Basic Information
The Statistical Inference Problem. Background in Probability. Statistical Models and Sufficient Statistics. Point Estimation, The Method-of-moments, Maximum Likelihood and Error Bounds. Confidence Intervals and The Bootstrap. Hypothesis Testing With a Pair And Multiple Hypotheses. Nonparametric Hypothesis Testing, Goodness-of-fit and Testing For Independence. Linear Regression And Lasso. Learning Outcomes# The Students Will Be Familiar With The Fundamental Problems Of Statistical Inference, and Their Theoretical Analysis.the Students Will Be Able to Rigorusly Plan a Statistical Inference Method For Engineering Problems and Understand Their Limitations. The Student Will Obtain Necessary Background to Advanced Courses and Research In Statistics, Data-science and Machine Learning.
Faculty: Electrical and Computer Engineering
|Undergraduate Studies
|Graduate Studies
Pre-required courses
94411 - Probability (ie) or 94412 - Probability (advanced) or 104034 - Introduction to Probability H or 104222 - Probability Theory
Course with no extra credit
98414 - Theory of Statistics 106434 - Mathematical Statistics
Course with no extra credit (contained)
94423 - Introduction to Statistics 94424 - Statistics 1 94481 - Int.to Probability and Statistics 334023 - Int. to Statistics For Biomedical Eng.