of Two Sets
124(1)
5.6.2.4 Complement of a Set
124(1)
5.6.2.5 Difference of Two Sets
124(1)
5.6.2.6 Cardinal Number of a Finite Set
125(1)
5.6.3 Operations of Sets
125(1)
5.6.3.1 Union of Two Sets
125(1)
5.6.3.2 Intersection of Two Sets
125(1)
5.6.3.3 Difference of Two Sets
125(1)
5.7 Venn Diagram
125(2)
5.7.1 Universal Set
125(1)
5.7.2 Complementary Set
126(1)
5.7.3 Union of Two Sets
126(1)
5.7.4 Intersection of Two Sets
126(1)
5.7.5 Difference of Two Sets
126(1)
5.7.6 Enhanced Application of the Venn Diagram
127(1)
5.8 Fundamental Laws of Operation
127(14)
5.9 Summary
141(2)
6 Statistical Decision Theory
143(24)
6.1 Introduction
143(1)
6.2 Decision Theory
143(2)
6.2.1 Certain Key Issues in Decision Theory
144(1)
6.2.2 Applications of Business Decision Making
144(1)
6.2.3 Framework for Decision Making
144(1)
6.2.4 Decision Making under Uncertainty
144(1)
6.2.5 Concept of Business Decision Making and Business Decision
145(1)
6.3 Determinants
145(2)
6.3.1 Business Environment
145(1)
6.3.2 Business Objective
145(1)
6.3.3 Alternative Course of Action/Strategies
146(1)
6.3.4 Decision Pay-Off or Pay-Off Matrix
146(1)
6.3.5 Decision Criteria
146(1)
6.3.6 Miscellaneous Factors
146(1)
6.4 Business Decision Theory under Certainty
147(2)
6.5 Business Decision Theory under Risk (Stochastic Business Situation)
149(4)
6.5.1 EMV Criterion
149(1)
6.5.1.1 Without Given Probability of Each State of Nature (Pj, Not Given)
149(1)
6.5.1.2 With Given Probability of Each State of Nature (Pj, Given)
150(1)
6.5.2 EOL Criterion
151(1)
6.5.2.1 Without Given Probability of Each State of Nature (Pj, Not Given)
151(1)
6.5.2.2 With Given Probability of Each State of Nature (Pj, Given)
152(1)
6.6 Business Decision Theory under Uncertainty
153(8)
6.6.1 Maximin Criterion
154(1)
6.6.2 Minimax Regret Criteria (Savage Principle) or Criterion of Pessimism or Wald's Criterion
155(1)
6.6.2.1 Working Method
155(1)
6.6.3 Maximax Criterion
156(1)
6.6.3.1 Working Method
156(1)
6.6.4 Equally Likely Decision (Laplace Criterion)
157(1)
6.6.4.1 Working Method
157(1)
6.6.5 Criterion of Realism (Hurwicz Alpha Criterion)
158(2)
6.6.6 Regret Criterion
160(1)
6.7 Decision Tree Analysis
161(4)
6.8 Summary
165(2)
7 Linear Programming and Problem Formulation
167(18)
7.1 Introduction
167(1)
7.2 Linear Programming Problem
167(7)
7.2.1 Linearity
167(1)
7.2.2 Definition of LPP
168(1)
7.2.3 Features of LPP
168(1)
7.2.4 Importance of LPP
168(1)
7.2.4.1 Modern Management
169(1)
7.2.4.2 Industry
169(1)
7.2.4.3 Other Uses
170(1)
7.2.5 Applications of Linear Programming
170(1)
7.2.6 Requirements of an LPP
170(1)
7.2.7 Formulation of LPP
171(1)
7.2.8 Essential Requirements to Formulate LPP
172(1)
7.2.8.1 Decision Variables
172(1)
7.2.8.2 Objective Function
172(1)
7.2.8.3 Constraint Function
173(1)
7.2.8.4 Non-Negative Function
173(1)
7.2.8.5 Alternative Course of Action
173(1)
7.2.8.6 Non-Negative Restriction
173(1)
7.2.8.7 Linearity
173(1)
7.3 Assumptions of Linear Programming Models
174(1)
7.3.1 Proportionality
174(1)
7.3.2 Additivity
174
7.3.3 Divisibility
174(3)
7.3.4 Certainty
174(1)
7.4 Graphical Method of Solving an LPP
174(3)
