Samples of Size 20 Samples of Size 50 400 300 300 200 200 100 100 0.5 1.0 0.65 1.00 Sample Proportions Sample Proportions Samples of Size 75 Samples of Size 100 250 6. 200 200 150 150 100 100 50 50 0.65 Sample Proportions 1.00 0.75 0.85 0.95 Sample Proportions Number of Samples Number of Samples Number of Samples Number of Samples
Samples of Size 20 Samples of Size 50 400 300 300 200 200 100 100 0.5 1.0 0.65 1.00 Sample Proportions Sample Proportions Samples of Size 75 Samples of Size 100 250 6. 200 200 150 150 100 100 50 50 0.65 Sample Proportions 1.00 0.75 0.85 0.95 Sample Proportions Number of Samples Number of Samples Number of Samples Number of Samples
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Character recognition An automatic character recogni-
tion device can successfully read about 85% of hand-
written credit card applications. To estimate what might
tion device can successfully read about 85% of hand-
written credit card applications. To estimate what might
happen when this device reads a stack of applications, the
company did a simulation using samples of size 20, 50,
75, and 100. For eachsample size , they simulated 1000
samples with success rate p = 0.85 and constructed the
histogram of the 1000 sample proportions, shown here.
Explain how these four histograms demonstrate what the
company did a simulation using samples of size 20, 50,
75, and 100. For each
samples with success rate p = 0.85 and constructed the
histogram of the 1000 sample proportions, shown here.
Explain how these four histograms demonstrate what the
Central Limit Theorem says about the sampling distribu-
tion model for sample proportions. Be sure to talk about
tion model for sample proportions. Be sure to talk about
shape, center, and spread.
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