I have this dataset with 6 different hw grades. I ned to find the HW average, but I need the lowest value to be dropped. Here is the code:
Name HW1 HW2 HW3 HW4 HW5 HW6
Abby | 95.00 | 85.00 | 69.00 | 93.00 | 81.70 | 85.00 |
Hans | 95.50 | 56.50 | 77.50 | 50.00 | 79.20 | 75.00 |
Beyonce | 90.00 | 83.00 | 89.00 | 97.00 | 90.80 | 85.00 |
Camila | 92.50 | 98.00 | 89.00 | 84.00 | 80.00 | 85.00 |
Carlos | 95.00 | 69.00 | 55.00 | 92.00 | 76.70 | 100.00 |
Darius | 95.00 | 97.00 | 99.00 | 89.00 | 100.00 | 87.50 |
Terrance | 93.00 | 92.50 | 95.00 | 68.50 | 82.00 | 95.00 |
Evelyn | 92.50 | 94.00 | 100.00 | 96.00 | 100.00 | 100.00 |
Gertrude | 95.00 | 96.00 | 100.00 | 97.00 | 92.50 | 100.00 |
Alamance | 93.50 | 84.00 | 100.00 | 91.00 | 72.50 | 85.00 |
Hiromi | 85.50 | 94.00 | 85.00 | 84.00 | 97.50 | 100.00 |
Isla | 80.00 | 40.00 | 45.00 | 61.70 | 64.00 | 72.50 |
Jasmine | 95.00 | 98.00 | 100.00 | 96.00 | 100.00 | 100.00 |
Julieta | 75.00 | 82.00 | 90.00 | 74.50 | 80.80 | 82.50 |
Lavanya | 85.00 | 79.00 | 85.00 | 96.00 | 100.00 | 82.50 |
Oliver | 98.00 | 100.00 | 96.50 | 98.00 | 97.50 | 100.00 |
Elon | 83.00 | 98.00 | 87.50 | 96.00 | 100.00 | 75.00 |
Yvette | 92.50 | 65.00 | 82.50 | 83.30 | 80.00 | 100.00 |
Lile this?
data T;
HW1=1;
HW2=2;
HW3=3;
HW4=4;
HW5=5;
HW6=6;
MIN=min(of HW1-HW6);
AVG=mean(ifn(HW1=MIN,.,HW1)
,ifn(HW2=MIN,.,HW2)
,ifn(HW3=MIN,.,HW3)
,ifn(HW4=MIN,.,HW4)
,ifn(HW5=MIN,.,HW5)
,ifn(HW6=MIN,.,HW6));
run;
Method #1:
data want;
set have;
avg_without_min = (6*mean(of hw1-hw6) - min(of hw1-hw6))/5;
run;
Method B:
data want;
set have;
call sortn(of hw1-hw6);
avg_without_min=mean(of hw2-hw6);
run;
What happens if there are two values of HW1-HW6 both with the minimum value (in other words, the two are tied)? Then what?
Or:
avg_without_min = (sum(of hw1-hw6) - min(of hw1-hw6))/(n(of hw1-hw6)-1);
@ChrisNZ wrote:
Or:
avg_without_min = (sum(of hw1-hw6) - min(of hw1-hw6))/(n(of hw1-hw6)-1);
Certainly an improvement on my earlier Method #1. Handles missing values properly as well.
One more for fun, but won't scale at all.
array HW(6) HW1-HW6;
x = mean(largest(1, of HW(*)),
largest(2, of HW(*)),
...
largest(5, of HW(*));
Another method would be to transpose the data, sorting it then dropping the first record.
I'd probably use @ChrisNZ solution in reality though.
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