7.4.1 Infeasible Solution
175(1)
7.4.2 Unbounded Solution
175(2)
7.4.3 Redundancy
177(1)
7.4.4 Multiple Solutions
177(1)
7.5 Duality
177(4)
7.5.1 Primal LPP versus Dual LPP
178(1)
7.5.2 Conversion of Dual from Primal
178(3)
7.6 Summary
181(4)
8 Sampling Theory
185(26)
8.1 Introduction
185(1)
8.2 Sample
185(3)
8.2.1 Differences between Random Sample and Non-Random Sample
185(1)
8.2.2 Differences between Population and Sample
185(1)
8.2.3 Determination of Sample Size
186(2)
8.3 Sampling
188(1)
8.3.1 Population
188(1)
8.3.2 Census or Complete Enumeration
188(1)
8.3.3 Sample or Selective Enumeration
188(1)
8.3.3.1 Characteristics of a Good Sample
189(1)
8.4 Sampling Methods
189(1)
8.4.1 Purposive or Subjective or Judgement Sampling
189(1)
8.4.2 Probability Sampling
190(1)
8.4.3 Mixed Sampling
190(1)
8.5 Simple Random Sampling
190(4)
8.5.1 Mathematically
190(1)
8.5.2 Selection of SR Sample
191(1)
8.5.2.1 Lottery Method
191(1)
8.5.2.2 Use of Table of Random Numbers
191(3)
8.6 Stratified Random Sampling
194(5)
8.6.1 Why Strata Are Created
195(1)
8.6.2 Size of the Sample
196(1)
8.6.2.1 Proportionate Manner
196(1)
8.6.2.2 Disproportionate Manner
196(1)
8.6.2.3 Optimum Manner
196(3)
8.7 Systematic Random Sampling or Quasi-Random Sampling or Interval Sampling
199(2)
8.7.1 Application of Systematic Sampling
201(1)
8.8 Cluster Sampling
201(2)
8.8.1 Importance of Cluster Sampling
202(1)
8.8.2 Application
202(1)
8.9 Multi-Stage Random Sampling
203(1)
8.10 Area Sampling
204(1)
8.11 Quota Sampling
204(1)
8.12 Non-Random/Non-Probability Sampling and Judgement Sampling
205(1)
8.12.1 Judgement Sampling or Purpose Sampling or Deliberated Sampling
205(1)
8.12.2 Convenience Sampling or Haphazard or Accidental Sampling or Chunk Sampling
205(1)
8.12.3 Sequential Sampling
206(1)
8.12.3.1 Application
206(1)
8.13 Error
206(3)
8.13.1 Sampling Error
206(1)
8.13.1.1 Reasons for Sampling Errors
207(1)
8.13.2 Non-Sampling Error
207(1)
8.13.2.1 Important Factors Responsible for Non-Sampling Errors in Any Survey
207(1)
8.13.2.2 Biased Errors or Cumulative Errors
208(1)
8.13.2.3 Unbiased Errors (Compensatory Error)
209(1)
8.14 Summary
209(2)
9 Hypothesis Testing
211(34)
9.1 Introduction
211(1)
9.2 Some Basic Concepts
211(3)
9.2.1 Null Hypothesis
211(1)
9.2.2 Alternative Hypothesis
211(1)
9.2.3 Hypothesis Testing
212(1)
9.2.4 Power
212(1)
9.2.5 Critical Region or Region of Rejection
212(1)
9.2.6 Region of Acceptance
212(1)
9.2.7 Critical Values
212(1)
9.2.8 Z-Score
212(1)
9.2.9 Inferential Statistics
212(1)
9.2.10 Types of Errors
213(1)
9.2.11 Level of Significance
213(1)
9.2.12 Confidence Interval
213(1)
9.2.13 Degrees of Freedom
213(1)
9.2.14 Test of Significance
213(1)
9.2.15 Parametric Test
214(1)
9.2.16 Non-Parametric Tests
214(1)
9.3 Probability Distributions
214(17)
9.3.1 Binomial Distribution
214(1)
9.3.1.1 Assumption
214(1)
9.3.1.2 Bernoulli Variable
214(1)
9.3.1.3 Random Variable
214(1)
9.3.1.4 Characteristics of Bernoulli Process
215(2)
9.3.2 Poisson Distribution
217(1)
9.3.2.1 Definition
217(1)
9.3.2.2 History
217(1)
9.3.2.3 Need for Poisson Probability Distribution
218(1)
