Learn the Normal or Gaussian distribution in statistics

Master the Normal Distribution with this comprehensive course featuring clear lectures and hands-on problem-solving for real-world applications in statistics and analytics.

  • Overview
  • Curriculum
  • Instructor
  • Review

Brief Summary

This course dives into the Normal Distribution, a key concept in statistics. Through easy lectures and hands-on problems, you’ll learn how to use standard tables and solve real-world issues related to this important distribution.

Key Points

  • Understanding the Normal Distribution
  • Importance in statistics and real-world applications
  • Use of standard normal tables with z values
  • Problem-solving and quizzes for reinforcement
  • Final test to assess understanding

Learning Outcomes

  • Fully use the standard normal table.
  • Find z values for different percentiles.
  • Solve real-world problems involving the Normal distribution.
  • Reinforce learning through quizzes.
  • Understand applications in various fields like psychology and business.

About This Course

Learn through clear lectures and hands-on solved problems how to fully understand the Normal Distribution.

This course is about the Normal distribution, the most important distribution in statistics. Since the Normal or Gaussian distribution is essential to understanding many inferential statistical concepts and real world applications in the area of quality engineering, six-sigma, business, psychology, health, education, etc. the course covers all the fundamental concepts.

We provide standard normal tables using both a negative and positive z values, a table of percentiles of the standard normal distribution and other supporting documents to help the student fully grasp the concepts of the Normal distribution and how to solve real world problems based on that distribution.

The course has a wealth of selected problems and quizzes to reinforce the understanding of the concepts. In addition, a final test is available for those who want to test their understanding.

In order to fully understand the material, it may take between ten or more hours to read the lectures, practice and complete the quizzes.

The normal distribution is highly important to understanding real world applications of statistics and as such is recommended to anyone interested in statistics and analytics.

  • By the end of this course, you will be able to fully use the standard normal table

  • By the end of this course you will be able to find the Z values corresponding to percentiles of the normal distribution

  • By the end of this course, you will be able to solve real world problems about the Normal distribution

Course Curriculum

Instructor

Profile photo of Luc Zio
Luc Zio

I  have over 20 years of work experience in the field of statistics as an Applied Statistician. For the last  twelve years, I have also  been teaching undergraduate college level statistics courses at St Petersburg College,Florida, USA.As a Data scientist, my interests lie in applying Data science techniques (Exploratory Data Analyses, Statistical analyses and other Machine Learning) to real world...

Review
4.9 course rating
4K ratings
ui-avatar of Anthony Pultrone
Anthony P.
5.0
4 years ago

Instructor explained topics well. Lots of practice problems that were worked out thoroughly and explained well. Enjoyed this instructor and course.

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ui-avatar of MAIGA Boubacar Abida
Maiga B. A.
5.0
7 years ago

Excellent course
I really appreciated the course. The course is excellent and practical, easy to follow. The way of explaining makes it possible to understand.

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ui-avatar of William Kendall
William K.
5.0
8 years ago

Excellent course, covers exactly the subject matter, no fluff, and provides lots of practice exercises with feedback for learning reinforcement. I just finished the course and am very comfortable with applying what I've learned thus far. Great course!

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ui-avatar of StacieBoyce
Stacieboyce
5.0
8 years ago

Very informative and knowledgeable the information at hand in explaining the concepts to beginners whom have no knowledge base to Stats

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