Hands-On Data Science with Anaconda

Review questions and exercises

1. What is the definition of a single-factor linear model?
2. How many independent variables are there in a single-factor model?
3. What does it mean for something to be statically different from zero?
4. What are the critical T-values and P-values to tell whether an estimate is statistically significant?
5. When the significant level is 1%, what is the critical T-value when there are 30 degrees of freedom?

6. What is the difference between a one-sided test and a two-sided test?
7. What are the corresponding missing codes for missing data items in R, Python, and Julia?
8. How do we treat missing variables if our sample is big? How about if our sample is small?
9. How do we generally detect outliners and deal with them?
10. How do we ...