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   The normal distribution is considered the most prominent probability distribution in statistics. There are several reasons for this:[1] First, the normal distribution arises from the central limit theorem, which states that under mild conditions, the mean of a large number of random variables drawn from the same distribution is distributed approximately normally, irrespective of the form of the original distribution. This gives it exceptionally wide application in, for example, sampling. Secondly, the normal distribution is very tractable analytically, that is, a large number of results involving this distribution can be derived in explicit form (Wikipedia).
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  In the physical sciences, random variables very often follow a normal distribution which makes error propagation and estimation much more feasible.

[:PiraScheme#Mechanics: Table of Mechanics Demonstration]

[:MEEquipmentList: List of Mechanics Equipment & Supplies]

[:Demonstrations:Lecture Demonstrations]

Hexstat Probability Demonstrator, 1A20.11

Topic and Concept:

  • Measurement, [:Measurement#ErrorAccuracy: 1A20. Error and Accuracy]

Location:

attachment:HexStat-02-400.jpg

Abstract:

256 Small steel balls fall into 9 columns or bins to form a probability curve similar to a Gaussian distribution.

Equipment

Location

ID Number

Hexstat Probability Demonstrator

ME, Bay A2, Shelf #1

1A20.10

Hexstat Teacher's Manual

ME, Bay A2, Shelf #1

1A.EQ.??

Important Setup Notes:

  • N/A

Setup and Procedure:

  1. Hold demonstrator upside down so that all of the balls fall into the reservoir (tap the board if needed).
  2. Turn the board back over so that it is right side up with the bottom flat on the table.

Cautions, Warnings, or Safety Concerns:

  • N/A

Discussion:

  • The normal distribution is considered the most prominent probability distribution in statistics. There are several reasons for this:[1] First, the normal distribution arises from the central limit theorem, which states that under mild conditions, the mean of a large number of random variables drawn from the same distribution is distributed approximately normally, irrespective of the form of the original distribution. This gives it exceptionally wide application in, for example, sampling. Secondly, the normal distribution is very tractable analytically, that is, a large number of results involving this distribution can be derived in explicit form (Wikipedia).
  • In the physical sciences, random variables very often follow a normal distribution which makes error propagation and estimation much more feasible.

attachment:HexStatIns-250.jpg

attachment:HexStat-3-250.jpg

attachment:HexStat-4-250.jpg

Videos:

References:

[:Instructional:Home]

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