Standard Error is a measure of how much the point estimate changes from sample to sample. The proportion of heads from flipping five coins has a relatively large standard error (SE = .2236), and it is not uncommon to see point estimates from 0% to 100%. The proportion of heads from flipping 1000 coins has a relatively small standard error (SE = .0158), and points estimates will rarely fall outside 45% to 55% heads P(1 – p) For proportions, the formula is SE = where n is the sample size and p = p, the sample proportion (point estimate). Compute the standard error, given a) point estimate = 0.61, null value = 0.7, and n = 120. The standard error = b) point estimate = 0.42, null value = 0.5, and n = 50. The standard error =

Standard Error is a measure of how much the point estimate changes from sample to sample. The proportion of heads from flipping five coins has a relatively large standard error (SE = .2236), and it is not uncommon to see point estimates from 0% to 100%. The proportion of heads from flipping 1000 coins has a relatively small standard error (SE = .0158), and points estimates will rarely fall outside 45% to 55% heads P(1 – p) For proportions, the formula is SE = where n is the sample size and p = p, the sample proportion (point estimate). Compute the standard error, given a) point estimate = 0.61, null value = 0.7, and n = 120. The standard error = b) point estimate = 0.42, null value = 0.5, and n = 50. The standard error =

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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we want to obtain a sample to estimate a population mean. Based on previous evidence, researchers believe the population standard deviation is approximately 38.7. We would like to be 99% confident that the estimate is within 4 of the true population mean. How large of a sample size is required ?
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