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Q: Will the standard error always be lower than the standard deviation?
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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.


Standard deviation is denoted by?

The letter s, or by sd. The Greek lower case sigma is also used.


Is standard deviation an absolute value?

No. Standard deviation is not an absolute value. The standard deviation is often written as a single positive value (magnitude), but it is really a binomial, and it equals both the positive and negative of the given magnitude. For example, if you are told that for a population the SD is 5.0, it really means +5.0 and -5.0 from the population mean. It defines a region within the distribution, starting at the lower magnitude (-5.0) increasing to zero (the mean), and another region starting at zero (the mean) and increasing up to the upper magnitude (+5.0). Both regions together define the (continuous) region of standard deviation from the mean value.


Can the five-number summary be used to calculate the standard deviation?

No. To calculate a sample standard deviation one requires the sample values. The five-number summary provides only the lowest value, the highest, the median, and the upper and lower quartiles. In any sample of size greater than five some values will be missing from the summary.


What is quartiles?

The quartile deviation(QD) is half the difference between the highest and lower quartile in a distribution.

Related questions

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.


Is sigma the same thing as standard deviation?

The lower case sigma character (σ) represents standard deviation.


Is the Symbol for the population standard deviation?

A lower case s is the symbol.


What is the symbol for simple standard deviation?

It is the lower case Greek sigma.


Which is more consistency arthematice mean is 110 and standard deviation is 25 and arthematic mean is 90 and standard deviation is 15?

The standard deviation is a number that tells you how scattered the data are centered about the arithmetic mean. The mean tells you nothing about the consistency of the data. The lower standard deviation dataset is less scattered and can be regarded as more consistent.


How does one interpret a standard deviation which is more than the mean?

Standard deviation is a measure of the dispersion of the data. When the standard deviation is greater than the mean, a coefficient of variation is greater than one. See: http://en.wikipedia.org/wiki/Coefficient_of_variation If you assume the data is normally distributed, then the lower limit of the interval of the mean +/- one standard deviation (68% confidence interval) will be a negative value. If it is not realistic to have negative values, then the assumption of a normal distribution may be in error and you should consider other distributions. Common distributions with no negative values are gamma, log normal and exponential.


What is the relevance of calculating standard deviation?

The Standard Deviation will give you an idea of how 'spread apart' the data is. Suppose the average gasoline prices in your town are 2.75 per gallon. A low standard deviation means many of the gas stations will have prices close to that price, while a high standard deviation means you would find prices much higher and also much lower than that average price.


Standard deviation is denoted by?

The letter s, or by sd. The Greek lower case sigma is also used.


How does a sample size impact the standard deviation?

If I take 10 items (a small sample) from a population and calculate the standard deviation, then I take 100 items (larger sample), and calculate the standard deviation, how will my statistics change? The smaller sample could have a higher, lower or about equal the standard deviation of the larger sample. It's also possible that the smaller sample could be, by chance, closer to the standard deviation of the population. However, A properly taken larger sample will, in general, be a more reliable estimate of the standard deviation of the population than a smaller one. There are mathematical equations to show this, that in the long run, larger samples provide better estimates. This is generally but not always true. If your population is changing as you are collecting data, then a very large sample may not be representative as it takes time to collect.


What is the relationship between the mean and standard deviation in statistics?

The 'standard deviation' in statistics or probability is a measure of how spread out the numbers are. It mathematical terms, it is the square root of the mean of the squared deviations of all the numbers in the data set from the mean of that set. It is approximately equal to the average deviation from the mean. If you have a set of values with low standard deviation, it means that in general, most of the values are close to the mean. A high standard deviation means that the values in general, differ a lot from the mean. The variance is the standard deviation squared. That is to say, the standard deviation is the square root of the variance. To calculate the variance, we simply take each number in the set and subtract it from the mean. Next square that value and do the same for each number in the set. Lastly, take the mean of all the squares. The mean of the squared deviation from the mean is the variance. The square root of the variance is the standard deviation. If you take the following data series for example, the mean for all of them is '3'. 3, 3, 3, 3, 3, 3 all the values are 3, they're the same as the mean. The standard deviation is zero. This is because the difference from the mean is zero in each case, and after squaring and then taking the mean, the variance is zero. Last, the square root of zero is zero so the standard deviation is zero. Of note is that since you are squaring the deviations from the mean, the variance and hence the standard deviation can never be negative. 1, 3, 3, 3, 3, 5 - most of the values are the same as the mean. This has a low standard deviation. In this case, the standard deviation is very small since most of the difference from the mean are small. 1, 1, 1, 5, 5, 5 - all the values are two higher or two lower than the mean. This series has the highest standard deviation.


What is mean by -3standard deviation in bmi?

BMI varies from person to person and one measure of this variability is the standard deviation. Assuming the BMI is approximately normally distributed, only around 0.135% of the people will have results that are -3 sd or lower.


When computing Standard deviation should you eliminate the extreme values?

Generally not without further reason. Extreme values are often called outliers. Eliminating unusually high values will lower the standard deviation. You may want to calculate standard deviations with and without the extreme values to identify their impact on calculations. See related link for additional discussion.