# Show Standard Deviation is Zero When X=k

• Simonel
In summary: So I think it's important to make the connection between the concepts. In summary, when a variable is a constant, the standard deviation is zero.

#### Simonel

Show that The standard deviation is zero if and only if X is a constant function,that is ,X(s) = k for every s belonging to S,or ,simply X=k.

When they say constant function it means every element in S is been mapped to single element in the range.That is the single element is k.
Which means all random variables are taking a single value which is K.
I don't if I should assume that it is an equiprobable space or no.
Due to that I'm getting confused in calculating my mean n thus heading towards showing std dev 0
I don't know if I'm thinking in the right direction

A bit more information is needed about the problem, in particular whether the sample space S contains only finitely many elements, in which case we say that X is a discrete random variable. The statement you are asked to prove is not true for a non-discrete (aka 'continuous') random variable, but there is a similar statement which is true, which is that the standard deviation is zero if and only if the random variable is 'almost surely' constant. That means that there exists some value k such that Prob(X(s)=k)=1.

So let's assume S has only finitely many elements. You do not need to assume anything about equiprobability in order to prove the statement. All you need to assume is that no element s of the sample space has probability zero, which is an assumption that is usually implicitly made for any discrete random variable.

I suggest you start by assuming S has n elements ##s_1,...,s_n##, with values ##X_1,...,X_n## and probabilities ##p_1,...,p_n## (which must add to 1, and none of which are zero) and use that to write out an expression for the standard deviation. Then assume there is at least one element, say ##X_k## that is not equal to the mean ##\bar X## and see if you can prove that the standard deviation must be nonzero.

Simonel said:
Show that The standard deviation is zero if and only if X is a constant function,that is ,X(s) = k for every s belonging to S,or ,simply X=k.

When they say constant function it means every element in S is been mapped to single element in the range.That is the single element is k.
Which means all random variables are taking a single value which is K.
I don't if I should assume that it is an equiprobable space or no.
No. You should not assume that.
Due to that I'm getting confused in calculating my mean n thus heading towards showing std dev 0
If the variable is a constant, k, what can you say about k and the mean, ##\mu##?
I don't know if I'm thinking in the right direction
For a homework problem, you need to show work and use the homework template. Then people can tell you if you are going in the right direction. Your profile says that you have a degree in statistics, so you should be able to show a corresponding level of work.

my approach would be to work directly with the CDF of ##X## and the definition of strict convexity.

From there work backwards to why Jensen's Inequality gives you the insight you want regarding variance (and std deviation is zero iff variance is zero).

If needed, you can then also work backward to the sample space implications, supposing that you understand the links between CDFs and sample spaces. In the case of an uncountable sample space, the term "almost" will show up...

- - - -
I suppose my approach de-emphasizes the sample space, but in general convexity is a big deal, and CDFs are extremely useful.

## 1. What does it mean for the standard deviation to be zero when X is equal to a constant k?

When the standard deviation is zero for a given data set, it means that all of the data points are the same value, which is the constant k in this case. This indicates that there is no variability in the data and all of the values are equal to the constant k.

## 2. How is the standard deviation calculated when X is equal to a constant k?

When calculating the standard deviation for a data set where all values are equal to a constant k, the standard deviation formula would yield a result of zero, as there is no variation in the data. The calculation would involve taking the difference between each data point and the mean, squaring those differences, summing them, and then taking the square root of the sum. However, since all values are the same, the difference between each value and the mean will always be zero, resulting in a sum of zero and a standard deviation of zero.

## 3. Can the standard deviation be zero for a data set with multiple values of X equal to a constant k?

Yes, it is possible for the standard deviation to be zero in a data set with multiple values of X equal to a constant k. This would occur if all of the data points are the same value of k. However, if there are any other values for X in the data set, the standard deviation would not be zero as there would be some variability in the data.

## 4. What does a standard deviation of zero indicate about the data set?

A standard deviation of zero indicates that there is no variability in the data set. This could mean that all of the data points are the same value, or that there is a consistent pattern or trend in the data. It is important to consider the context of the data and the reasoning behind why the standard deviation is zero.

## 5. Is it possible for the standard deviation to change from zero to a non-zero value when X is equal to a constant k?

No, if all of the data points have a value of the constant k, the standard deviation will remain at zero. This is because the standard deviation is a measure of variability, and with all values being the same, there is no variability in the data. However, if there are any changes in the values of X, the standard deviation may become non-zero as the data becomes more varied.

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