We can normalize data using Z-score, Z-score=(data value-mean)/standard deviation.

1. Data.

select num from TBL_TEST order by num;

NUM

----------

1

1

2

2

2

3

4

4

5

2. Calculate Z-score.

with tbl_mean_std as

(

select avg(num) m, stddev(num) std from TBL_TEST

)

select num, (num-m)/std as z_score from TBL_TEST , tbl_mean_std order by num;

NUM Z_SCORE

---------- ----------

1 -1.1785113

1 -1.1785113

2 -.47140452

2 -.47140452

2 -.47140452

3 .23570226

4 .942809042

4 .942809042

5 1.64991582

## 2 comments:

In my opinion a z-score is the number of standard deviations that a value, x, is above or below the mean.If the value of x is less than the mean, the z score is negative.If the value of x is more than the mean, the z score is positive.If the value of x equals the mean,the z score is zero.

algebra solver

That is a good interpretation of z-score. I think one benefit of z-score is that it makes variables of different scales comparable. Thank you for your input.

Jay

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