answersLogoWhite

0


Best Answer

There is no actual "smallest" observation - a standard deviation of zero means that all 100 of the observations had to be 46.

User Avatar

Wiki User

6y ago
This answer is:
User Avatar

Add your answer:

Earn +20 pts
Q: For a set of 100 observations with a mean of 46 and a standard deviation of 0 What is the value of the smallest observation in the set?
Write your answer...
Submit
Still have questions?
magnify glass
imp
Related questions

There is a set of 100 observations with a mean of 50 and a standard deviation of 0 What is the value of the smallest observation in the set?

If there is zero deviation all the observations are 50.


What is the standard deviation for 1.3?

The standard deviation for a single observation is 0.


What is the sample standard deviation of 27.5?

A single observation cannot have a sample standard deviation.


How do you calculate Q1 Q3 IQR and the standard deviation?

Suppose there are n observations. Put them in ascending order (smallest first) of size. Calculate k = n/4. Round up to the next integer, if necessary. Then Q1 is the kth observation in the ordered sets. Also Q3 is the 3kth observation in the ordered sets. IQR = Q3 - Q1 Calculation of the standards deviation is a lot more work. First find the mean = sum of all the observations, divided by the number of observations. Call that number M. Next find the mean "sum of squares", MSS. Square the value of each observation and add them together. Then divide this sum by the number of observations. Then the Variance is V = MSS - M2 Finally, the standard deviation is sqrt(V).


What is the relation between quartile deviation and standard deviation?

Strictly speaking, none. A quartile deviation is a quick and easy method to get a measure of the spread which takes account of only some of the data. The standard deviation is a detailed measure which uses all the data. Also, because the standard deviation uses all the observations it can be unduly influenced by any outliers in the data. On the other hand, because the quartile deviation ignores the smallest 25% and the largest 25% of of the observations, there are no outliers.


What is the definition of Standard deviation of a single measurement?

The standard deviation of a single observation is not defined. With a single observation, the mean of the observation(s) would be the same as the value of the observation itself. By definition, therefore, the deviation (difference between observation and mean) would always be zero. Rather a pointless exercise!


What does standard deviation tell about distribution and varity?

It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.


What is the standard deviation?

The standard deviation of a set of data is a measure of the spread of the observations. It is the square root of the mean squared deviations from the mean of the data.


What do you do if you are running a comparison to historical data and your background standard deviation is zero?

A standard deviation of 0 implies all of the observations are equal. That is, there is no variation in the data.


What are the four numbers have the smallest possible standard deviation?

If all four numbers are the same, there is no standard deviation. The mean will be equal to all 4 numbers, resulting in a 0 standard deviation. Ex) 5,5,5,5


How do I calculate the standard deviation cube test compressive results of 50486055535157526145?

A single observation, such as 50486055535157526145 cannot have a standard deviation cube test compressive result.


How is it possible to convert normal distributions to the standard normal distribution?

use this link http://www.ltcconline.net/greenl/Courses/201/probdist/zScore.htm Say you start with 1000 observations from a standard normal distribution. Then the mean is 0 and the standard deviation is 1, ignoring sample error. If you multiply every observation by Beta and add Alpha, then the new results will have a mean of Alpha and a standard deviation of Beta. Or, do the reverse. Start with a normal distribution with mean Alpha and standard deviation Beta. Subtract Alpha from all observations and divide by Beta and you wind up with the standard normal distribution.