9.3.2.4 Applications of the Poisson Distribution
218(1)
9.3.2.5 Properties of the Poisson Distribution
218(2)
9.3.3 Normal Probability Distribution
220(1)
9.3.3.1 Discrete Random Variable
220(1)
9.3.3.2 Continuous Random Variable
221(1)
9.3.3.3 Characteristics of Normal Distribution
221(1)
9.3.3.4 Gaussian or Normal Curve
222(1)
9.3.3.5 Properties of the Normal Probability Curve
222(1)
9.3.3.6 Importance of Normal Probability Curve
223(1)
9.3.3.7 Finding Probability for Different Values of Z (Using Table)
223(7)
9.3.3.8 Standard Normal Distribution
230(1)
9.3.3.9 Standard Normal Variables
230(1)
9.4 t-Test
231(12)
9.4.1 Types of t-Tests
231(1)
9.4.2 Assumptions for the t-Test Application
232(1)
9.4.3 Characteristics of Student's t or the t-Distribution
232(1)
9.4.4 t-Distribution with (n -- 1) Degrees of Freedom
232(1)
9.4.5 Uses of t-Distribution
232(1)
9.4.6 Test for the Population Mean (Single)
232(2)
9.4.7 Hypothesis Tests of Mean When Population Standard Deviation Is Known and Unknown for Large Samples (p-Value Approach)
234(1)
9.4.8 Test for Equality of Means for Small and Independent Samples
235(1)
9.4.8.1 Assumption
235(1)
9.4.8.2 Confidence Interval
236(1)
9.4.8.3 t-Distribution Value
236(1)
9.4.8.4 Hypothesis Testing
236(2)
9.4.9 Equality of Means for Dependent Samples
238(1)
9.4.10 Paired t-test
238(1)
9.4.11 Paired Difference
238(1)
9.4.11.1 Confidence Interval
239(1)
9.4.11.2 Hypothesis Testing
239(4)
9.5 Summary
243(2)
10 The Chi-Square Tests
245(16)
10.1 Introduction
245(1)
10.2 Chi-Square, Χ2
245(5)
10.2.1 Need for the Χ2-Test
246(1)
10.2.2 Conditions for the Validity of Χ2
246(1)
10.2.2.1 Assumptions
246(1)
10.2.2.2 Interval Scale
246(1)
10.2.2.3 Nominal-Level or Nominal-Scale Data
246(1)
10.2.2.4 Ordinal-Level Data
246(1)
10.2.3 Degrees of Freedom
246(1)
10.2.3.1 In Binomial Distribution
247(1)
10.2.3.2 In Poisson Distribution
247(1)
10.2.3.3 In Normal Distribution
247(1)
10.2.3.4 For a Contingency Table
247(1)
10.2.3.5 Important Characteristics of Degrees of Freedom (v)
248(1)
10.2.4 General Aspects of Χ2
248(1)
10.2.5 Characteristics of the Chi-Square Distribution
248(1)
10.2.6 Application of Chi-Square
249(1)
10.2.7 Limitations of Chi-Square
249(1)
10.3 Chi-Square Test of Goodness of Fit
250(1)
10.3.1 Procedure for Χ-Test of Goodness of Fit -- Steps
250(1)
10.3.2 Critical Value
250(1)
10.3.3 Decision Rules
250(1)
10.4 Chi-Square Test - Test of Independence
251(6)
10.4.1 Characteristics
251(1)
10.4.2 Procedure for x2-Test of Independence - Steps
251(6)
10.5 Strength of Association
257(1)
10.6 Phi-Coefficient
257(1)
10.7 Coefficient of Contingency
258(1)
10.8 Summary
258(3)
11 Business Forecasting
261(14)
11.1 Introduction
261(1)
11.2 Forecasting
261(1)
11.3 Future Uncertainty
262(1)
11.4 Forecasting for Planning Decisions
262(1)
11.5 Steps in Forecasting
263(1)
11.6 Methods of Forecasting
263(5)
11.6.1 Business Barometers
264(1)
11.6.2 Extrapolation
264(1)
11.6.3 Regression Analysis
265(1)
11.6.4 Econometric Models
266(1)
11.6.5 Forecasting by the Use of Time Series Analysis
267(1)
11.6.6 Opinion Polling
267(1)
11.6.7 Causal Models
267(1)
11.7 Choice of a Method of Forecasting
