Here you can find lecture slides on Multiple regression. In this chapter you can learn how to best handle multiple covariates and the meaning of p-values and hypothesis testing in the context of regression (applied regression).
Regression – Intuition
Here you can find slides on Linear Regression chp6 There you can find how to Fit linear models Treat discrete/qualitative covariates Check validity of the model
Case Study 4 – Calibrating Snow Gauge
Lecture Slides for the Case Study 4 / Homework 4 can be found here chp5 This study allows us to revisit/renew Regression modeling Properties of Least Squares/Fitting “a line” Multiple observation Datasets for this study are The main file: gauge Supplementary large-scale files: http://iabp.apl.washington.edu/data.html as well as http://nsidc.org/data/G00791
Reading on Computational Statistics
If you are interested in reading more about bootstrap and cross-validation I find this pdf file a good starting point http://stat.ethz.ch/education/semesters/ss2012/CompStat/sk.pdf : Chapters 4 and 5 If you’d like to learn more about monte carlo, i.e., simulations http://statweb.stanford.edu/~owen/mc/Ch-intro.pdf https://cse.sc.edu/~terejanu/files/tutorialMC.pdf
HOMEWORK 2 DUE DATE (updated)
Please note that the Homework 2 is now due on Saturday (instead of previously announced Thursday), February 16th by 11:59pm. The best way to submit your homework is through GRADESCOPE, one submission per team that includes two attachments – PDF file of your report and R code (or other code files) of your implementation. Please […]