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| ||<:30%>[:PiraScheme#Mechanics: Table of Mechanics Demonstration]||<:30%>[:MEEquipmentList: List of Mechanics Equipment & Supplies]||<:30%>[:Demonstrations:Lecture Demonstrations]|| | ||<:30%>[[PiraScheme#Mechanics| Table of Mechanics Demonstration]]||<:30%>[[MEEquipmentList| List of Mechanics Equipment & Supplies]]||<:30%>[[Demonstrations|Lecture Demonstrations]]|| |
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| = Sampling Demonstrator, Unknown PIRA# = | = Sampling Demonstrator, 1A20.15 = '''Topic and Concept:''' Measurement, [[Measurement#ErrorAccuracy| 1A20. Error and Accuracy]] |
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| * '''Cabinet:''' [:MechanicsCabinet:Mechanic (ME)] * '''Bay:''' [:MechanicsCabinetBayA2:(A2)] |
* '''Cabinet:''' [[MechanicsCabinet|Mechanic (ME)]] * '''Bay:''' [[MechanicsCabinetBayA2|(A2)]] |
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| attachment:Sampling-02-400.jpg | {{attachment:Sampling-02-400.jpg}} |
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| '''Description:''' | '''Abstract:''' |
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| ||apparatus||ME, Bay B1, Shelf #2|| || ||all other parts||ME, Bay B1, Shelf #2|| || ||...||ME, Bay B1, Shelf #2|| || ||Possible supplies that are needed||Rode and Tack Cabinet|| || ||...|| In Lecture Halls|| || ||...|| Stock Cabinet || || ||...|| Stock Cabinet || || |
||Bowl of 5000 Beads||ME, Bay A2, Shelf #1|| || ||(10x10)||ME, Bay A2, Shelf #1|| || ||(10x5)||ME, Bay A2, Shelf #1|| || ||(5x5)||ME, Bay A2, Shelf #1|| || ||(5x2)||ME, Bay A2, Shelf #1|| || ||Large Tray||ME, Bay A2, Shelf #1|| || |
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| A. '''''This demonstration requires a minimum 24 hour notice.''''' * '''''This demonstration requires LN2''''' * '''''Back-to-Back lectures is NOT possible; We'll do one lecture one day and the other the next day.''''' |
* '''''Please do not spill the beads!''''' '''Setup and Procedure:''' * N/A '''Cautions, Warnings, or Safety Concerns:''' * Beads are loose and can be lost easily. * Use a large tray to collect loose beads. |
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| '''Setup:''' | '''Discussion:''' |
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| 1. Make a Setup check list. 1. ... |
Sampling is using a subset of a set of data to determine the overall characteristics of the set. From Wikipedia, the three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. |
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| '''Cautions, Warnings, or Safety Concerns:''' 1. List any Warnings.... 1. Demonstration may require practice. |
||{{attachment:Sampling-02-250.jpg}}||{{attachment:Sampling-03-250.jpg}}||{{attachment:Sampling-04-250.jpg}}||{{attachment:Sampling-05-250.jpg}}|| |
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'''Demonstration:''' ||attachment:Sampling-02-250.jpg||attachment:Sampling-03-250.jpg||attachment:Sampling-04-250.jpg||attachment:Sampling-05-250.jpg|| |
'''Videos:''' * [[https://www.youtube.com/user/LectureDemostrations/videos?view=1|Lecture Demonstration's Youtube Channel]] |
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| * [[http://en.wikipedia.org/wiki/Normal_distribution|Normal Distribution - Wikipedia]] * [[https://en.wikipedia.org/wiki/Sampling_%28statistics%29|Sampling - Wikipedia]] |
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| 1. List any references [:Instructional:Home] |
[[Instructional|Home]] |
Sampling Demonstrator, 1A20.15
Topic and Concept:
Measurement, 1A20. Error and Accuracy
Location:
Cabinet: Mechanic (ME)
Bay: (A2)
Shelf: #1
Abstract:
This is a Lansford 5000 Colored Bead Sampling Demonstrator with 4 wooden sampling paddles of different sizes; (10x10), (10x5), (5x5), and a (5x2). Statistical sampling of 5000 color balls consisting of; 50%White, 30#Green, 10%Red, 5%Black, 3%Violet, 1%Yellow, 0.5%Pink, and 0.5%Blue.
Equipment |
Location |
ID Number |
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Bowl of 5000 Beads |
ME, Bay A2, Shelf #1 |
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(10x10) |
ME, Bay A2, Shelf #1 |
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(10x5) |
ME, Bay A2, Shelf #1 |
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(5x5) |
ME, Bay A2, Shelf #1 |
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(5x2) |
ME, Bay A2, Shelf #1 |
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Large Tray |
ME, Bay A2, Shelf #1 |
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Important Setup Notes:
Please do not spill the beads!
Setup and Procedure:
- N/A
Cautions, Warnings, or Safety Concerns:
- Beads are loose and can be lost easily.
- Use a large tray to collect loose beads.
Discussion:
Sampling is using a subset of a set of data to determine the overall characteristics of the set. From Wikipedia, the three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data.
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Videos:
References: