Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 27 Minute(s)
Language
English
Taught by
Luc Zio
Rating
2 views
Course Overview
Master the Normal Distribution through clear lectures and hands-on exercises to apply it effectively in analytics
The Normal Distribution, also known as the Gaussian Distribution, is a cornerstone of statistics and data analysis. This course provides an in-depth understanding of the Normal Distribution, its properties, and its critical role in inferential statistics. Whether you're a student, professional, or data enthusiast, this course will equip you with the knowledge and skills to apply the Normal Distribution in real-world scenarios.
The course begins by exploring the fundamental concepts of the Normal Distribution, including its shape, properties, and parameters (mean and standard deviation). You'll learn how to calculate z-scores, use standard normal tables, and interpret probabilities associated with the distribution. Key applications across fields such as quality engineering, Six Sigma, business, psychology, healthcare, education, and analytics are covered to highlight the distribution's versatility and importance.
To support your learning, the course provides:
Standard Normal Tables: Both positive and negative z-values, along with percentile tables.
Step-by-Step Guides: Practical examples to help you apply the concepts to solve real-world problems.
Reinforcement Tools: A wide variety of problems and quizzes carefully designed to solidify your understanding.
Final Test: A comprehensive assessment to evaluate your mastery of the material.
The course is self-paced and requires approximately 10 or more hours to complete, including time to read the lectures, practice problems, and complete the quizzes. Supporting documents and visual aids are included to ensure a seamless learning experience.
Understanding the Normal Distribution is essential for anyone working with data, as it forms the foundation of many advanced statistical methods. By the end of the course, you’ll be equipped to confidently analyze data and make informed decisions in various domains. This course is highly recommended for anyone interested in statistics, data analytics, or decision science.
Course Content
- 6 section(s)
- 18 lecture(s)
- Section 1 Normal distribution course data files
- Section 2 Basics of Normal distribution and reading the standard normal table
- Section 3 Properties of the Normal distribution and solving related problems
- Section 4 Percentiles of the normal distribution
- Section 5 Sampling distribution of the mean and the Central Limit Theorem
- Section 6 Conclusion
What You’ll Learn
- Understand the characteristics of the Normal Distribution
- Understand real-world applications, such as modeling height, weight, test scores, and other natural phenomena.
- By the end of this course, you will be able to fully use the standard normal table to solve problems related to the normal distribution
- 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
- By the end of this course, you will understand what a sampling distribution of the mean is and the Central limit theorem
Reviews
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AAnthony Pultrone
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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MMAIGA Boubacar Abida
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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WWilliam Kendall
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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SStacieBoyce
Very informative and knowledgeable the information at hand in explaining the concepts to beginners whom have no knowledge base to Stats
