Скачать или смотреть How To Solve Normal Distribution Problems in GRE | Continuous Random Variable GRE (Part-1)

This video is the 1st part of "How To Solve Normal Distribution Problems in GRE | Continuous Random Variable GRE ". The normal distribution is a form of distribution of data that follows a bell-shaped curve. All normal distributions satisfy the following properties:

1- The mean, median, and mode of the data are nearly all equal.
2- Approximately 68% of the observations fall within 1 standard deviation of the mean.
3- Approximately 96% of the observations fall within 2 standard deviations of the mean.
4- Approximately 100% of the observations fall within 3 standard deviations of the mean.

A Histogram is the most commonly used graph to show frequency distributions. Three different scenarios are discussed which will definitely help to solve any kind of histogram and Normal Distribution Problems in GRE.

A continuous random variable is one that takes an infinite number of possible values. This concept is highly asked about these days and this video covers most of the aspects of this concept.

Once understood by the students, everyone will be well equipped with tools including shortcuts to ace such questions in exams. GRE and GMAT are the two widely accepted Graduate Exams for anyone seeking admission to a Master's Degree or Master's in Business Administration (MBA). These are not simple math-based exams, but Quantitative Reasoning exams. Although the exam is based on the same concepts as simple high school math, it tests the logical reasoning behind each concept. So the test taker must be conceptually sound and should have enough tips and tricks to perform well on the exam.

GRE INSIGHT is an Ideal place to make yourself Conceptually strong and to get equipped with Tips & Tricks for performing Exceptionally well on GRE Quantitative Reasoning.

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⏱️⏱️VIDEO CHAPTERS⏱️⏱️
0:00 Introduction To Histogram
6:25 1st Scenario (Symmetrical)
10:48 2nd Scenario (Left Skewed)
14:05 3rd Scenario (Right Skewed)
16:05 Summary (3 Scenarios)
17:09 Introduction to Normal DIstribution
23:36 Important Concept for Normal DIstribution (2 Scenarios)
29:35 Introduction to Continuous Random Variable
33:37 Highly Tested Practice Question (Continuous Random Variable)

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