**Live, Learn, and Laugh**

## Teaching Assistant appointments (since Winter 2016)

### Current Courses

Institution | Session | Course Code | Course Name | Brief Description | Number of tutorials | Link to webpage |
---|---|---|---|---|---|---|

University of British Columbia | Winter 2021 | STAT540 | Statistical Methods for High Dimensional Biology | Exploration, visualization, and quality assessment of high dimensional genomics data Large scale statistical inference, Analysis of microarray, RNASeq, and epigenetics data, Principal component analysis (PCA), Cluster analysis, Cross validation, Model selection for classification and linear regression models, Gene function and gene set analysis, Resampling and the bootstrap | 1 | STAT540 |

University of British Columbia | Fall 2020 | STAT460/560 | (Graduate course) Statistical Inference I | Review of asymptotic theory and asymptotic inference, Multinomial distribution, Entropy and mutual information, Multivariate normal distribution, Least square estimation: Linear regression models, Maximum likelihood estimation (MLE), MLE for the parameters of the multivariate normal, Robust estimation of the parameters of the multivariate normal distribution, EM algorithm, Bayesian inference and MCMC | 1 | CANVAS |

#### Historical Courses

Institution | Session | Course Code | Course Name | Brief Description | Number of tutorials in total | Link to webpage |
---|---|---|---|---|---|---|

University of British Columbia | Winter 2020 | STAT300 | Intermediate Statistics for Applications | Further topics in statistical inference, including parametric and non-parametric methods, goodness-of-fit methods, analysis of variance and covariance, regression analysis, categorical data analysis, experimental designs, time series, model fitting, and statistical computing. | 1 | STAT300 |

Yale University | Spring 2019 | S&DS 100 | Introductory Statistics | Descriptive and inferential statistics applied to analysis of data from the social sciences. Introduction of concepts and skills for understanding and conducting quantitative research. | 1 | CANVAS SDS100 |

Yale University | Fall 2018 | S&DS 103 | Introductory Statistics | Descriptive and inferential statistics applied to analysis of data from the social sciences. Introduction of concepts and skills for understanding and conducting quantitative research. | --- | CANVAS |

University of Toronto, Scarborough | Winter 2018; Winter 2017 | MATB42 | Multivariable Calculus II | Fourier series. Vector fields in Rn, Divergence and curl, curves, parametric representation of curves, path and line integrals, surfaces, parametric representations of surfaces, surface integrals. Green's, Gauss', and Stokes' theorems will also be covered. An introduction to differential forms, total derivative. | 5 | MATB42 |

University of Toronto, Scarborough | Winter 2018 | STAB23 | Introduction to Statistics for Social Sciences | This course covers the basic concepts of statistics and the statistical methods most commonly used in the social sciences. The first half introduces descriptive statistics and the inferential statistical methods. The second half introduces bivariate and multivariate methods, emphasizing contingency table analysis and Chi-square test, regression, and analysis of variance. | 1 | STAB23 |

University of Toronto, Scarborough | Winter 2018, Fall 2016; Winter 2016 | STAB22 | Introduction to Statistics I | This course is a basic introduction to statistical reasoning and methodology, with a minimal amount of mathematics and calculation. The course covers descriptive statistics, populations, sampling, confidence intervals, tests of significance, correlation, regression and experimental design. | 4 | STAB22 |

University of Toronto, Scarborough | Winter 2017; Winter 2016 | MATA37 | Calculus II for Mathematical Science | A rigorous introduction to Integral Calculus of one variable and infinite series; strong emphasis on combining theory and applications; further developing of tools for mathematical analysis. Riemann Sum, definite integral, Fundamental Theorem of Calculus, techniques of integration, improper integrals, numerical integration, sequences and series, absolute and conditional convergence of series, convergence tests for series, Taylor polynomials and series, power series and applications. | 2 | Not available |

University of Toronto, Scarborough | Fall 2016 | MATB41 | Multivariable Calculus I | Partial derivatives, gradient, tangent plane, Jacobian matrix and chain rule, Taylor series; extremal problems, extremal problems with constraints and Lagrange multipliers, multiple integrals, spherical and cylindrical coordinates, law of transformation of variables. | 2 | Not available |

University of Toronto, Scarborough | Fall 2016 | STAB57 | (Honours) Introduction to Statistics | A mathematical treatment of the theory of statistics. The topics covered include: the statistical model, data collection, descriptive statistics, estimation, confidence intervals and P-values, likelihood inference methods, distribution-free methods, bootstrapping, Bayesian methods, relationship among variables, contingency tables, regression, ANOVA, logistic regression, applications. | 1 | Not available |

From below, you can see the responses from my former students who were enrolled in my tutorials at the University of Toronto.