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I have two data sets with the same number of values with means x1 and x2 and standard deviations of n1 and n2. How do you average means with standard deviations?
You can't average means with standard deviations. What are you trying to do with the two sets of data?
What are the standard deviation of Barclays bank?
The Bank, itself does not have a standard deviation. The number of branches, the number of customers, lending, profits, CEO's pay are all variables which will have standard deviations but none of them are mentioned. It is not possible to guess which one you are interested in!
What is the mean and standard deviations and the standard normal distribution?
Mean is the average, sum total divided by total number of data entries. Standard deviation is the square root of the sum total of the data values divided by the total number of data values. The standard normal distribution is a distribution that closely resembles a bell curve.
Why are standard z values so important?
A z-score gives the distance (specifically number of standard deviations) from the mean so when you compare z-scores, it gives a direct comparison of how far from the mean the values are.
In any distribution is the sum of the squared deviations from the mean always equal to zero?
No. It cannot be. Remember that when you square a negative number it becomes a positive number. Thus all squared deviations are positive and their sum must be positive.
How many standard deviations is 99?
You cannot have a standard deviation for 1 number.
I have two data sets with the same number of values with means x1 and x2 and standard deviations of n1 and n2. How do you average means with standard deviations?
You can't average means with standard deviations. What are you trying to do with the two sets of data?
What statistic is produced when the difference between a score and then mean is divided by the standard deviation?
z-score or standard score... tells you how many standard deviations away from the mean a particular number is in relations to all numbers in a population (or sample)
How do you find highest standard deviation in given number?
Standard deviations are measures of data distributions. Therefore, a single number cannot have meaningful standard deviation.
Give the term for the number of the standard deviations that a particular X value is away from the mean?
z
What denotes the number of standard deviations a particular score is from the mean?
The absolute value of the z-score.
What are the standard deviation of Barclays bank?
The Bank, itself does not have a standard deviation. The number of branches, the number of customers, lending, profits, CEO's pay are all variables which will have standard deviations but none of them are mentioned. It is not possible to guess which one you are interested in!
The mean number is 14 with a standard deviation of 2.5 How many standard deviations is 16.50 from the mean?
16.5 is 1 standard deviation from the mean. If you add the mean of 14 to the 1 standard deviation of 2.5, the result is 16.5.
What is the mean and standard deviations and the standard normal distribution?
Mean is the average, sum total divided by total number of data entries. Standard deviation is the square root of the sum total of the data values divided by the total number of data values. The standard normal distribution is a distribution that closely resembles a bell curve.
Why are standard z values so important?
A z-score gives the distance (specifically number of standard deviations) from the mean so when you compare z-scores, it gives a direct comparison of how far from the mean the values are.
What is the z score?
z = (x - u)/(standard dev)The z score expresses the difference of the experimental result x from the most probable result u as a number of standard deviations. The probability can then be calculated from the cumulative standard normal distribution. ie sigma(z)
What is chebychev's rule?
Chebyshev's rule, also known as Chebyshev's inequality, is a statistical theorem that describes the proportion of values that fall within a certain number of standard deviations from the mean in any distribution. It states that for any set of data, regardless of the shape of the distribution, at least (1 - 1/k^2) where k is greater than 1, of the data values will fall within k standard deviations of the mean.
