Help with making a two sided confidence interval

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SUMMARY

The discussion focuses on calculating a 90% two-sided confidence interval for the mean difference in screw diameters measured by digital and vernier scale calipers. The user initially calculated a mean of 0.004 and a standard deviation of 0.1148, but these values were incorrect. After corrections, the standard deviation was determined to be approximately 0.0116. The final confidence interval calculated using the formula x-bar ± t*(s/sqrt(n)) yielded the result of approximately [-0.0024, 0.0032], aligning closely with the expected answer in the textbook, which may have contained a rounding error.

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  • Understanding of confidence intervals and their significance in statistics.
  • Familiarity with t-distribution and how to find t-values for given confidence levels.
  • Proficiency in calculating mean and standard deviation from frequency distributions.
  • Basic knowledge of statistical software, such as R, for performing t-tests.
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  • Study the differences between digital and vernier scale measurements in precision applications.
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ldlafountain
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I am working on a problem for my Statistics class and I am looking for some clarification and some direction.

The questions asks about a study that has been done on the diameter of 50 screws (both digital and vernier scale calipers). The differences in the measured diameters had the following frequency distribution.

Difference: Frequency:
-0.03 1
-0.02 3
-0.01 11
0.00 19
0.01 10
0.02 6

I am then asked to make a 90% two sided interval for the mean difference in digital and vernier readings.

So naturally I find the mean of all of the differences by adding up all the differences (by their frequencies) and I get 0.004 as my mean and 0.1148 as my standard deviation. Next I would try and find the t-value for Q(.95) (because we are using a 90% two sided confidence interval). I had to look it up online I came up with 1.677. I would plug this all into the following equation:

x-bar (plus-minus) t*(s/sqrt(n))

I have tried this multiple times and I keep obtaining the wrong intervals. According to the back of my book I should obtain the answer [-0.0023,0.0031], but I come nowhere near. Can anyone help me? If there is something wrong with my math or the way I set up the problem, please let me know. I am thankful for any help.
 
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Hi Idlafountain! Welcome to MHB! :)

I can tell that your standard deviation is wrong. Looking at the data we can see that it should be about 0.01.
How did you calculate it?
 
Honestly, I plugged all of the numbers into a standard deviation calculator online. I actually used the one from mathisfun.com. I got the mean the same way. But what could the standard deviation be. I understand how it is calculated, but I am still having issues.
 
ldlafountain said:
Honestly, I plugged all of the numbers into a standard deviation calculator online. I actually used the one from mathisfun.com. I got the mean the same way. But what could the standard deviation be. I understand how it is calculated, but I am still having issues.

Perhaps a typing mistake? Perhaps there should be a zero after the decimal point?
Or else use a different calculator.

Btw, the remainder of your calculation is fine.
 
So I double checked my calculation on standard deviation and I got 0.0116.

So to plug it all in, I should be able to use:

.0004(plus/minus) 1.677 * (0.0116/sqrt{50})

I got the 50 from my sample size and I got the 1.677 from a t-value chart. After plugging this in, I do not get the answer I a supposed to get in the back of the book. Any ideas?
 
ldlafountain said:
So I double checked my calculation on standard deviation and I got 0.0116.

So to plug it all in, I should be able to use:

.0004(plus/minus) 1.677 * (0.0116/sqrt{50})

I got the 50 from my sample size and I got the 1.677 from a t-value chart. After plugging this in, I do not get the answer I a supposed to get in the back of the book. Any ideas?

Calculating what you have, I get:
$$0.0004 \pm 1.677 \cdot (0.0116/\sqrt{50}) = [-0.0023508, +0.0031508] \approx [-0.0024, +0.0032]$$

Isn't that what your book's answer is?
(That is, the book seems to have made either a rounding error, or a slight mistake in calculating the standard deviation.)
 
I just wanted to add that I get the same thing as ILS (after rounding) when running this in R.
Code:
data <- c(-0.03,rep(-0.02,3),rep(-0.01,11),rep(0,19),rep(0.01,10),rep(0.02,6))
t.test(data,conf.level=0.9)

The 90% CI is $(-0.002350061,0.003150061)$ and the SD is $0.01159873$. :)
 

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