30204 Statistical Inference 1

Credits: 4 intermediate credits in Mathematics

Prerequisites: none

Required: One of the following: Introduction to Statistics and Probability for Science Students, Probability for Computer Science Students

Authors: Shmuel Zamir, Ruth Beyth-Marom, Gad Nathan, Moshe Pollack

A continuation of Introduction to Statistics and Probability for Science Students (30203), this course presents methods in statistical research and its applications. Understanding these topics requires familiarity with probability theory and data description methods.

Topics: Sampling the law of large numbers, the central limit theorem; Estimation and confidence intervals; Hypothesis testing; Nonparametric tests and Bayesian inference; Correlation; Regression; Analysis of variance (one-way and multivariable).

1There is some overlap in the content of this and other courses. For details, see Overlapping Courses.