0
I've been looking up the same thing for part of a stats module I do in my nutrition course. This is what I've found - no guarantee it's right but might help a bit. sampling error ∝ 1/√n ∝ means varies directly as so SE = k/√n where k is an unknown constant if we have the size of the sample, n, and the sampling error for one case in a study (which in my question we are given) we can calculate k and get the formula for that study. In my question: for 48 subjects the sample error is 0.3mmol/l. We are asked to find how many subjects would be required to get the sampling error down to 0.1mmol/l. SE = 0.3, n = 48 so 0.3 = k/√48 k = 0.3 * √48 k = 2.078 So in this case, SE = 2.078/√n. K IS NOT ALWAYS GOING TO BE THIS NUMBER!!! You'll need to work it out each time as I dont think it will always be the same. Now work backwards to find n when SE = 0.1mmol/l 0.1 = 2.078/√n √n = 20.78 n = (20.78)2 = 432 So to get a sampling error of 0.1mmol/l we would need 432 subjects. Hope this helps! Jen xx
The formula for sampling error is calculated as the difference between a population parameter and a sample statistic. It is typically represented as the margin of error, which is calculated by multiplying the standard error by a critical value from the standard normal distribution. Sampling error quantifies the amount of variability expected between different samples drawn from the same population.
Add your answer:
Earn +20 pts
How can one avoid sampling error?
To avoid sampling error, you should ensure that your sample is representative of the population, use random sampling techniques, increase the sample size when possible, and use stratified sampling if your population can be divided into subgroups. Additionally, verify the reliability of your data collection methods to minimize errors.
What kind of systematic errors are detected by varying the sample size?
Varying the sample size can detect systematic errors related to sampling bias or outliers. With larger sample sizes, trends and patterns in the data become more apparent, making it easier to identify any biases in the sampling process or extreme values that may skew results. This can help researchers understand and correct for these systematic errors to improve the reliability and validity of their findings.
Which element has the chemical formula ma?
Any chemical element; it is an error.
What is the chemical formula name for carbon tetra dihydrogen monoxide?
Probable an error or joke.
How do you name the compound CH3OC2O5?
Very unlikely that that is a real compound... probably a typographical error in the formula. There are way too many oxygens in the formula... it's just not going to form a stable molecule. Sorry...For more information on naming molecules, see the Related Questions to the left.
What is the difference between Sampling error vs sampling bias?
Sampling error leads to random error. Sampling bias leads to systematic error.
Error is serious Sampling error or non sampling error?
Both. But sampling error can be reduced through better design.Both. But sampling error can be reduced through better design.Both. But sampling error can be reduced through better design.Both. But sampling error can be reduced through better design.
Sampling error can be reduced by?
Sampling error can be reduced by
What is the difference between Sampling error and non sampling error?
In stats, a sampling error is simply one that comes from looking at a sample of the population in question and not the entire population. That is where the name comes from. But there are other kinds of stats errors. In contrast, non sampling error refers to ANY other kind of error that does NOT come from looking at the sample instead of the population. One example you may want to know about of a non sampling error is a systematic error. OR Sampling Error: There may be inaccuracy in the information collected during the sample survey, this inaccuracy may be termed as Sampling error. Sampling error = Frame error + Chance error + Response error.
Difference between standard error and sampling error?
Standard error is random error, represented by a standard deviation. Sampling error is systematic error, represented by a bias in the mean.
What causes a Sampling error?
a sampling error is o ne that occurs when one uses a population istead of a sample
What are the effects of sample size on sampling error?
The sampling error is inversely proportional to the square root of the sample size.
What are the major source of sampling error?
The major source of sampling error is sampling bias. Sampling bias is when the sample or people in the study are selected because they will side with the researcher. It is not random and therefore not an adequate sample.
What is slovene's formula?
it's a random sampling technique formula to estimate sampling size n=N/1+N(e)2 n- sampling size N-total population e-level of confidence
Sampling error refers to?
Sampling error occurs when the sampling protocol does not produce a representative sample. It may be that the sampling technique over represented a certain portion of the population, causing sample bias in the final study population.
How does a sampling error affect the interpretation of your data?
The greater the sampling error the greater the uncertainty about the results and therefore the more careful you need to be in the interpretation.
What is the committed sampling error?
The Literary Digest
