What Does STA302(Data Analysis I) And STA303 (Data Analysis II) Teach Me
STA302 is a compulsory course that everyone in the statistics major must learn. His existence is indeed a certain degree of difficulty.
My professor at the time was Dr. Shivon Sue-Chee. The epidemic had not yet started when I took this course. When I felt her classroom offline, I thought she was a very responsible and friendly teacher because she was always Will try her best to answer my questions and especially welcome everyone to ask questions. At the same time, her syllabus is well planned, and the homework is related to the exam, which makes all students’ study burden a lot lighter because everyone finds that the assignment’s knowledge points will be about the same. Hence, her exams are not complicated but very practical.
STA302 provides a solid introduction to data analysis and is an introductory course. This course focuses on the theory and application of linear regression. Topics to be covered include initial examination of data, correlation, simple and multiple regression models using least squares, the geometry of least squares, inference for regression parameters for normally distributed errors, confidence and prediction intervals, model diagnostics, and remedial measures when the model assumptions are violated, interactions and dummy variables, ANOVA, model selection, and penalized regression.
Other topics include non-linear regression and non-parametric data smoothing techniques. Emphasis will be on methodology and interpretation of the results of data analysis. (syllabus of STA302H1S Autumn 2019) Simultaneously, to develop our students’ applied functions, this course also Taught R software and Rmarkdown to develop data analysis skills.
In general, this course’s primary learning goal is to have an in-depth understanding of linear regression and learn the practical skills to develop linear regression models for reasoning and prediction and interpret the results.
This course is a threshold course for students majoring in statistics. The subsequent courses will have some difficulty learning if this course can’t be well down because this course is one of the foundations of introductory statistics. But if you learn this course very solidly, it will be of great help to the subsequent periods and lay a solid foundation for future work applications.
Rating: ✮✮✮✮☆
STA303
The professor of this course is Prof. Liza Bolton. She seems to be teaching ST303 for the first year, and she designed this course very organized. The tight learning tasks every week make it impossible for students to stop learning STA303. This kind of teaching method is very suitable for temporary students. For students of the Buddha-legged type, the weekly pre-class quiz can help everyone complete most of this course content and then consolidate their knowledge through the classroom. This is actually worth learning by all professors during the online class.
STA303 is the upgrade course of STA302 because many problems that cannot be solved in STA302 will be solved by learning new models in STA303. The course is a mixture of theory and application. Simultaneously, we have many assignments that use R for coding and then connect to the exam. The final task is a large group project that requires everyone to cooperate to complete. From many assignments, I found that Prof. Liza Bolton believes that what a statistician needs most is not to analyze the data but to have the ability to communicate with people. After all, if we can’t simplify our analysis results to ordinary people, If you listen, our analysis is useless.
All in all, if Prof. Liza Bolton teaches this course, then I highly recommend you to take it.
Rating: ✮✮✮✮✮
