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Table of Values for Computing the Standard Deviation Computational Method ID 37 41 35 43 45 QA = (DA)² = 1 A 87 74 94 70 97 OA²=OB=B² = (B)² = 2. Variance (²) Use the information obtained above to compute the following: 1. Sum or Squares (SS) A² SS=A²_= 3. Standard Deviation (s or sd) SS S² = n-1= S = B SS n-1= B²

Table of Values for Computing the Standard Deviation Computational Method ID 37 41 35 43 45 QA = (DA)² = 1 A 87 74 94 70 97 OA²=OB=B² = (B)² = 2. Variance (²) Use the information obtained above to compute the following: 1. Sum or Squares (SS) A² SS=A²_= 3. Standard Deviation (s or sd) SS S² = n-1= S = B SS n-1= B²

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Table of Values for Computing the Standard Deviation Computational Method ID 37 41 35 43 45 A = (DA)²: A 87 74 94 70 97 A² =B=B²: (B)2 2. Variance (²) A² Use the information obtained above to compute the following: 1. Sum or Squares (SS) SS=A²-= 5² SS = n-1= 3. Standard Deviation (s or sd) SS S = √n-1 B SD_Computational Approach Table B²
Transcribed Image Text:Table of Values for Computing the Standard Deviation Computational Method ID 37 41 35 43 45 A = (DA)²: A 87 74 94 70 97 A² =B=B²: (B)2 2. Variance (²) A² Use the information obtained above to compute the following: 1. Sum or Squares (SS) SS=A²-= 5² SS = n-1= 3. Standard Deviation (s or sd) SS S = √n-1 B SD_Computational Approach Table B²
Review Previously - Configuration of data Shape - Frequency - Class intervals - Normal vs Skewed Outcomes ● Location Midpoint Balancing point - Think See-Saw • Measures of Central Tendency ● . . . ● Mean most accurate measure Median the middle of ordered scores (even- vs odd-numbered data set) Mode - location of frequently occurring scores (uni, bi, tri, multi)
Transcribed Image Text:Review Previously - Configuration of data Shape - Frequency - Class intervals - Normal vs Skewed Outcomes ● Location Midpoint Balancing point - Think See-Saw • Measures of Central Tendency ● . . . ● Mean most accurate measure Median the middle of ordered scores (even- vs odd-numbered data set) Mode - location of frequently occurring scores (uni, bi, tri, multi)
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