Quantitative Analysis For Business Decisions

Syllabus

DSC-204-  Quantitative Analysis for Business Decisions

Unit – I: Statistics                                                                                            12 Hours

Definitions – Statistical Methods – Importance and Scope – Limitations – Need for Data – Principals of Measurement. Tabulation and Presentation:

Classification of Data – Data Array – Frequency Distribution – Methods of data Classification – Types of Frequency Distributions / Tabulation of Data – Objectives of Tabulation – Parts and Types of Tables – Graphical Presentation – Functions of Graphs – Advantages and Limitations of Graphs.

Unit – II: Measures of Central Tendency                                                 12 Hours

Introduction to Averages – Requisites for a Measure of Central Tendency, Mean - Combined Mean – Weighted Mean, Median – Partition Values – Quartiles, Deciles and Percentiles, Relationship between Partition Values–Mode– Relationship between Mean, Median and Mode.

Unit – III: Measures of Dispersion                                                             12 Hours

Introduction – Significance and Requisites of a Measure of Dispersion, Range, QD, MD and SD- For Grouped and Ungrouped – Advantages and Disadvantages. Concept of Variation – Coefficient of Variation. Skewness and Kurtosis (SK): Introduction, Measures of SK, Relative Measures of SK – Advantages and Disadvantages. Moments – concepts –Calculation – Kurtosis.

Unit – IV: Index Numbers                                                                             12 Hours

Index Numbers - Introduction – Types – Characteristics – Construction Weighted and Unweighted Index Numbers – Price and Quantity/Volume Index Numbers – Tests – Time Reversal – Factor Reversal and Circular Tests – Chain and Fixed Base – Changing of Base – Combining of Two of More Overlapping Indices Consumer Price Index – Problems in Construction.

Unit – V: Correlation Analysis                                                                    12 Hours

Scatter Diagram, Positive and Negative Correlation, Limits for Coefficient of Correlation, Karl Pearson’s Coefficient of Correlation, Spearman’s Rank Correlation.

Regression Analysis: Concept, Least Square Fit of a Linear Regression, Two Lines of Regression, Properties of Regression Coefficients (Simple Problems Only)

Time Series Analysis: Components, Models of Time Series – Additive, Multiplicative and Mixed Models; Trend Analysis- Free Hand Curve, Semi Averages, Moving Averages, Least Square Methods(Simple Problems only).