Topic outline

  • General

  • M-01. Introduction to Quantitative Techniques

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  • M-02. Introduction, Significance, Scope and Limitations of Statistics

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  • M-03. Data Classification and Tabulation

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  • M-04. Data Presentations: Graphs and Diagrams

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  • M-05. Measures of Central Tendency: Mathematical Averages (AM, GM, HM)

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  • M-06. Measures of Central Tendency: Averages of Positions (Median, Mode, Quartile, Deciles, Percentile)

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  • M-07. Measures of Dispersion: Mean Absolute Deviation, Standard Deviation, Variance, Coefficient of Variation

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  • M-08. Measures of Dispersion: Skewness and Kurtosis

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  • M-09. Probability: Concept and Enumeration

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  • M-10. Probability: Conditional Probability, Bayes’ Theorem

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  • M-11. Discrete Probability Distributions: Random variables, Expected Value and Variance

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  • M-12. Discrete Probability Distributions: Binomial Distribution

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  • M-13. Discrete Probability Distributions: Poisson Distribution

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  • M-14. Continuous Distributions- Normal Distribution: Normal Curve

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  • M-15. Continuous Distributions- Normal Distribution: Standard Normal Probability Distribution

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  • M-16. Sampling and Sampling Distributions: Random Sampling, non-random sampling,

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  • M-17. Sampling and Sampling Distributions: Sampling Distribution of x Bar

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  • M-18. Sampling and Sampling Distributions: Determining Sample Size

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  • M-19. Estimation: Point Estimation, Interval Estimation, Population mean-(known or unknown)

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  • M-20. Hypothesis Testing: Developing Null and Alternate Hypothesis

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  • M-21. Hypothesis Testing: Type-I and Type-II error; One-tail and two tail tests with σ - known and un-known

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  • M-22. Hypothesis Testing and Decision Making

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  • M-23. Statistical Inference with two populations: Hypothesis Techniques-two sample tests: σ1 and σ2 (known and un-known

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  • M-24. Test of Goodness of Fit and Independence: Chi-Square-test-as a test of independence

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  • M-25. Test of Goodness of Fit and Independence: Chi-Square-test- as a test of Goodness of Fit

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  • M-26. Analysis of Variance and Experimental Design: testing for equality of k population means

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  • M-27. Analysis of Variance and Experimental Design: One –Way ANOVA

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  • M-28. Analysis of Variance and Experimental Design: two –Way ANOVA

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  • M-29. Analysis of Variance and Experimental Design: An Introduction to Experimental, Randomized and Block Design

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  • M-30. Analysis of Variance and Experimental Design: Conclusion

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  • M-31. Linear Regression: Simple Linear Regression Model with Least Square Method

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  • M-32. Correlation: Karl Pearson’s Coefficient of Correlation, Spearman Rank Correlation

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  • M-33. Correlation: Coefficient of Determination and Testing for Significance

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  • M-34. Multiple Regression Model

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  • M-35. Regression Analysis-An Introduction to Model Building

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  • M-36. Forecasting & Time series Analysis: Forecasting Methods, Time Series Analysis

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  • M-37. Forecasting & Time series Analysis: Measuring- Seasonal Effect, Cyclical Effect, and Measuring Irregular Effect

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  • M-38. Fundamental of Decision Theory: Decision making under uncertainty, certainty and risk

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  • M-39. Decision Analysis with Probabilities: Expected Value Approach

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  • M-40. Decision Trees, Analytical Approach to Decision Problems

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