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Prabhakar Bhattacharya
Prabhakar Bhattacharya

The document discusses the scope and applications of statistics. It provides definitions of key terms and outlines the typical phases of a statistical study. It then discusses the scope of statistics in simplifying data, quantifying uncertainty, discovering patterns, and helping with decision making. Several applications of statistics are mentioned, including in marketing, economics, finance, operations, and more. Statistical techniques commonly used in different fields are listed with examples.

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Chapter 1 Introduction – Scope & Applications
Definition of Statistics Historical Development Phases of a Statistical Study Scope and Limitations of Statistics Applications of Statistics in Marketing, Economics, Finance, Operations, Human Resource Development, Information Systems, Data Mining. Introduction – Scope & Applications
Defining Objective(s) Specification of the Population and its Characteristic(s) Planning for Collection of Data - Census Vs Sampling Collection of Data Compilation/Presentation of Data Statistical Analysis Drawing Conclusions, Testing Assumptions or Making Predictions Phases of a Statistical Study
Scope of Statistics Statistics increases the field of mental vision just as a binocular increases the field of physical vision Simplifies unwieldy and complex mass of data, and present them in a form and manner that they become intelligible. Conversion of data into information, makes it better suited for decision making
Scope of Statistics Quantifies and measures uncertainty and variability, and thereby helps in decision making Discovers past and emerging patterns in a data. Using such analysis, it helps in forecasting. Sometimes, Statistics can even suggest possible reasons for such pattern. Helps in estimation and validating assumptions.
Ways of manipulating the data Changing definition of a variable to suit preconceived notion Inadequate sample or unrepresentative sample selection Manipulative collection of data Interpretation of association and correlation Inappropriate comparison Defective data – definition confusing or not considering all possibilities
Applications of Statistics in Various Areas Marketing Economics Finance Insurance Operations Human Resource Management or Development Information Systems Data Mining
Illustrative List of Statistical Techniques and their Applications Hedging of Investments Financial Risk Correlation and Regression Analysis 5 Quality Control Production Engineering Control Chart 4 Identifying Similar Groups Planning and Management Cluster Analysis 3 Target Marketing, Customer Profiling Marketing Cluster Analysis 2 Sampling Inspection Quality Assurance Binomial Distribution 1 Specific Application Field Statistical Technique Sr No
Illustrative List of Statistical Techniques and their Applications Business Forecasting Banking Forecasting 10 Customer Profiling Marketing Discriminant Analysis 9 Credit Risk Analysis Finance Discriminant Analysis 8 Investments, Portfolio Selection, Mergers and Acquisitions Finance Decision Theory 7 Cross-Market Analysis Marketing Correlation and Regression Analysis 6 Specific Application Field Statistical Technique Sr No
Illustrative List of Statistical Techniques and their Applications Wholesale and Consumer Price Indices Economics Index Numbers 15 Demand Forecasting, Marketing Forecasting 14 Determining Premiums Insurance Forecasting 13 Manpower Planning HRD Forecasting 12 Pricing of Financial Products, Return on Investment Finance Forecasting 11 Specific Application Field Statistical Technique Sr No
Illustrative List of Statistical Techniques and their Applications Six Sigma Production Engineering Normal Distribution 21 Performance Appraisal HRD Normal Distribution 20 Yield Curve Finance Normal Distribution 19 Risk Management Finance Normal Distribution 18 EPS Equity Research Normal Distribution 17 Credit Risk Analysis Finance Logistic Regression 16 Specific Application Field Statistical Technique Sr No
Illustrative List of Statistical Techniques and their Applications Opinion/Exit Polls Election Sampling 28 Rankings with Multiple Criteria Rankings Rank Correlation 27 Rankings in Contests With Multiple Judges Rankings Rank Correlation 26 Formulating Compensation Strategies HR Percentiles 25 Relative Ranking Education Percentiles 24 PERT / CPM Project Management Normal Distribution 23 Statistical Quality Control Production Engineering Normal Distribution 22 Specific Application Field Statistical Technique Sr No
Illustrative List of Statistical Techniques and their Applications WACC (Weighted Average Cost of Capital) and EVA (Economic Value Added) Finance Weighted Average 34 Sensex, NIFTY, Wholesale Price and Consumer Price Indices Finance Weighted Average 33 Testing a Drug on Clinical Trial Paramedical- Pharmaceutical Testing of Hypothesis 32 Testing a Pesticide on Field Agriculture/Chemical Testing of Hypothesis 31 Inspection and Quality Control Production Engineering Sampling 30 Consumer Survey Market Research Sampling 29 Specific Application Field Statistical Technique Sr No
Illustrative List of Decision Situations and Corresponding Statistical Techniques Cluster Analysis Correlation and Regression Analysis Conjoint Analysis Identifying Customer Buying Behaviors and Patterns Retail Management Sample Surveys Conjoint Analysis Multidimensional Scaling Market Research Cluster Analysis Customer Profiling Time Series Correlation and Regression Analysis Statistical Inference Assessment/Forecast of Demand for the Product or a Service Marketing Statistical Techniques Applicable Decision Situation Area
Illustrative List of Decision Situations and Corresponding Statistical Techniques Probability. Time Series Regression Analysis Determining the Premium Insurance Discriminant Analysis Logistic Regression Correlation Analysis Assessing Credit Worthiness ‘  ’ Analysis and Regression Analysis Derivatives Regression Analysis Predicting EPS ‘  ’ Analysis Volatility of Stocks Regression Analysis, Decision Analysis Evaluation of Investment Finance and Banking Statistical Techniques Applicable Decision Situation Area
Illustrative List of Decision Situations and Corresponding Statistical Techniques Cluster Analysis Correlation Conjoint Analysis Identifying customer buying behaviors and patterns Retail Management Normal Distribution Percentiles Performance Appraisal and Reward System HRD ABC Analysis Inventory Management Statistical Quality Control Six Sigma Sampling Inspections Statistical Inference Controlling and Improving Production Process and Quality Operations Regression Analysis Discriminant Analysis Impact of Different Factors on Health and Life Statistical Techniques Applicable Decision Situation Area

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Module1

  • 1. Chapter 1 Introduction – Scope & Applications
  • 2. Definition of Statistics Historical Development Phases of a Statistical Study Scope and Limitations of Statistics Applications of Statistics in Marketing, Economics, Finance, Operations, Human Resource Development, Information Systems, Data Mining. Introduction – Scope & Applications
  • 3. Defining Objective(s) Specification of the Population and its Characteristic(s) Planning for Collection of Data - Census Vs Sampling Collection of Data Compilation/Presentation of Data Statistical Analysis Drawing Conclusions, Testing Assumptions or Making Predictions Phases of a Statistical Study
  • 4. Scope of Statistics Statistics increases the field of mental vision just as a binocular increases the field of physical vision Simplifies unwieldy and complex mass of data, and present them in a form and manner that they become intelligible. Conversion of data into information, makes it better suited for decision making
  • 5. Scope of Statistics Quantifies and measures uncertainty and variability, and thereby helps in decision making Discovers past and emerging patterns in a data. Using such analysis, it helps in forecasting. Sometimes, Statistics can even suggest possible reasons for such pattern. Helps in estimation and validating assumptions.
  • 6. Ways of manipulating the data Changing definition of a variable to suit preconceived notion Inadequate sample or unrepresentative sample selection Manipulative collection of data Interpretation of association and correlation Inappropriate comparison Defective data – definition confusing or not considering all possibilities
  • 7. Applications of Statistics in Various Areas Marketing Economics Finance Insurance Operations Human Resource Management or Development Information Systems Data Mining
  • 8. Illustrative List of Statistical Techniques and their Applications Hedging of Investments Financial Risk Correlation and Regression Analysis 5 Quality Control Production Engineering Control Chart 4 Identifying Similar Groups Planning and Management Cluster Analysis 3 Target Marketing, Customer Profiling Marketing Cluster Analysis 2 Sampling Inspection Quality Assurance Binomial Distribution 1 Specific Application Field Statistical Technique Sr No
  • 9. Illustrative List of Statistical Techniques and their Applications Business Forecasting Banking Forecasting 10 Customer Profiling Marketing Discriminant Analysis 9 Credit Risk Analysis Finance Discriminant Analysis 8 Investments, Portfolio Selection, Mergers and Acquisitions Finance Decision Theory 7 Cross-Market Analysis Marketing Correlation and Regression Analysis 6 Specific Application Field Statistical Technique Sr No
  • 10. Illustrative List of Statistical Techniques and their Applications Wholesale and Consumer Price Indices Economics Index Numbers 15 Demand Forecasting, Marketing Forecasting 14 Determining Premiums Insurance Forecasting 13 Manpower Planning HRD Forecasting 12 Pricing of Financial Products, Return on Investment Finance Forecasting 11 Specific Application Field Statistical Technique Sr No
  • 11. Illustrative List of Statistical Techniques and their Applications Six Sigma Production Engineering Normal Distribution 21 Performance Appraisal HRD Normal Distribution 20 Yield Curve Finance Normal Distribution 19 Risk Management Finance Normal Distribution 18 EPS Equity Research Normal Distribution 17 Credit Risk Analysis Finance Logistic Regression 16 Specific Application Field Statistical Technique Sr No
  • 12. Illustrative List of Statistical Techniques and their Applications Opinion/Exit Polls Election Sampling 28 Rankings with Multiple Criteria Rankings Rank Correlation 27 Rankings in Contests With Multiple Judges Rankings Rank Correlation 26 Formulating Compensation Strategies HR Percentiles 25 Relative Ranking Education Percentiles 24 PERT / CPM Project Management Normal Distribution 23 Statistical Quality Control Production Engineering Normal Distribution 22 Specific Application Field Statistical Technique Sr No
  • 13. Illustrative List of Statistical Techniques and their Applications WACC (Weighted Average Cost of Capital) and EVA (Economic Value Added) Finance Weighted Average 34 Sensex, NIFTY, Wholesale Price and Consumer Price Indices Finance Weighted Average 33 Testing a Drug on Clinical Trial Paramedical- Pharmaceutical Testing of Hypothesis 32 Testing a Pesticide on Field Agriculture/Chemical Testing of Hypothesis 31 Inspection and Quality Control Production Engineering Sampling 30 Consumer Survey Market Research Sampling 29 Specific Application Field Statistical Technique Sr No
  • 14. Illustrative List of Decision Situations and Corresponding Statistical Techniques Cluster Analysis Correlation and Regression Analysis Conjoint Analysis Identifying Customer Buying Behaviors and Patterns Retail Management Sample Surveys Conjoint Analysis Multidimensional Scaling Market Research Cluster Analysis Customer Profiling Time Series Correlation and Regression Analysis Statistical Inference Assessment/Forecast of Demand for the Product or a Service Marketing Statistical Techniques Applicable Decision Situation Area
  • 15. Illustrative List of Decision Situations and Corresponding Statistical Techniques Probability. Time Series Regression Analysis Determining the Premium Insurance Discriminant Analysis Logistic Regression Correlation Analysis Assessing Credit Worthiness ‘  ’ Analysis and Regression Analysis Derivatives Regression Analysis Predicting EPS ‘  ’ Analysis Volatility of Stocks Regression Analysis, Decision Analysis Evaluation of Investment Finance and Banking Statistical Techniques Applicable Decision Situation Area
  • 16. Illustrative List of Decision Situations and Corresponding Statistical Techniques Cluster Analysis Correlation Conjoint Analysis Identifying customer buying behaviors and patterns Retail Management Normal Distribution Percentiles Performance Appraisal and Reward System HRD ABC Analysis Inventory Management Statistical Quality Control Six Sigma Sampling Inspections Statistical Inference Controlling and Improving Production Process and Quality Operations Regression Analysis Discriminant Analysis Impact of Different Factors on Health and Life Statistical Techniques Applicable Decision Situation Area