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How do you find the sample size when given the standard deviation and the mean with a sample value?
You cannot from the information provided.
A recent survey of 50 executives who were laid off from their previous position revealed it took a mean of 26 weeks for them to find anoher positio the standard deviation of the sample was 6.2 weeks?
A recent survey of 50 executives who were laid off from their previous position revealed it took a mean of 26 weeks for them to find anoher positio. the standard deviation of the sample was 6.2 weeks. construct a 95 % confidence interval for the population. Is it reasonable that the population mean is 28 weeks? Justify your answer
We have a population with mean of 100 and standard deviation of 28 take repeated samples of size 49 and calculate the mean of each sample to form a sampling distribution Is it a Normal Distribution?
a) T or F The sampling distribution will be normal. Explain your answer. b) Find the mean and standard deviation of the sampling distribution. c) We pick one of our samples from the sampling distribution what is the probability that this sample has a mean that is greater than 109 ? Is this a usual or unusual event? these are the rest of the question.
What is the difference standard error of mean and sampling error?
The standard error of the mean and sampling error are two similar but still very different things. In order to find some statistical information about a group that is extremely large, you are often only able to look into a small group called a sample. In order to gain some insight into the reliability of your sample, you have to look at its standard deviation. Standard deviation in general tells you spread out or variable your data is. If you have a low standard deviation, that means your data is very close together with little variability. The standard deviation of the mean is calculated by dividing the standard deviation of the sample by the square root of the number of things in the sample. What this essentially tells you is how certain are that your sample accurately describes the entire group. A low standard error of the mean implies a very high accuracy. While the standard error of the mean just gives a sense for how far you are away from a true value, the sampling error gives you the exact value of the error by subtracting the value calculated for the sample from the value for the entire group. However, since it is often hard to find a value for an entire large group, this exact calculation is often impossible, while the standard error of the mean can always be found.
How do you calculate salary variance?
I believe you are interested in calculating the variance from a set of data related to salaries. Variance = square of the standard deviation, where: s= square root[sum (xi- mean)2/(n-1)] where mean of the set is the sum of all data divided by the number in the sample. X of i is a single data point (single salary). If instead of a sample of data, you have the entire population of size N, substitute N for n-1 in the above equation. You may find more information on the interpretation of variance, by searching wikipedia under variance and standard deviation. I note that an advantage of using the standard deviation rather than variance, is because the standard deviation will be in the same units as the mean.
A population has mean 128 and standard deviation 22. find the mean and the standard deviation of mean for sample of size 36?
The mean of the sample means remains the same as the population mean, which is 128. The standard deviation of the sample means, also known as the standard error, is calculated by dividing the population standard deviation by the square root of the sample size. Therefore, the standard error is ( \frac{22}{\sqrt{36}} = \frac{22}{6} \approx 3.67 ). Thus, the mean is 128 and the standard deviation of the sample means is approximately 3.67.
How do you find the sample deviation?
You're an idiot. It's standard deviation. Google that for your answer.
N equals 36 with a population mean of 74 and a mean score of 79.4 with a standard deviation of 18?
Can someone help me find the answer for a sample n=36 with a population mean of of 76 and a mean of 79.4 with a standard deviation of 18?
What is the probability that a sample of 120 female graduates will provide a sample mean more than .30 below the population mean?
To determine the probability that a sample mean from 120 female graduates is more than 0.30 below the population mean, you would need information about the population standard deviation or the standard error of the sample mean. Assuming a normal distribution, you can use the Central Limit Theorem to find the standard error by dividing the population standard deviation by the square root of the sample size (120). Then, you can calculate the z-score corresponding to a sample mean that is 0.30 below the population mean and use a standard normal distribution table or calculator to find the probability associated with that z-score.
How do you find the sample size when given the standard deviation and the mean with a sample value?
You cannot from the information provided.
Population has a mean of and micro80 and standard deviation of and sigma10. If a sample is taken from the population with a sample size of and 57345 25 find the percentage that the sample mean is samp?
To find the percentage that the sample mean is within a certain range, we can use the Central Limit Theorem. Given a population mean (μ) of 80 and a standard deviation (σ) of 10, for a sample size (n) of 25, the standard error (SE) is calculated as σ/√n = 10/√25 = 2. To find the percentage of sample means that fall within a specific range, you would use the z-score formula and standard normal distribution tables. However, without specifying the range for the sample mean, we cannot provide a specific percentage.
If quartile deviation is 24. find mean deviation and standard deviation?
Information is not sufficient to find mean deviation and standard deviation.
How do you determine your sample score on the comparison distribution?
To determine your sample score on the comparison distribution, you first need to calculate the sample mean and standard deviation. Then, you can use these statistics to find the z-score, which indicates how many standard deviations your sample mean is from the population mean. By comparing this z-score to critical values from the standard normal distribution, you can assess the significance of your sample score in relation to the comparison distribution.
A recent survey of 50 executives who were laid off from their previous position revealed it took a mean of 26 weeks for them to find anoher positio the standard deviation of the sample was 6.2 weeks?
A recent survey of 50 executives who were laid off from their previous position revealed it took a mean of 26 weeks for them to find anoher positio. the standard deviation of the sample was 6.2 weeks. construct a 95 % confidence interval for the population. Is it reasonable that the population mean is 28 weeks? Justify your answer
What Percent of population between 1 standard deviation below the mean and 2 standard deviations above mean?
In a normal distribution, approximately 68% of the population falls within one standard deviation of the mean, and about 95% falls within two standard deviations. Therefore, to find the percentage of the population between one standard deviation below the mean and two standard deviations above the mean, you would calculate 95% (within two standard deviations) minus 34% (the portion below one standard deviation), resulting in approximately 61% of the population.
How do you calculate standard deviation without a normal distribution?
You calculate standard deviation the same way as always. You find the mean, and then you sum the squares of the deviations of the samples from the means, divide by N-1, and then take the square root. This has nothing to do with whether you have a normal distribution or not. This is how you calculate sample standard deviation, where the mean is determined along with the standard deviation, and the N-1 factor represents the loss of a degree of freedom in doing so. If you knew the mean a priori, you could calculate standard deviation of the sample, and only use N, instead of N-1.
Why we calculate standard deviation and quartile deviation?
we calculate standard deviation to find the avg of the difference of all values from mean.,
