About this Course

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Shareable Certificate
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100% online
Start instantly and learn at your own schedule.
Intermediate Level

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

Approx. 34 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.
Intermediate Level

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

Approx. 34 hours to complete
English

Offered by

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University of Colorado Boulder

Start working towards your Master's degree

This course is part of the 100% online Master of Science in Data Science 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

Week
1

Week 1

8 hours to complete

Fundamental Concepts of Hypothesis Testing

8 hours to complete
6 videos (Total 70 min), 5 readings, 2 quizzes
Week
2

Week 2

8 hours to complete

Composite Tests, Power Functions, and P-Values

8 hours to complete
7 videos (Total 125 min), 7 readings, 2 quizzes
Week
3

Week 3

8 hours to complete

t-Tests and Two-Sample Tests

8 hours to complete
7 videos (Total 140 min), 7 readings, 2 quizzes
Week
4

Week 4

4 hours to complete

Beyond Normality

4 hours to complete
6 videos (Total 118 min), 6 readings, 2 quizzes

About the Data Science Foundations: Statistical Inference Specialization

Data Science Foundations: Statistical Inference

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