# 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.