Quantitative techniques are very powerful medium through which we solve uncertainty in decision making and enhance projectability and efficiency in the business. Therefore, these quantitative techniques evaluate planning factors and when these arise then provide meaningful solution to particular business problem
Objective: The objective of this course is to familiarize the students with more advanced tools of data analysis and forecasting and also to have an understanding of the fundamentals of theory of probability
Module – I
Bi-Variate Data Analysis- I- Correlation – Concept- Correlation and Causation -Types of Correlation-Methods- Scatter diagram and Correlation graph- -Karl Pearson’s Co-efficient of Correlation-Spearman’s Rank Correlation Co-efficient- – Probable Error-Concurrent Deviation Method- Concept of lag and lead in correlation (Problems- Un grouped Data only)
Bi-Variate Data Analysis- II -Regression Analysis– Concept-Utility- Comparison of correlation and regression- Lines of Regression- – Regression Equations and regression co-efficient- Algebraic Methods of studying regression- Standard Error of estimate – (Problems- Un grouped Data only)
Module – III
Index Numbers-Meaning-Importance- Characteristics and uses of Index Numbers- Types of index numbers- Problems in construction of index numbers- Methods of constructing price index, quantity index and value index- : Unweighted Index numbers- Simple aggregative method and Simple average of price relatives method- Weighted Index numbers- Weighted average of price relative method- Weighted aggregative method applying Laspeyer’s, Paasche’s and Fishers methods- Test of Consistency of index numbers- Cost of Living Index Numbers and its Uses- Construction of cost of living index numbers-Aggregate expenditure method and family budget method- Concepts of Fixed base index numbers, chain based index numbers, base shifting, deflating and splicing(theory only)- Limitations of index numbers
Module – IV
Time Series Analysis-Meaning-Definition- Components of Time Series-Time series analysis- Utility of Time Series Analysis- Mathematical models- Determination of Trend- Free hand curve method- Method of semi averages- Method of Moving Average-Method of Least Squares (first degree only)- Shifting the origin of trend- converting annual trend into monthly trend
Module – V
Probability-Meaning-Definition – Basic Terms-Concepts-Approaches to Assigning Probability – Permutation and Combination-Theorems of Probability- Addition Theorem- Multiplication Theorem-Conditional Probability- Baye’s Theorem of Inverse probability
1. Richard, Levin & Rubin, David, S., Statistics for Management, Prentice Hall of India, New Delhi.
2. Spiegel, M.R., Theory and Problems of Statistics, Schaum’s Outlines Series, McGraw Hill Publishing Co.
3. Kothari, C.R., Research Methodology, New Age Publications, New Delhi.
4. Sharma, J. K., Business Statistics, Pearson Education.
5. Gupta, S.C., Fundamentals of Statistics, Himalaya Publishing House.
6. Gupta, S.P. & Gupta, Archana, Elementary Statistics, Sultan Chand and Sons, New Delhi.
7. Elhance D N, Elhance,Veena and Aggarwal B M Fundamentals of Statistics , Kitab Mahal
8. Gupta, C B and Gupta, Vijay., An Introduction to Statistical Methods, Vikas Publishing House
9. Pillai , R S N and Bagavathi,V ., Statistics , S Chand & Co
Module – I Bi-Variate Data Analysis- I
Module II Bi-Variate Data Analysis- II