268(1)
11.8 Theories of Business Forecasting
268(3)
11.8.1 Sequence or Time-Lag Theory
268(1)
11.8.2 Action and Reaction Theory
269(1)
11.8.3 Economic Rhythm Theory
269(1)
11.8.4 Specific Historical Analogy
270(1)
11.8.5 Cross-Section Analysis
270(1)
11.9 Forecasting Agencies
271(1)
11.10 Caution While Using Forecasting Techniques
271(1)
11.11 Advantages of Forecasting
271(1)
11.12 Disadvantages of Forecasting
272(1)
11.13 Summary
273(2)
12 Correlation Analysis
275(28)
12.1 Introduction
275(1)
12.2 Correlation
275(3)
12.2.1 Correlation Coefficient
276(1)
12.2.2 Correlation Analysis
276(1)
12.2.3 Bi-Variate Correlation
276(1)
12.2.3.1 Bi-Variate Data
276(1)
12.2.4 Correlation: Cause and Effect Relation
276(1)
12.2.5 Significance of Correlation
277(1)
12.2.6 Limitations of Correlation
277(1)
12.2.7 Properties of Correlation
278(1)
12.3 Types of Relationships
278(2)
12.3.1 Positive or Negative
279(1)
12.3.2 Simple, Partial and Multiple
279(1)
12.3.3 Linear and Non-Linear or Curvilinear Correlation
279(1)
12.4 Difference between Positive and Negative Correlation
280(1)
12.5 Distinction between Simple, Partial and Multiple Correlation
280(1)
12.5.1 No Correlation
281(1)
12.6 Lag and Lead in Correlation
281(1)
12.7 Methods of Studying Correlation
281(10)
12.7.1 Scatter Diagram Method or Dotogram or Scatter Gram or Dot Chart
282(1)
12.7.2 Karl Pearson's Coefficient of Correlation or Pearsonian Coefficient of Correlation
283(4)
12.7.3 Karl Pearson's Correlation Coefficient (Actual Mean Method)
287(4)
12.7.4 Correlation Coefficient when Deviations Are Taken from an Assumed Mean
291(1)
12.8 Correlation of Bi-Variate Grouped Data
291(1)
12.9 Caveat
292(1)
12.10 Coefficient of Determination
292(1)
12.11 Spearman's Rank Correlation Coefficient
293(4)
12.12 Coefficient of Correlation and Probable Error
297(1)
12.12.1 Conditions for the Use of Probable Error
297(1)
12.13 Summary
298(5)
13 Regression Analysis
303(34)
13.1 Introduction
303(1)
13.2 Regression
303(7)
13.2.1 History, Meaning and Application
303(1)
13.2.2 Regression Analysis
304(1)
13.2.3 Advantages of Regression Analysis
304(1)
13.2.4 Features of Regression
304(1)
13.2.5 Assumptions in Regression Analysis
304(1)
13.2.6 Application of Regression
305(1)
13.2.7 Limitations of Regression Analysis
305(1)
13.2.8 Regression Coefficient
305(2)
13.2.9 Properties of the Regression Coefficients
307(1)
13.2.10 Features of Regression Coefficients
308(1)
13.2.11 Regression Line
308(1)
13.2.12 Interpretation of Regression line
309(1)
13.2.13 Role of Regression Analysis in Business Decision Making
309(1)
13.2.14 Correlation Analysis versus Regression Analysis
309(1)
13.3 The Least-Squares Method
310(1)
13.3.1 Application of Least-Squares Method
311(1)
13.4 Standard Error of Estimate (SE)
311(2)
13.4.1 Standard Error of Estimate of Y on X
312(1)
13.4.2 Interpretation of SE of Estimates
312(1)
13.5 Multiple Regressions
313(20)
13.5.1 Multiple Regression Equation
313(1)
13.5.2 Multicollinearity
313(20)
13.6 Summary
333(4)
14 Time Series Analysis
337(42)
14.1 Introduction
337(1)
14.2 Time Series
337(2)
14.2.1 Definition
337(1)
