V Mandrekar (Instructor) - Grade Details
(with breakdown by course)
V Mandrekar - All Courses
Average Grade - 3.467
Median Grade - 3.5
Latest grades from Fall 2019
V Mandrekar - Overview
| Course Number | Grade Info | Number of Students | Latest Grade Data | Breakdown |
|---|---|---|---|---|
| STT 881 | Average Grade - 3.719 Median Grade - 4.0 |
19 | Fall 2014 | |
| STT 861 | Average Grade - 3.864 Median Grade - 4.0 |
33 | Fall 2015 | |
| STT 351 | Average Grade - 3.446 Median Grade - 3.5 |
833 | Fall 2019 | |
| STT 961 | Average Grade - 3.833 Median Grade - 4.0 |
12 | Fall 2017 | |
| STT 882 | Average Grade - 3.625 Median Grade - 4.0 |
16 | Spring 2015 | |
| STT 862 | Average Grade - 3.182 Median Grade - 3.5 |
22 | Spring 2016 |
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STT 351 - Probability and Statistics for Engineering
Probability models and random variables. Estimation, confidence intervals, tests of hypotheses, simple linear regression. Applications to engineering.
Average Grade - 3.446
Median Grade - 3.5
Latest grades from Fall 2019
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STT 861 - Theory of Probability and Statistics I
Probability models, random variables and vectors. Special distributions including exponential family. Expected values, covariance matrices, moment generating functions. Convergence in probability and distribution. Weak Law of Large Numbers and Lyapunov Central Limit Theorem.
Average Grade - 3.864
Median Grade - 4.0
Latest grades from Fall 2015
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STT 862 - Theory of Probability and Statistics II
Statistical inference: sufficiency, estimation, confidence intervals and testing of hypotheses. One and two sample nonparametric tests. Linear models and Gauss-Markov Theorem.
Average Grade - 3.182
Median Grade - 3.5
Latest grades from Spring 2016
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STT 881 - Theory of Probability I
Measures and their extensions, integration. Lp spaces and Inequalities. Lebesgue decomposition, the Radon-Nikodym theorem. Product measures, Fubini's theorem. Kolmogorov consistency theorem. Independence, Kolmogorov's zero-one law, the Borel-Cantelli lemma. Law of large numbers. Central limit theorems, characteristic functions, the Lindeberg-Feller theorem, asymptotic normality of sample median. Poisson convergence. Conditional expectations.
Average Grade - 3.719
Median Grade - 4.0
Latest grades from Fall 2014
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STT 882 - Theory of Probability II
Random walks, transcience and recurrence. Martingales, martingale convergence theorem, Doob's inequality, optional stopping theorem. Stationary processes and Ergodic theorem. Brownian motion. Kolmogorov's continuity theorem, strong Markov property, the reflection principle, martingales related to Brownian motion. Weak convergence in C([0,1]) and D([0,1]), Donsker's invariance principle, empirical processes.
Average Grade - 3.625
Median Grade - 4.0
Latest grades from Spring 2015
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STT 961 - Weak Convergence and Asymptotic Theory
Maximal inequalities, covering numbers, symmetrization technique, Glivenko-Cantelli Theorems, Donsker Theorems and some results for Gaussian processes, Vapnik-Chervonenkis classes of sets and functions, applications to M-estimators, bootstrap, delta-method
Average Grade - 3.833
Median Grade - 4.0
Latest grades from Fall 2017
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