STA302H1 Lecture Notes - Lecture 1: Regression Analysis, Matrix Multiplication, Model Selection
Document Summary
Sta302 / 1001 hf - methods of data analysis i. The main objectives of this course are to gain a solid understanding of the theory and application of linear regression analysis and practical skills for developing linear regression models for inference, prediction and interpreting the results. Extensive use of r language to analyze data and use rmarkdown for homework solution. Students should have a second year statistics course such as sta 248h1 / sta 255h1 / sta 261h1 / eco. Students are expected to also have the mathematics pre- and co-requisites required by students in these second-year statistics courses. You will need to know basic matrix operations. A short but good review of matrix algebra is available on the website at https://onlinecourses. science. psu. edu/statprogram/matrix_review: sections l0101/l2001. Tuesday 10:10-12:00 in ms2158 (no lecture on tuesday, november 8 (fall break)) Thursday 10:10-11:00 in oi-g162. (class on thursday, october 27 will take place in es1050: section l5101: thursday 17:10-20:00 in pb-b150.
