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Q: How do you find the deviation from the mean for each value not for a whole set of data?
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What is the standard deviation if all data points are different?

It depends on the data. The standard deviation takes account of each value, therefore it is necessary to know the values to find the sd.


Which measure of central location will the sum of the deviation of each value from the data's average will always be zero?

the mean %100


How standard deviation and Mean deviation differ from each other?

There is 1) standard deviation, 2) mean deviation and 3) mean absolute deviation. The standard deviation is calculated most of the time. If our objective is to estimate the variance of the overall population from a representative random sample, then it has been shown theoretically that the standard deviation is the best estimate (most efficient). The mean deviation is calculated by first calculating the mean of the data and then calculating the deviation (value - mean) for each value. If we then sum these deviations, we calculate the mean deviation which will always be zero. So this statistic has little value. The individual deviations may however be of interest. See related link. To obtain the means absolute deviation (MAD), we sum the absolute value of the individual deviations. We will obtain a value that is similar to the standard deviation, a measure of dispersal of the data values. The MAD may be transformed to a standard deviation, if the distribution is known. The MAD has been shown to be less efficient in estimating the standard deviation, but a more robust estimator (not as influenced by erroneous data) as the standard deviation. See related link. Most of the time we use the standard deviation to provide the best estimate of the variance of the population.


What is a standard deviation?

Standard deviation is a statistical tool used to determine how tight or spread out your data is. In effect, this is quantitatively calculating your precision, the reproducibility of your data points. Here's how you find it: 1). Take the average of all the data points in your set. 2). Find the deviation of each point by finding the difference between each data point and the mean. 3). Add the squares of each deviation together. 4). Divide by one less than the number of data points. If there are 20 data points, divide by 19. 5). Take the square root of this value. 6). Done.


How do you calculate mean absolute deviation on excel?

To calculate the mean absolute deviation (MAD) in Excel, you need to follow these steps: First, enter your data set into a column in Excel. In an empty cell, use the formula =AVERAGE(ABS(A1:A10-MEDIAN(A1:A10))), replacing A1:A10 with the range of your data. Press Enter to get the MAD value, which represents the average of the absolute differences between each data point and the median of the data set.

Related questions

What is the average distance of each data value from the mean?

The standard deviation.


What is the standard deviation if all data points are different?

It depends on the data. The standard deviation takes account of each value, therefore it is necessary to know the values to find the sd.


What does mean absolute deviation indicates?

The mean absolute deviation for a set of data is a measure of the spread of data. It is calculated as follows:Find the mean (average) value for the set of data. Call it M.For each observation, O, calculate the deviation, which is O - M.The absolute deviation is the absolute value of the deviation. If O - M is positive (or 0), the absolute value is the same. If not, it is M - O. The absolute value of O - M is written as |O - M|.Calculate the average of all the absolute deviations.One reason for using the absolute value is that the sum of the deviations will always be 0 and so will provide no useful information. The mean absolute deviation will be small for compact data sets and large for more spread out data.


Which measure of central location will the sum of the deviation of each value from the data's average will always be zero?

the mean %100


What statistical measure is not a summary number but rather a comparison between each data value and a single number?

Standard deviation


What can be said about a set of data when its standard deviation is small but not zero?

This means that the set of data is clustered really close to the mean/average. Your data set likely has a small range (highest value - lowest value). In other words, if the average is 6.3, and the standard deviation is 0.7, this means that each individual piece of data, on average, is different from the mean by 0.7. Each piece of data deviates from the mean by an average (standard) of 0.7; hence standard deviation! By definition, 66% of all data is 1 standard deviation from the mean, so 66% of the data in this example would be between the values of 5.6 and 7.0.


How standard deviation and Mean deviation differ from each other?

There is 1) standard deviation, 2) mean deviation and 3) mean absolute deviation. The standard deviation is calculated most of the time. If our objective is to estimate the variance of the overall population from a representative random sample, then it has been shown theoretically that the standard deviation is the best estimate (most efficient). The mean deviation is calculated by first calculating the mean of the data and then calculating the deviation (value - mean) for each value. If we then sum these deviations, we calculate the mean deviation which will always be zero. So this statistic has little value. The individual deviations may however be of interest. See related link. To obtain the means absolute deviation (MAD), we sum the absolute value of the individual deviations. We will obtain a value that is similar to the standard deviation, a measure of dispersal of the data values. The MAD may be transformed to a standard deviation, if the distribution is known. The MAD has been shown to be less efficient in estimating the standard deviation, but a more robust estimator (not as influenced by erroneous data) as the standard deviation. See related link. Most of the time we use the standard deviation to provide the best estimate of the variance of the population.


What is a standard deviation?

Standard deviation is a statistical tool used to determine how tight or spread out your data is. In effect, this is quantitatively calculating your precision, the reproducibility of your data points. Here's how you find it: 1). Take the average of all the data points in your set. 2). Find the deviation of each point by finding the difference between each data point and the mean. 3). Add the squares of each deviation together. 4). Divide by one less than the number of data points. If there are 20 data points, divide by 19. 5). Take the square root of this value. 6). Done.


Does the value of the standard deviation depend on the value of the mean?

The standard deviation is a measure of the spread of data about the mean. Although it is essentially a measure of the spread, the fact that it is the spread ABOUT THE MEAN that is being measured means that it does depend on the value of the mean. However, the SD is not affected by a translation of the data. What that means is that if I add any fixed number to each data point, the mean will increase by that number, but the SD will be unchanged.


Is standard deviation same as standard error?

From what ive gathered standard error is how relative to the population some data is, such as how relative an answer is to men or to women. The lower the standard error the more meaningful to the population the data is. Standard deviation is how different sets of data vary between each other, sort of like the mean. * * * * * Not true! Standard deviation is a property of the whole population or distribution. Standard error applies to a sample taken from the population and is an estimate for the standard deviation.


A large set of data has a mean of 100 and standard deviation of 15Five are addedto each score in data what is the new mean and standard deviation?

The mean will move up by 5 also as the whole data set has shifted up by 5, hence the mean is 105. The spread of the data has not changed, its just been "lifted up and moved along 5" and so the standard deviation is the same, i.e. 15 Hope this helps


How do you calculate mean absolute deviation on excel?

To calculate the mean absolute deviation (MAD) in Excel, you need to follow these steps: First, enter your data set into a column in Excel. In an empty cell, use the formula =AVERAGE(ABS(A1:A10-MEDIAN(A1:A10))), replacing A1:A10 with the range of your data. Press Enter to get the MAD value, which represents the average of the absolute differences between each data point and the median of the data set.