Selecting Data with Minimum Standard Deviation

alvaro037  Here is an alternate solution.  I reduce the number of trials because we know std will be lowest for numbers close together so I sort the numbers and then increment through the list:

=LET(in,B2:K2,
n,5, 
sortin, SORT(TRANSPOSE(in)), 
start, SEQUENCE(ROWS(sortin)-n),
stdlist, SCAN(0,start,LAMBDA(p,i,STDEV.P(INDEX(sortin,start+i-1)))),
findLow,MATCH(MIN(stdlist),stdlist,0),
INDEX(sortin,start+findLow-1))

see attached

EDIT:

a) please note my SD calculation used STD.P per Joe's suggestion above while Hans' uses STD.S and my solution found a set starting with 8.6-8.9 and Hans' found 8.7-9.0 but the SD is the same in each case.

b) here is an alternate version of the formula that stacks/includes the AVG and SD:

=LET(in,B2:K2,
n,5,
sortin, SORT(TRANSPOSE(in)),
start, SEQUENCE(ROWS(sortin)-n),
stdlist, SCAN(0,start,LAMBDA(p,i,STDEV.P(INDEX(sortin,start+i-1)))),
findLow,MATCH(MIN(stdlist),stdlist,0),
ans,INDEX(sortin,start+findLow-1),
out,VSTACK(ans,"Avg",AVERAGE(ans),"SD",STDEV.P(ans)),
out)

I prefer to have them separate as in the attached file but that is up to you

HansVogelaar 

Use StDev_P and STDEV.P (STDEVP), not StDev_S and STDEV.S (STDEV).

StDev_P returns the actual std dev of a set of numbers.

Use StDev_S when the set of numbers represents a sampling from a larger population, and we want to estimate the std dev of the population, not the subset per se.

That does not apply here (``choose data with the minimum deviation``)