Pingshou Zhong (Instructor) - Grade Details
(with breakdown by course)
Pingshou Zhong - All Courses
Average Grade - 3.340
Median Grade - 3.5
Latest grades from Spring 2018
Pingshou Zhong - Overview
| Course Number | Grade Info | Number of Students | Latest Grade Data | Breakdown | ||
|---|---|---|---|---|---|---|
| STT 861 | Average Grade - 3.549 Median Grade - 3.5 |
123 | Fall 2013 | |||
| STT 441 | Average Grade - 2.977 Median Grade - 3.5 |
171 | Spring 2015 | |||
| STT 867 | Average Grade - 3.586 Median Grade - 3.5 |
29 | Fall 2016 | |||
| STT 862 | Average Grade - 3.667 Median Grade - 4.0 |
33 | Spring 2012 | |||
| STT 864 | Average Grade - 3.512 Median Grade - 3.5 |
124 | Spring 2018 | |||
| STT 421 | Average Grade - 3.159 Median Grade - 3.0 |
41 | Spring 2017 | |||
| STT 843 | Average Grade - 3.462 Median Grade - 3.5 |
39 | Spring 2018 | |||
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STT 421 - Statistics I
Basic probability, random variables, and common distributions. Estimation and tests for one-, two-, and paired sample problems. Introduction to simple linear regression and correlation, one-way ANOVA.
Average Grade - 3.159
Median Grade - 3.0
Latest grades from Spring 2017
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STT 441 - Probability and Statistics I: Probability
Probability, conditional probability and independence. Random variables. Discrete, continuous, univariate, and multivariate distributions. Expectation and its properties, moment generating functions. Law of large numbers, central limit theorem.
Average Grade - 2.977
Median Grade - 3.5
Latest grades from Spring 2015
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STT 843 - Multivariate Analysis
Multivariate normal distribution, tests of hypotheses on means, multivariate analysis of variance. Discriminant analysis. Principal components. Factor analysis. Analysis of frequency data.
Average Grade - 3.462
Median Grade - 3.5
Latest grades from Spring 2018
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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 - 3.549
Median Grade - 3.5
Latest grades from Fall 2013
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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 - 3.667
Median Grade - 4.0
Latest grades from Spring 2012
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STT 864 - Statistical Methods II
Generalized linear models(GLMs). Deviance and residual analysis in GLMs. Analysis of two-way and three-way contingency tables. Logistic regression. Log-linear models. Multicategorical response models. Poisson regression. Introduction to generalized estimating equations. Introduction to longitudinal data. Bayesian analysis using WinBUGS.
Average Grade - 3.512
Median Grade - 3.5
Latest grades from Spring 2018
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STT 867 - Linear Model Methodology
Properties of the multivariate normal distribution, Cochran's Theorem, simple and multiple linear regression models, Gauss-Markov Theorem, best linear unbiased prediction, one- and two-way ANOVA models, sums of squares, diagnostics and model selection, contingency tables and multinomial models, generalized linear models, logistic regression.
Average Grade - 3.586
Median Grade - 3.5
Latest grades from Fall 2016
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