IE605: Engineering Statistics, Aug-Nov 2020The course provides a strong foundation in theory and methods of modeling randomness and data analysis in engineering applications. Lecture HoursMonday 8.30-9.30amTuesday 9.30-10.30am Thursday 10.30am-11.30am LocationOnline via MS TeamsTeaching AssistantsArun VermaFehmina Malik Debamita Ghosh Sayan Chatterjee Harshit Pandey TA HoursTimings: Every Monday 2-4pmVenue : Virtual meetings on request SyllabusReview of calculus-based probability concepts, common distributions, expectation, moment generating functions Sampling statistics, order statistics, properties of sample mean, Central Limit Theorem. Sampling from a Normal distribution Parameter estimation, maximum likelihood estimators, interval estimates; bias, efficiency and consistency of point estimators Sampling plans, sequential tests, Hypothesis testing, common tests concerning means, variances Goodness-of-fit, likelihood ratio test, Neyman-Pearson lemma; Regression models, design of experiments. Course Grades (to revise)25 points: Midterm40 points: 4 Assingments 35 points: Endterm Reference textsTutorials |