Are the statements about the confidence interval correct?

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Discussion Overview

The discussion revolves around the correctness of statements related to a 90% confidence interval, specifically addressing the effects of sample size and standard error on the confidence interval's properties. The scope includes statistical theory and reasoning regarding confidence intervals.

Discussion Character

  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant suggests that doubling the sample size reduces the likelihood of the true value being outside the confidence interval.
  • Another participant agrees that the confidence interval will shrink in width with a larger sample size but emphasizes that the confidence level remains at 90%.
  • A participant questions the application of a z-value, noting that a t-score may be more appropriate if the standard deviation is not known and that standard error refers to the standard deviation of the sample mean.
  • There is a challenge regarding the relationship between standard error and confidence interval width, with one participant asserting that a larger standard error leads to a wider confidence interval.

Areas of Agreement / Disagreement

Participants express differing views on the implications of sample size and standard error on confidence intervals, indicating that multiple competing views remain without consensus on the correctness of the statements presented.

Contextual Notes

There are unresolved assumptions regarding the use of z-scores versus t-scores, as well as the definitions and implications of standard error in the context of confidence intervals.

mathmari
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Hey! :o

We have a 90%-confidence interval. I want to check if the following statements are correct.

1. If double the sample, the possibility that the value that we are looking for is out of the confidence interval is smaller.

2. The bigger the standard error, the smaller the confidence interval. Since the confidence interval is $\left (\overline{x}- Z_{a/2}\cdot s_x, \overline{x}+ Z_{a/2}\cdot s_x\right )$, where $s_x$ is the standard error, I think that the second statement is wrong and it should be that the bigger the standard error, the bigger the confidence interval.
Is this correct? (Wondering)

What about the first statement? (Wondering)
 
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It's still a $90\%$ confidence interval, right? With double the sample size, your confidence interval will shrink in absolute width, but it will still be calculated on the basis of $90\%$ confidence. The probabilities will not change, just the interval size.
 
Ackbach said:
It's still a $90\%$ confidence interval, right? With double the sample size, your confidence interval will shrink in absolute width, but it will still be calculated on the basis of $90\%$ confidence. The probabilities will not change, just the interval size.

I see! Thank you very much! (Smile)
 
Erm...
We're applying a z-value, which can only apply if the standard deviation $\sigma_x$ is given.
But apparently it's not, since we have an $s_x$, which would typically be calculated from a sample.
In that case I think we're supposed to apply a $t$-score instead of a $z$-score, aren't we? (Wondering)

Furthermore, you mention a so called standard error, but that means we're talking about the standard deviation of the mean of a sample, typically defined as $SE=s_{\bar x}=\frac{s_x}{\sqrt n}$.

This is about the standard deviation of the sample mean. Are we on the same page here? (Wondering)
 

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