Dropped this course, taking it again next fall probably
Notes
- A course taught by Shahriar Shams
- sharir.shams@utoronto.ca
- Textbooks:
- Mathematical statistics and data analytics
- Probability and statistics - the science of uncertainty
- Homework is not for credit
- Quizzes start week 3 - write atleast 5/10 quizzes
- Tutorials start week 2
- Two assignments worth 10% each, first released mid-feb, second released mid-march
- Students are forced to submit doctors note after missing midterm, it just automatically rolls over
- Quizzes are open book - can use laptop, but don’t email people
- Final/midterm potential questions
Concepts
Week 1
- R
- Probability
- Expectation
- Variance
- Covariance
- Indicator RV
- Indicator Function for Branchless Piecewise Functions
- WLLN
- CLT
- MGF
- Linear Combination of Normal Variables
- Exponential Theta Distribution
- Gamma Theta Distribution
- Beta Distribution
- Synthetic Distribution
- t Distribution
- F Distribution
Week 2
- Population
- Sample
- Parameter
- Statistic
- Estimator
- Statistical Inference
- Population Moment
- Sample Moment
- MME
- MLE
- Parameter Space
- Sigma Algebra
- Sampling Distribution
Week 3
- Mean Squared Error
- Bias
- Bias-Variance Tradeoff
- Unbiasedness
- Population Variance
- Unbiasedness Identity
- Sample Variance Well Known Theorem
- E&R Theorem
- Sample Mean Independent of Population Variance
- Chi Squared Variance Independent Distribution
- Covariance Does Not Imply Independence