14.2.2 Features of Time Series
338(1)
14.2.3 Uses of Analysis of Time Series
338(1)
14.3 Components of Time Series
339(2)
14.3.1 Secular Trend or Long-Term Trend
339(1)
14.3.1.1 Meaning of Long Term
340(1)
14.3.1.2 Measurement of Secular Trends
340(1)
14.3.1.3 Features of Secular Trends
340(1)
14.3.1.4 Uses of Secular Trends
341(1)
14.4 Seasonal Variations
341(2)
14.4.1 Factors that Cause Seasonal Variations
342(1)
14.4.2 Application of Seasonal Variation
342(1)
14.4.3 Features of Seasonal Variations
343(1)
14.5 Cyclical Variations
343(2)
14.5.1 Business Cycle
343(1)
14.5.1.1 Periods or Phases in the Business Cycle
343(2)
14.5.2 Importance of Measuring Cyclical Variation
345(1)
14.5.3 Limitations of Measuring Cyclical Variation
345(1)
14.6 Irregular Variations, Random Movements, Unpredictable Movements, Erratic Variations or Accidental Variations
345(1)
14.6.1 Reasons for Recognising Irregular Movements
346(1)
14.7 Measurement of Trend
346(19)
14.7.1 Freehand or Graphic Method of Measuring Trend
347(1)
14.7.2 Semi-Average Method
348(3)
14.7.3 Moving Average Method
351(5)
14.7.4 The Method of Least Squares
356(9)
14.8 Second-Degree Parabola
365(1)
14.9 Measurement of Seasonal Variations
366(10)
14.9.1 Seasonal Index
366(1)
14.9.2 Criteria for Computing an Index of Seasonal Variation
367(1)
14.9.3 Methods Used for Measuring Seasonal Variations
367(1)
14.9.3.1 Method of Simple Averages (Weekly, Monthly or Quarterly)
367(2)
14.9.3.2 Ratio-to-Trend Method or Percentage-to-Trend Method
369(3)
14.9.3.3 Ratio-to-Moving Average Method or Percentages of Moving Average Method
372(2)
14.9.3.4 Link Relative Method
374(2)
14.10 Summary
376(3)
15 Research Methodology
379(16)
15.1 Introduction
379(1)
15.2 Types of Research
380(3)
15.2.1 Application of Descriptive Research
380(1)
15.2.2 Analytical Research
381(1)
15.2.3 Applied Research
381(1)
15.2.4 Fundamental Research
381(1)
15.2.5 Quantitative Research
381(1)
15.2.6 Attitude or Opinion Research
381(1)
15.2.7 Qualitative Research
381(1)
15.2.8 Motivation Research
381(1)
15.2.9 Conceptual Research
381(1)
15.2.10 Empirical Research
381(1)
15.2.11 Descriptive Research or Ex Post Facto Research
382(1)
15.2.12 Categorical Research
382(1)
15.2.13 Longitudinal Research
382(1)
15.2.14 Field-Setting or Laboratory or Simulation Research
382(1)
15.2.15 Clinical or Diagnostic Research
382(1)
15.2.16 Exploratory Research
382(1)
15.2.17 Formalised Research
382(1)
15.2.18 Historical Research
382(1)
15.2.19 Target-Oriented Research
383(1)
15.2.20 Decision-Oriented Research
383(1)
15.2.21 Operation Research
383(1)
15.2.22 Market Research
383(1)
15.3 Types of Research Approach
383(1)
15.3.1 Quantitative Approach
383(1)
15.3.2 Inferential Approach
383(1)
15.3.3 Experimental Approach
383(1)
15.3.4 Simulation Approach
383(1)
15.3.5 Qualitative Approach
384(1)
15.4 Benefits of Research
384(1)
15.4.1 Benefits in Business and Industry
384(1)
15.4.2 Benefits to Society
384(1)
15.4.3 Benefits for Professions, Philosophers and Thinkers
384(1)
15.5 Contents of Research Plan
385(2)
15.5.1 Layout of the Report
385(1)
15.5.2 Preliminary Pages
385(1)
15.5.3 Main Text
