How does one find sample size without a given variance?

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Homework Help Overview

The problem involves determining the sample size required to detect deviations in the mean pH value of a chemical, specifically when the mean is targeted at 5. The context includes considerations of statistical significance and error probabilities related to hypothesis testing.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the interpretation of type-II error and the necessary parameters for calculating sample size, including the unknown variance and margin of error. Questions arise regarding the relationship between sample variance and the variance of the mean.

Discussion Status

The discussion is active, with participants exploring different statistical approaches and clarifying the requirements of the problem. Some guidance has been offered regarding the use of t-distribution and the formulation of the sample size equation, but no consensus has been reached on the values of the unknown parameters.

Contextual Notes

There is uncertainty regarding the existence of a part (a) of the question, which may provide additional context or requirements. Participants are also navigating the implications of not having a specified variance.

Eclair_de_XII
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Homework Statement


"The mean pH value of a certain chemical is to be controlled at ##\mu = 5##. Deviation from this target value in either direction is to be detected with high probability. For this purpose it is proposed to measure a ceratin number of samples from each batch and decide that the mean pH is different from 5 if the sample mean differs significantly from 5 at the 10% level of significance."
(b) "What sample size is needed if the probability of not detecting a change of one standard deviation is to be no more than 1%?"

Homework Equations


##H_0: \mu = 5##
##H_1: \mu ≠ 5##

The Attempt at a Solution


Basically, I'm interpreting this probability as the probability of a type-II error. So ##\beta = 0.01##. I know that the formula for the required sample size in this case would be: ##n=(\frac{\sigma}{E})^2##, but I don't know what ##\sigma## is. For that matter, I don't know what ##E## is supposed to be, either. So I'm kind of stuck, here.
 
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What is the relationship between the variance of a sample and the variance of the mean?
 
The question , as quoted, has a part (b). Is there a part (a)?
 
mjc123 said:
What is the relationship between the variance of a sample and the variance of the mean?

Let's see... The variance of a sample is: ##s^2=\frac{1}{n-1}∑(\bar X - X_i)^2## and the variance of the mean, was ##Var(\bar X)=\frac{Var(X)}{\sqrt{n}}##? I'll get back to you on the matter of their relationship.

Stephen Tashi said:
Is there a part (a)?

(a) "State the null hypothesis and the alternate hypothesis. What can you infer about the statistic ##\mu##?"
I didn't think it was related to the problem, so I decided to exclude it.
 
Eclair_de_XII said:
but I don't know what ##\sigma## is.

Instead of thinking about a statistic ("z") with a normal distribution, think about using the statistic with a t-distribution.
 
So what I'm gathering is to find an ##n## such that ##T=\frac{\mu - \bar x}{s/\sqrt{n}}=t_{n-1,\alpha /2}##.

In any case, though, my instructor told me to use ##-z_{\alpha /2}+\frac{\delta \sqrt{n}}{\sigma}=z_{\beta}##, and by setting ##\delta=\sigma##, I get ##n=(z_{\alpha /2}+z_{\beta})^2##.
 

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