What is the standard error of the mean in analytical chemistry?

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In summary, The question in the analytical chemistry review is about the probability of a single determination being further below the mean than 2 standard deviations. The first part, with the help of a table, is simpler and the answer is 2.28%. However, the second part, which asks about the probability of the average of 4 determinations being further below the mean than 2 standard deviations, has an answer of 0.0032% which can be found by looking at the standard error of the mean.
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in my analytical chemistry review, this question cropped up. the first part was simple, but the second part has me confused to no end. I've tried playing around with the math as well as scouring my textbook for answers. help!

what is the probability that a single determination of a value is further below the mean than 2 standard deviations?

this part is the simpler part, given the table at the bottom of http://64.233.167.104/custom?q=cache:bdW_K0aRhzEJ:www.palgrave.com/business/taylor/taylor1/lecturers/lectures/handouts/hChap5.doc+chart+area+beneath+normal+curve+standard+deviations&hl=en&ct=clnk&cd=7&client=pub-8993703457585266" page.
the answer turns out to be 2.28%

the second part of the problem is: what is the probability that the average of 4 determinations is further below the mean than 2 standard deviations?

the answer was given to be 0.0032% but i cannot figure out where this value comes from.



ps. my apologies for not reading the sticky, I'll post this in the proper forums now.
 
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The standard error of the mean in analytical chemistry is a measure of the variability of the sample means from the true population mean. It is calculated by dividing the standard deviation of the sample by the square root of the number of samples. It is used to estimate the range within which the true population mean is likely to fall.

As for the second part of the question, the probability that a single determination is further below the mean than 2 standard deviations is 2.28%. This means that if you were to take a random sample and make a single determination, there is a 2.28% chance that the value you get will be further below the mean than 2 standard deviations.

Now, for the average of 4 determinations, the probability is much lower because you are taking the average of multiple values. This means that the variability is reduced and the probability of getting a value further below the mean than 2 standard deviations is also reduced. The value of 0.0032% comes from the calculations for the standard error of the mean, which takes into account the reduced variability due to the multiple determinations. This probability is much lower because it is less likely to get a value further below the mean when taking the average of 4 determinations compared to just one determination.

I would recommend reviewing the calculations for the standard error of the mean and the concept of variability in multiple determinations to better understand where the value of 0.0032% comes from. Additionally, consulting with your professor or a tutor may also help clarify any confusion you have.
 

What is a standard deviation?

A standard deviation is a measure of the spread or variability of a set of data from its mean or average. It tells you how much the data points are scattered around the mean.

How is standard deviation calculated?

To calculate the standard deviation, you need to first find the mean of your data set. Then, subtract the mean from each data point and square the result. Next, find the average of these squared differences. Finally, take the square root of this average to get the standard deviation.

What does a large standard deviation indicate?

A large standard deviation indicates that the data points are spread out over a wider range of values. This means that there is a higher variability within the data set.

What does a small standard deviation indicate?

A small standard deviation indicates that the data points are clustered around the mean and there is less variability within the data set.

Why is standard deviation important?

Standard deviation is important because it helps to measure the reliability and consistency of data. It also allows for comparison of data sets and helps to identify outliers or unusual data points.

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