This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.

This course is part of the Data Science Foundations: Statistical Inference Specialization

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Data Science Foundations: Statistical Inference SpecializationUniversity of Colorado Boulder

## About this Course

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Course 3 of 3 in the

Intermediate Level

Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R

Approx. 36 hours to complete

English

## What you will learn

## Define a composite hypothesis and the level of significance for a test with a composite null hypothesis.

## Define a test statistic, level of significance, and the rejection region for a hypothesis test. Give the form of a rejection region.

## Perform tests concerning a true population variance.

## Compute the sampling distributions for the sample mean and sample minimum of the exponential distribution.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 3 of 3 in the

Intermediate Level

Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R

Approx. 36 hours to complete

English

## Offered by

## Start working towards your Master's degree

This course is part of the 100% online Master of Science in Electrical Engineering from University of Colorado Boulder. If you are admitted to the full program, your courses count towards your degree learning.

## Syllabus - What you will learn from this course

**2 hours to complete**

### Start Here!

**2 hours to complete**

3 readings

**8 hours to complete**

### Fundamental Concepts of Hypothesis Testing

**8 hours to complete**

6 videos (Total 70 min), 11 readings, 2 quizzes

**8 hours to complete**

### Composite Tests, Power Functions, and P-Values

**8 hours to complete**

7 videos (Total 125 min), 7 readings, 2 quizzes

**8 hours to complete**

### t-Tests and Two-Sample Tests

**8 hours to complete**

7 videos (Total 140 min), 7 readings, 2 quizzes

**4 hours to complete**

### Beyond Normality

**4 hours to complete**

6 videos (Total 118 min), 6 readings, 2 quizzes

## Reviews

- 5 stars81.48%
- 4 stars14.81%
- 3 stars3.70%

### TOP REVIEWS FROM STATISTICAL INFERENCE AND HYPOTHESIS TESTING IN DATA SCIENCE APPLICATIONS

by GVJul 27, 2022

Loved the material. Content looks quite convincing and well explained!

by RKOct 26, 2022

In-depth course on Hypothesis testing. Course instructor is quite engaging.

## About the Data Science Foundations: Statistical Inference Specialization

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