385(1)
15.5.3.1 Introduction
386(1)
15.5.3.2 Statement of Findings and Recommendations
386(1)
15.5.3.3 Results
386(1)
15.5.3.4 Implications of the Results
387(1)
15.5.3.5 Summary
387(1)
15.5.4 End Matter
387(1)
15.6 Criteria of Good Research
387(1)
15.7 Features of a Research Report
387(5)
15.7.1 Problem Definition
388(1)
15.7.2 Research Objectives
388(1)
15.7.3 Background Material
389(1)
15.7.4 Methodology
389(1)
15.7.4.1 Sampling Design
389(1)
15.7.4.2 Research Design
389(1)
15.7.4.3 Data Collection
390(1)
15.7.4.4 Data Analysis
390(1)
15.7.4.5 Limitations
390(1)
15.7.4.6 Findings
390(1)
15.7.4.7 Conclusions
391(1)
15.7.4.8 Recommendations
391(1)
15.7.4.9 Appendices
391(1)
15.7.4.10 Bibliography
391(1)
15.7.4.11 Index
391(1)
15.8 Summary
392(3)
16 Case Studies for Highlighting Quantitative Techniques
395(18)
16.1 Application of Hypothesis Testing in Industry
395(6)
16.1.1 Introduction
395(1)
16.1.2 Company Profile
395(1)
16.1.3 Brands
396(1)
16.1.4 Marketing
396(1)
16.1.5 Area of Study
396(1)
16.1.6 Data Source
396(1)
16.1.7 Data Analysis
397(1)
16.1.8 Findings
398(1)
16.1.9 Thrust Area of the Project
399(2)
16.2 Universal Home Care Products
401(3)
16.2.1 Introduction
401(1)
16.2.2 Recent Development
402(1)
16.2.3 The Problem
402(1)
16.2.4 Procedure
402(2)
16.3 Model Pertaining to Heart Attack
404(4)
16.3.1 Introduction
404(1)
16.3.2 The Problem
405(1)
16.3.3 My Idea
405(1)
16.3.4 Details
405(1)
16.3.5 Objectives
405(1)
16.3.6 Methodology
405(1)
16.3.7 Related Works
406(2)
16.3.8 Conclusion and Further Work
408(1)
16.4 A Study of Mall Intercept Survey by the Application of Purchase Intercepts Technique
408(5)
16.4.1 Introduction
408(1)
16.4.2 Problem Statement
408(1)
16.4.3 Company Profile
408(1)
16.4.4 Methodology
409(1)
16.4.4.1 Sampling Design
409(1)
16.4.4.2 Research Design
409(1)
16.4.5 Data Collection
410(1)
16.4.6 Data Analysis
410(1)
16.4.7 Primary Data
410(1)
16.4.8 Findings
411(1)
16.4.9 Conclusion
411(1)
16.4.10 Appendix: Questionnaires
412(1)
17 Multiple Choice Questions with Answers and Necessary Explanation
413(20)
Bibliography 433(8)
Glossary 441(14)
Appendix I Areas under the Normal Curve Corresponding to Given Value of z 455(6)
Appendix II Student's t-Distribution 461(2)
Appendix III The Χ2 Distribution 463(2)
Appendix IV The F-Distribution 465(4)
Appendix V Proportions of Area for the %2 Distribution 469(2)
Appendix VI Area under Normal Curve 471(2)
Index 473
Dr. Umeshkumar Dubey is the head of MBA TGPCET, Nagpur. He earned a PhD in statistics from RTMNU, Nagpur. Dr. Dubey has more than 17 years of teaching and research experience. Dr. D P Kothari is the Director Research, S B Jain Institute of Technology, Management & Research, Nagpur. He has been research director of GPGI, Nagpur, vice-chancellor of Vellore University, director IIT, Delhi and principal of VRCE, Nagpur. Dr. Kothari has 50 years of teaching and research experience. Dr. G K Awari is the principal of TGPCET, Nagpur and he has more than 22 years of experience in academics.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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