This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.

Statistical Inference is course 6 of 10 in the Data Science Specialization.

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.

### Syllabus

**WEEK 1**

Probability & Expected Values

This week, we'll focus on the fundamentals including probability, random variables, expectations and more.

Graded: Quiz 1

**WEEK 2**

Variability, Distribution, & Asymptotics

We're going to tackle variability, distributions, limits, and confidence intervals.

Graded: Quiz 2

**WEEK 3**

Intervals, Testing, & Pvalues

We will be taking a look at intervals, testing, and pvalues in this lesson.

Graded: Quiz 3

**WEEK 4**

Power, Bootstrapping, & Permutation Tests

We will begin looking into power, bootstrapping, and permutation tests.

Graded: Quiz 4

Graded: Statistical Inference Course Project - Peer Review