This course equips students with the necessary background in statistical inference techniques that would allow them to correctly apply such topics in data analysis. The topics to be covered include: 1. Frequentist inference: point estimation, maximum likelihood estimation, properties of estimators (consistency, sufficiency, mean squared error, unbiasedness, fisher information, Cramer-Rao bound), confidence intervals, hypothesis testing; Neyman Pearson Lemma, likelihood ratio tests, uniformly most powerful tests. 2. Bayesian inference: bayes principle, prior and posterior probabilities, loss function, bayesian decision rules. 3. Predictive models: logistic regression, Bootstrap, Jackknifing, Cross validation.
Department of Mathematics and Statistics
Faculty of Science and Technology
Compulsory Fees: TTD 640.00
Tuition Fees: TTD 3769.00
- Pre-Requisites: None
- Course Credits: 3
- Assessment: TBA
- Mode: Face to Face
- Duration: Lectures: January 19 – April 10, 2026
- Lecture Time: TBA
For More Information, Contact: devika.bhagwandin@sta.uwi.edu