Calculating Standard Deviation inside Excel.

I have been able to calculate the Standard Deviation Values for each data set respectively, by following the suggestion given by crystal here -
https://www.experts-exchange.com/questions/28978630/Calculating-Z-SCORE-inside-Excel.html

But I am still stuck at the last part, now how do I get the Standard Deviation Values from "+4 to zero to -4", in the orange box ?

Thanks for any ideas.

The problem isn't very well stated.  So, one has to make some assumptions about what it means.  I believe it's reasonable to state the problem this way:

"Provide the value for the underlying distribution of the data at the number of standard deviations given in column F."

One might (or might not) decide that the data is "zero mean" effectively .. otherwise it is not.
Or, one might (or might not) decide that the underlying distribution of the data is "zero mean" .. it may well be as it's close to zero.  But what's "close" in this case?  It's up to the eye of the beholder.

So, a simplified view might be that one wants to know the values at +/- 1,2,3,4 standard deviations of the underlying distribution assumed or declared to have zero mean.  In this case, the formulas in Column J would be:
J12==F12*STDEV.P(J$30:J$141)
etc.

A more precise view might be:
j12=F12*STDEV.P(J$30:J$141)+AVERAGE(J$30:J$141)
etc.

The latter formulation biases the results according to the offset of the mean value of the data.
It still assumes a symmetric distribution around the mean which is implied by 1,2,3,4 standard deviations.  Is that reasonable in this case?
In that regard, it's interesting to note that there is NO data value that reaches +4 sigma but it might be said that the underlying distribution could reach that value.
After all, there are only 112 values given and the probability of a value occurring at 4 sigma is low.

"Provide the value for the underlying distribution of the data at the number of standard deviations given in column F."

Thank you so much for your comment, Fred Marshall, you have understood the requirement 100 % correctly.

I really do not know if the data is zero mean or not. If we assume that the data is not symmetrically distributed around the mean, then does that means we cannot use Standard Deviations based concepts on this data, in order to separate the middle values from outlier values etc. ? I am just experimenting, I am not sure about all this.

In that regard, it's interesting to note that there is NO data value that reaches +4 sigma but it might be said that the underlying distribution could reach that value.
After all, there are only 112 values given and the probability of a value occurring at 4 sigma is low.

It is perfectly fine, if we do not have any value within this data sample, which would have a +4 sigma. We just need to know what value would have +4 sigma, even if it is not present within the current sample.

J12==F12*STDEV.P(J$30:J$141)
etc.
A more precise view might be:
j12=F12*STDEV.P(J$30:J$141)+AVERAGE(J$30:J$141)

Regarding these 2 different formulas, would you please tell what EXACT DIFFERENCE, does that makes. And which one is preferred over the other, if we are trying to find the middle values and the outlier values from a data sample, by using the concept of standard deviations.

Thanks again for giving it a shot.

Thank you Fred Marshall