The Meaning of a 95% T Confidence Interval for the Mean

In summary: MORE sure that the interval contains the true mean, then we are LESS sure that there is no mean weight gain... to the extent that the interval is small, we are more sure that there is no mean weight gain, and that is what "support" means.In summary, the 95% confidence interval for the average difference in weight loss after taking a diet pill for 6 weeks is between -3.5 and -0.5 pounds, with a standard deviation of approximately 2.6 pounds or less. At 95% confidence, it can be said that there is support for a mean weight loss, as there is no possibility that the population mean falls within the interval and there is no support for a mean
  • #1
FredericChopin
101
0

Homework Statement


A diet pill is given to 9 subjects over six weeks. The average difference in weight (follow up - baseline) is -2 pounds. What would the standard deviation have to be for the 95% T confidence interval to lie entirely below 0?

ANSWER: Around 2.6 pounds or less

Refer to the previous question. The interval would up being [-3.5, -0.5] pounds. What can be said about the population mean weight loss at 95% confidence?

A: We can not rule out the possibility of no mean weight loss at 95% confidence.

B: There is support of mean weight gain at 95% confidence.

C: There is support at 95% confidence of mean weight loss.

D: We can not rule out the possibility of mean weight gain at 95% confidence.

Homework Equations

The Attempt at a Solution


I have three attempts to answer this question.

On my first attempt, I said D, thinking that since 5% of intervals do not contain the population mean, there is a chance that the population mean could be positive (and there a mean weight gain). But I got the wrong answer, and I don't understand why.

On my second attempt, I thought that "weight gain" wasn't necessarily going to occur but "no mean weight loss" was, so I chose A, and I still got the wrong answer.

I am surprised that confidence intervals will guarantee a support (as the remaining answers of the question suggest), so I now think the answer is C. B sounds ridiculous, because it doesn't make sense why there is support for mean weight gain at 95% confidence.

Can someone help me understanding the question? I hope I finally get this question right.

Thank you.
 
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  • #2
FredericChopin said:

Homework Statement


A diet pill is given to 9 subjects over six weeks. The average difference in weight (follow up - baseline) is -2 pounds. What would the standard deviation have to be for the 95% T confidence interval to lie entirely below 0?

ANSWER: Around 2.6 pounds or less

Refer to the previous question. The interval would up being [-3.5, -0.5] pounds. What can be said about the population mean weight loss at 95% confidence?

A: We can not rule out the possibility of no mean weight loss at 95% confidence.

B: There is support of mean weight gain at 95% confidence.

C: There is support at 95% confidence of mean weight loss.

D: We can not rule out the possibility of mean weight gain at 95% confidence.

Homework Equations

The Attempt at a Solution


I have three attempts to answer this question.

On my first attempt, I said D, thinking that since 5% of intervals do not contain the population mean, there is a chance that the population mean could be positive (and there a mean weight gain). But I got the wrong answer, and I don't understand why.

On my second attempt, I thought that "weight gain" wasn't necessarily going to occur but "no mean weight loss" was, so I chose A, and I still got the wrong answer.

I am surprised that confidence intervals will guarantee a support (as the remaining answers of the question suggest), so I now think the answer is C. B sounds ridiculous, because it doesn't make sense why there is support for mean weight gain at 95% confidence.

Can someone help me understanding the question? I hope I finally get this question right.

Thank you.

For D: it said "We can not rule out the possibility of mean weight gain at 95% confidence". Of course we cannot rule out the possibility of mean gain altogether, but with 95% confidence, we can. In other words, 95% confidence is not 100% confidence.

Look at your other answers in the same way.
 
  • #3
Ray Vickson said:
For D: it said "We can not rule out the possibility of mean weight gain at 95% confidence". Of course we cannot rule out the possibility of mean gain altogether, but with 95% confidence, we can. In other words, 95% confidence is not 100% confidence.

Look at your other answers in the same way.

I see.

So (theoretically), a 100% confidence interval would be the interval (-∞, +∞). But in this case, a 95% confidence interval is [-3.5, -0.5]. As you said, the important thing is that the question asks what can be said at 95% confidence.

Since the interval does not contain any positive numbers, at 95% confidence, there is no possibility that there can be a mean weight gain (and for that matter, no mean weight loss), so D and A must be incorrect.

Using the same positive-numbers argument, presumably, there is no support for a mean weight gain at 95% confidence, so B must also be incorrect. Therefore, C must be correct.

How is that?

What puzzles me still is why any confidence interval can guarantee a support within that interval. Isn't there the slightest chance that the function is 0 within the interval?

Thank you.
 
  • #4
FredericChopin said:
I see.

So (theoretically), a 100% confidence interval would be the interval (-∞, +∞). But in this case, a 95% confidence interval is [-3.5, -0.5]. As you said, the important thing is that the question asks what can be said at 95% confidence.

Since the interval does not contain any positive numbers, at 95% confidence, there is no possibility that there can be a mean weight gain (and for that matter, no mean weight loss), so D and A must be incorrect.

Using the same positive-numbers argument, presumably, there is no support for a mean weight gain at 95% confidence, so B must also be incorrect. Therefore, C must be correct.

How is that?

What puzzles me still is why any confidence interval can guarantee a support within that interval. Isn't there the slightest chance that the function is 0 within the interval?

Thank you.

(1) A 100% confidence interval need not be the whole line; it is just an interval we are SURE contains the true mean---not just "almost sure", but absolutely sure. It could be a point (which it would be in the limit of an infinite sample size, example).
(2) I think you have identified the true/false answers correctly.
(3) Your statement "why any confidence interval can guarantee a support within that interval" is false: there is no such guarantee. We can only be more-or-less sure, but not absolutely, 100% sure. Every once in a while we will be wrong (about 5% of the time if we are looking at a 95% confidence interval).
 
  • #5
Ray Vickson said:
(1) A 100% confidence interval need not be the whole line; it is just an interval we are SURE contains the true mean---not just "almost sure", but absolutely sure. It could be a point (which it would be in the limit of an infinite sample size, example).
(2) I think you have identified the true/false answers correctly.
(3) Your statement "why any confidence interval can guarantee a support within that interval" is false: there is no such guarantee. We can only be more-or-less sure, but not absolutely, 100% sure. Every once in a while we will be wrong (about 5% of the time if we are looking at a 95% confidence interval).

That makes sense. Thank you very much. I did get the right answer, by the way. :)
 

What is a 95% confidence interval?

A 95% confidence interval is a range of values that is likely to include the true population mean with a probability of 95%. It is calculated using a sample of data and takes into account the variability in the data to estimate the range of possible values for the population mean.

Why is a 95% confidence interval commonly used?

A 95% confidence interval is commonly used because it strikes a balance between being narrow enough to provide a precise estimate of the population mean, while still being wide enough to account for the variability in the data. It is also a standard level of confidence used in many scientific studies.

How is a 95% confidence interval calculated?

A 95% confidence interval is calculated using the sample mean, sample standard deviation, sample size, and the t-distribution. The formula for a 95% confidence interval is: sample mean ± (t-value * (sample standard deviation / √sample size)), where the t-value is based on the degrees of freedom and chosen level of confidence.

What does the 95% confidence interval tell us about the population mean?

The 95% confidence interval tells us that there is a 95% chance that the true population mean falls within the calculated range. It gives us a range of possible values for the population mean, rather than a single point estimate.

Can a 95% confidence interval be used for any type of data?

A 95% confidence interval can be used for any type of data as long as certain assumptions are met, such as the data being normally distributed. However, for small sample sizes or data that is heavily skewed, other methods may be more appropriate for calculating confidence intervals.

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