100% Plagiarism-Free
+1-727-416-5453

Sign In

Access your dashboard and order activity.

Forgot password?

Create Account

Register to place orders and track every step.

EN.553.730

Statistical Theory I

Johns Hopkins University 4 credits Applied Mathematics & Statistics

Course Description

The fundamentals of mathematical statistics will be covered. Topics include: distribution theory for statistics of normal samples, exponential statistical models, the sufficiency principle, least squares estimation, maximum likelihood estimation, uniform minimum variance unbiased estimation, hypothesis testing, the Neyman-Pearson lemma, likelihood ratio procedures, the general linear model, the Gauss-Markov theorem, simultaneous inference, decision theory, Bayes and minimax procedures, chi-square methods, goodness-of-fit tests, and nonparametric and robust methods. Prerequisite(s): Students may take EN.550.630 or EN.553.730, but not both.

Code
EN.553.730
Credits
4
Subject
Applied Mathematics & Statistics

Programs That Include This Course

Get expert help with EN.553.730 Statistical Theory I

Our subject experts help with essays, research papers, case studies, discussion posts, and capstone projects for these programs β€” written from scratch to your course requirements.

Get Help Now

Program and course information is reproduced from each university's published academic catalog for informational purposes and may change. Always confirm current requirements with your university. We are an independent academic support service and are not affiliated with or endorsed by the universities listed.

Academic Resources

Latest from the Blog

Expert guides on essay writing, citation styles, study skills, and academic success.

View All Articles