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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.
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Section 1: Normal distribution course data files | |||
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Lecture 1 | 1 page | ||
Table of the standard normal table with positive Z values |
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Lecture 2 | 1 page | ||
This table provides the Z values corresponding any given percentile of the normal distribution |
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Lecture 3 | 1 page | ||
This lecture summarizes the central limit theorem results |
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Section 2: Basics of Normal distribution and reading the standard normal table | |||
Lecture 4 | 07:00 | ||
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.. |
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Lecture 5 | 09:56 | ||
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. |
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Lecture 6 | 12:15 | ||
This video explains through practical examples how to find the areas under the standard normal curve. |
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Lecture 7 | 02:14 | ||
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. |
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Quiz 1 | 6 questions | ||
In this quiz, we are asked to find the areas under the standard normal curve |
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Quiz 2 | 5 questions | ||
In this quiz we continue finding the area understand normal table |
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Section 3: Properties of the Normal distribution and solving related problems | |||
Lecture 8 | 03:15 | ||
This lecture discusses the properties of the normal distribution and how to standardize by computing the Z values. |
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Lecture 9 | 04:19 | ||
In this lecture, we explain how to solve various normal distribution problems by standardizing or computing the Z values. |
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Lecture 10 | 04:14 | ||
This video explains through more practical exercises how to use the normal distribution. |
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Quiz 3 | 1 question | ||
Hands-on application of the normal distribution to solve problem. |
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Quiz 4 | 1 question | ||
In this quiz, you are asked to solve a normal distribution problem. |
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Quiz 5 | 2 questions | ||
In this quiz, you are asked to solve a normal distribution problem. |
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Quiz 6 | 1 question | ||
In this quiz, you are asked to solve a problem related to the normal distribution |
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Quiz 7 | 1 question | ||
In this quiz, you are asked to solve a normal distribution related problem. |
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Quiz 8 | 1 question | ||
In this quiz, you are asked to calculate a probability of the normal distribution. |
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Section 4: Percentiles of the normal distribution | |||
Lecture 11 | 04:49 | ||
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 |
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Lecture 12 | 07:23 | ||
Practical examples abut how to read a Z value corresponding to any given percentile of the standard normal distribution |
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Lecture 13 | 03:45 | ||
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 |
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Lecture 14 | 06:03 | ||
In this lecture, we show how to solve problems about percentiles of the normal distribution |
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Lecture 15 | 02:13 | ||
In this lecture, we continue with hands-on examples showing how to solve problems pertaining to percentiles of the Normal distribution. |
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Quiz 9 | 1 question | ||
In this quiz, we are asked to compute a score corresponding to a top percentile of the normal distribution |
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Quiz 10 | 1 question | ||
In this quiz, you are asked to find a score corresponding to a 99th percentile of the standard normal distribution |
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Quiz 11 | 1 question | ||
In this quiz, you are asked to find cut-offs values corresponding to a normal distribution percentiles |
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Quiz 12 | 1 question | ||
In this quiz, we are asked to find the cut-off value corresponding to a percentile of the standard normal distribution. |
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Section 5: Sampling distribution of the mean and the Central Limit Theorem | |||
Lecture 16 | 07:26 | ||
This video discusses the sampling distribution of the mean, provides the sampling distribution results and also explains the central limit theorem |
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Lecture 17 | 05:48 | ||
In this lecture we solve problems related to the sampling distribution of the mean and the central limit theorem |
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Quiz 13 | 1 question | ||
In this quiz, we want to calculate a probability about the sample mean |
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Quiz 14 | 1 question | ||
In this quiz, you will calculate a probability about the sample mean |
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Quiz 15 | 1 question | ||
In this quiz, you will solve problem related to the sampling distribution of the sample mean |
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Quiz 16 | 1 question | ||
In this quiz, we want to solve a sampling distribution of the sample mean problem |
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Section 6: Conclusion | |||
Lecture 18 | 03:31 | ||
Concluding remarks about the Normal Distribution |
I have over 18 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. As an Applied Statistician, I have developed over the years a strong interest in using EXCEL as a statistical tool with my classes in order to give to the students real world hands-on experience with Statistics.