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Probability Distribution and Decision Theory: Discrete and Continuous Random Variables,
Discrete Uniform, Binomial, Hypergeometric, Continuous Uniform, Normal, Lognormal, t and F
Distributions, Decision making under Conditions of Certainty and Uncertainty, Conditional
Profit/Loss Table, Expected Value of Perfect Information, Decision Trees.
Correlation: The Concept of Covariance and Correlation, Cause and Effect in Correlation, The
Scatter Diagram, Correlation analysis, Rank Correlation.
Simple Regression: Assumptions, Calculation of Regression Coefficients, Limitations, Testing
the Significance of the Model.
Multiple Regression: Regression with two Independent Variables, Computers and Multiple
Regression, Coefficient of Multiple Correlation, Coefficient of Multiple Determination, Testing
the Significance of the Model.
Time Series Analysis: Introduction, Variations in Time Series, Trend Analysis, Cyclical
Variation, Seasonal Variation, Irregular Variation, Time Series Analysis in Forecasting.
Index Numbers: Concept, Types, (Un) Weighted and Weighted Aggregates, Average of Relatives
Methods, Quantity and Value Indices.
Sampling: Population and Samples, Types of Sampling, Errors in Statistics, Central Limit
Theorem, Point Estimates, Interval Estimates, Standard Error, Estimating Population Means.
Testing of Hypothesis: Hypothesis testing for Means and Proportions, One Sample Test, Two
Sample Test, Runs Test.
Quality Control: Control Charts for Mean, Variability, Attributes, Chi-Square Test; Analysis of
Variance.

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