MTL390: Difference between revisions
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| credits = 4 | | credits = 4 | ||
| credit_structure = 3-1-0 | | credit_structure = 3-1-0 | ||
| pre_requisites = MTL106 | | pre_requisites = [[MTL106]] | ||
| overlaps = MTL108 | | overlaps = [[MTL108]] | ||
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== MTL390 : Statistical Methods == | == MTL390 : Statistical Methods == | ||
Basic concepts and Data Visualization: Measures of central tendency, Dispersion, Skewness, Kurtosis, Data Representation using Histogram, Pie Chart, Boxplot, Biplot, Multi Dimensional Scaling etc. Revision of Probability Distribution: Emphasis on Normal, Chi-Square, Student's T, F distributions; Order Statistics: Different Order Statistics and their single and joint Distribution; Sampling Distribution of Mean, Variance; Generation of Random Numbers following certain distributions; Theory of Estimation (Point and Interval)Properties of an estimator, MVUE, BLUE, Cramer-Rao Inequality, Rao-Blackwell Theorem; Testing of Hypothesis: Mean and Variance, Confidence Interval, Neyman-Pearson Lemma; Non-Parametric Methods Run Tests, Rank Tests, Signed Rank Tests, Kruskal Wallis Test, Kolmogorov-Smirnov Test etc.; Regression Analysis Linear Regression, Multiple Regression, Logit, Probit, Regression. | Basic concepts and Data Visualization: Measures of central tendency, Dispersion, Skewness, Kurtosis, Data Representation using Histogram, Pie Chart, Boxplot, Biplot, Multi Dimensional Scaling etc. Revision of Probability Distribution: Emphasis on Normal, Chi-Square, Student's T, F distributions; Order Statistics: Different Order Statistics and their single and joint Distribution; Sampling Distribution of Mean, Variance; Generation of Random Numbers following certain distributions; Theory of Estimation (Point and Interval)Properties of an estimator, MVUE, BLUE, Cramer-Rao Inequality, Rao-Blackwell Theorem; Testing of Hypothesis: Mean and Variance, Confidence Interval, Neyman-Pearson Lemma; Non-Parametric Methods Run Tests, Rank Tests, Signed Rank Tests, Kruskal Wallis Test, Kolmogorov-Smirnov Test etc.; Regression Analysis Linear Regression, Multiple Regression, Logit, Probit, Regression. | ||
Latest revision as of 16:42, 14 April 2026
| MTL390 | |
|---|---|
| Statistical Methods | |
| Credits | 4 |
| Structure | 3-1-0 |
| Pre-requisites | MTL106 |
| Overlaps | MTL108 |
MTL390 : Statistical Methods
Basic concepts and Data Visualization: Measures of central tendency, Dispersion, Skewness, Kurtosis, Data Representation using Histogram, Pie Chart, Boxplot, Biplot, Multi Dimensional Scaling etc. Revision of Probability Distribution: Emphasis on Normal, Chi-Square, Student's T, F distributions; Order Statistics: Different Order Statistics and their single and joint Distribution; Sampling Distribution of Mean, Variance; Generation of Random Numbers following certain distributions; Theory of Estimation (Point and Interval)Properties of an estimator, MVUE, BLUE, Cramer-Rao Inequality, Rao-Blackwell Theorem; Testing of Hypothesis: Mean and Variance, Confidence Interval, Neyman-Pearson Lemma; Non-Parametric Methods Run Tests, Rank Tests, Signed Rank Tests, Kruskal Wallis Test, Kolmogorov-Smirnov Test etc.; Regression Analysis Linear Regression, Multiple Regression, Logit, Probit, Regression.