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

Course content

6 sections • 18 lectures • 1h 24m total length

Standard Normal tables1:00
Table of the standard normal table with positive Z values
Table of Z values corresponding to percentiles of the normal distribution1:00
This table provides the Z values corresponding any given percentile of the normal distribution
Central limit theorem: Pierre-Simon Laplace1:00
This lecture summarizes the central limit theorem results

About the Normal, Gaussian or Bell-shaped distribution7:00
This video provides a good introduction to the normal distribution, by explaining its properties and the many uses of the normal distribution in practical applications such as business, education, engineering, health, etc..
It also explains the standard normal distribution which is a normal distribution with mean zero and standard deviation one.
Finding the areas under the standard normal table9:56
This video explains in detail how to read the standard normal table. Using the tables with negative and positive Z values, the lecture explains how the areas or probabilities under the standard normal table are found.
Practical examples finding the areas under the standard normal table12:15
This video explains through practical examples how to find the areas under the standard normal curve.
Finding the areas under the standard normal table when the Z value is not listed2:14
This video explains in details how to find the areas under the standard normal curve when the Z value is not listed on the table.
Finding the area under the standard normal curve
Reading the standard normal table

Properties of the Normal distribution: computing the Z value3:15
This lecture discusses the properties of the normal distribution and how to standardize by computing the Z values.
Solving Normal distributions problems by standardizing or computing the Z value4:19
In this lecture, we explain how to solve various normal distribution problems by standardizing or computing the Z values.
Understanding how to use the normal distribution to solve problems4:14
This video explains through more practical exercises how to use the normal distribution.
Solving problems about the normal distribution (1)
Solving normal distribution problems (2)
Solving normal distribution problems (3)
Normal distribution problem
Solving normal distribution problems (4)
Application of the normal distribution

Percentiles of the normal distribution4:49
This videos discusses the concepts of percentiles under the normal distribution, how to find a score or measurement corresponding to a given percentile of the normal distribution and how to find the Z value
Finding the Z values corresponding to given percentiles7:23
Practical examples abut how to read a Z value corresponding to any given percentile of the standard normal distribution
More about finding the Z values corresponding to a given percentile3:45
In this video, we continue explaining how to find the Z value corresponding to a given percentile including cases where we need to find Z values to a given middle X%, say 60, 80, 85, 90, etc.. percent
Solving problems about percentiles of the normal distribution6:03
In this lecture, we show how to solve problems about percentiles of the normal distribution
Finding scores or measurements corresponding to a given percentile2:13
In this lecture, we continue with hands-on examples showing how to solve problems pertaining to percentiles of the Normal distribution.
Finding a score corresponding to a percentiles of the normal distribution
Finding a score corresponding to the 99th percentile of the standard normal
Finding cut-offs values based on the percentile of the normal distribution
Finding a cut-off value corresponding to a percentile of the standard normal

Sampling distribution of the mean and the central limit theorem.7:26
This video discusses the sampling distribution of the mean, provides the sampling distribution results and also explains the central limit theorem
Practical examples of the sampling distributions and the central limit theorem5:48
In this lecture we solve problems related to the sampling distribution of the mean and the central limit theorem
Finding probabilties about the sample mean - Normal distribution
Central limit theorem: Probability about the sample mean
Sampling distribution of the sample mean problems
Solving problems about the sampling distribution of the sample mean

Requirements

Basic Algebra course
Basic probability concepts
A scientific calculator to calculate Z values or any other software

Description

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.

Who this course is for:

College students taking a statistics course
Those looking to learn or refresh statistical concepts for data-driven roles, such as data analysts, business managers, or public health officials.
Professionals interested in six-sigma applications
Professionals in the area of data sciences. business, engineering, psychology, health, social sciences, etc/.
Anyone interested in understand the Normal (Bell-Shaped) or Gaussian distribution

What you'll learn

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Course content

Normal distribution course data files3 lectures • 3min

Basics of Normal distribution and reading the standard normal table4 lectures • 31min

Properties of the Normal distribution and solving related problems3 lectures • 12min

Percentiles of the normal distribution5 lectures • 24min

Sampling distribution of the mean and the Central Limit Theorem2 lectures • 13min

Conclusion1 lecture • 4min

Requirements

Description

Who this course is for: