ORF 245: Statistics
Lectures Based on
Mathematical Statistics and Data Analysis (by John A. Rice)
- Mon, Sept 22, 2014: pp 54-64, Sec. 3.1-3.3
- Fri, Sept 19, 2014: pp 47-54
- Wed, Sept 17, 2014: pp 35-47
- Mon, Sept 15, 2014: pp 1-40
- Basics of probability including the definition of a sample space and
probabilities of events defined on the sample space.
- Indepedent events.
- Random variables cumulative distribution function, and density function.
- The most common/important discrete and continuous random variables.
- Independent random variables.
- Joint distribution, marginal and conditional distributions.
- Bayesian Inference.
- Expectation, mean, and variance.
- Collections of independent identically distributed random variables.
- Sample mean and sample variance.
- Central Limit Theorem.
- Confidence intervals for the mean.
- Method of Moments (MoM) and Maximum Likelihood Estimators (MLE).
- Confidence intervals based on t-distribution.
- Hypothesis Testing.
- Linear Regression.
Throughout the course, we will use the computer language Matlab to perform
computations on real-world data to illustrate the methods and ideas covered
in the course. The data sets will span from historical stock market prices
to temperature data needed to study climate change.
- Homeworks due every Friday, 5:00pm. 10% off for each day
(or part of a day) thereafter.
- At the end of the semester, the lowest homework grade will be dropped
- Two midterms (Friday of the 5th and 10th weeks).
- Final grade based on:
- Precepts: 3:30-4:20pm and 7:30-8:20pm on Mondays and Tuesdays.
- Office Hours:
|2:00pm to 3:30pm, Sherrerd 218.|
|11:00am to 12:30pm, Sherrerd 324.|
|2:30pm to 4:00pm, Sherrerd 219.|
|10:00am to 11:30 am, Sherrerd 002. |
|3:00pm to 4:30pm, Sherrerd 220.|
|1:30pm to 3:00pm, Sherrerd 209.|