Confusion about using the t table or z table for confidence intervals

In summary, the PCB concentration of a fish caught in Lake Michigan was measured using a technique known to have a normally distributed error with a standard deviation of .08ppm. With a sample size of 10, the confidence interval for the PCB level of this fish with 95% confidence is between 10.91ppm and 12.49ppm. If the standard deviation is not known, the Student's t-distribution is used for estimation. The distinction between population parameters and sample statistics is important in understanding statistics.
  • #1
Bill Nye Tho
48
0
Here's the question:

The PCB concentration of a fis hcaught in Lake Michigan was measured by a technique that is known to result in an error of measurement that is normally distributed with a standard deviation of .08 ppm. Suppose the results of 10 independent measurements of this fish are:

11.2, 12.4, 10.8, 11.6, 12.5, 10.1, 11.0, 12.2, 12.4, 10.6

Give a 95 percent interval for the PCB level of this fish.

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So, I have a small sample size (10) and a normal distribution. I attempted to use the t-table for this solution but the solutions manual used the Z-distribution table. I can't figure out why.
 
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  • #2
We have a known standard deviation. It should probably be .8 ppm typo? So the confidence interval is
$$\bar{x}-Z_{.95/2}\frac{\sigma}{\sqrt{n}}<\mu<\bar{x}+Z_{.95/2}\frac{\sigma}{\sqrt{n}}$$

If the standard deviation is not know, we use the sample standard deviation s to estimate it and the Student's t-distribution

$$\bar{x}-t_{.95/2}\frac{s}{\sqrt{n}}<\mu<\bar{x}+t_{.95/2}\frac{s}{\sqrt{n}}$$
 
  • #3
lurflurf said:
We have a known standard deviation. It should probably be .8 ppm typo? So the confidence interval is
$$\bar{x}-Z_{.95/2}\frac{\sigma}{\sqrt{n}}<\mu<\bar{x}+Z_{.95/2}\frac{\sigma}{\sqrt{n}}$$

If the standard deviation is not know, we use the sample standard deviation s to estimate it and the Student's t-distribution

$$\bar{x}-t_{.95/2}\frac{s}{\sqrt{n}}<\mu<\bar{x}+t_{.95/2}\frac{s}{\sqrt{n}}$$

Thanks for the reply lurflurf!

That leads me to additional question. I'm given a data set of a sample of 18 students and their IQ scores. Why is the confidence interval for the mean IQ estimated with the Student's t-distribution. I can easily find the variance and the deviation from the data set.

What is the difference between finding the standard deviation myself and having it explicitly stated?
 
  • #4
Bill Nye Tho said:
Thanks for the reply lurflurf!

That leads me to additional question. I'm given a data set of a sample of 18 students and their IQ scores. Why is the confidence interval for the mean IQ estimated with the Student's t-distribution. I can easily find the variance and the deviation from the data set.

What is the difference between finding the standard deviation myself and having it explicitly stated?


You can't find the standard deviation yourself. You CAN estimate the standard deviation using your sample.

The distinction between population parameters and sample statistics is very important. You won't get anywhere in statistics until you grasp this.
 
  • #5
Hornbein said:
You can't find the standard deviation yourself. You CAN estimate the standard deviation using your sample.

The distinction between population parameters and sample statistics is very important. You won't get anywhere in statistics until you grasp this.

That just cleared up a whoooooole lot of this course for me.

Thanks for that!
 

1. What is the difference between the t table and the z table?

The t table and the z table are both statistical tables used to determine critical values for confidence intervals. The main difference between them is that the t table is used when the sample size is small (typically less than 30), while the z table is used when the sample size is large (typically greater than 30).

2. When should I use the t table for confidence intervals?

The t table should be used when the sample size is small, as mentioned earlier. This is because the t distribution takes into account the variability of smaller sample sizes, while the z distribution assumes a larger sample size and a known population standard deviation.

3. Can I use the z table for confidence intervals even if my sample size is small?

No, it is not recommended to use the z table for small sample sizes. This is because the z distribution assumes a larger sample size and a known population standard deviation, which may not accurately reflect the data from a smaller sample size.

4. How do I determine which table to use for my confidence interval?

The decision of which table to use for your confidence interval depends on the sample size and whether the population standard deviation is known or unknown. If the sample size is large (typically greater than 30) and the population standard deviation is known, the z table should be used. If the sample size is small (typically less than 30) or the population standard deviation is unknown, the t table should be used.

5. Can I use the t table for confidence intervals even if my sample size is large?

Yes, you can use the t table for confidence intervals even if your sample size is large. However, as the sample size gets larger, the t distribution becomes more similar to the z distribution, and the results from both tables will be very similar. Therefore, it is recommended to use the z table for larger sample sizes to simplify calculations.

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