On Tue, 19 Feb 2013 05:37:38 -0800
Frank Chang <frankchan...@gmail.com> wrote:
> Would anyone know how to use Sqlite to calculate the streakedness of
> data? The definition of streakedness is show below. Thank you for
> your help.
>
> [EDIT] From our company's chief software architect, here is the
> requirement for a statistical measure. Could someone please define a
> statistical formula based onour architect's definition of data
> streakedness? -- February 19th 2013 8:45 AM
One way to go about this is to ask your architect the criteria by which
cases A-F were sorted. IOW, what is the definition of "less than"? It
seems to be:
0. non-streak has length zero
1. longest streak wins
2. if tied for longest streak, more instances of longest rank wins
3. if tied for #2, repeat (1,2) with next longest streak
But is that true? It seems like you might be measuring serial
correlation, for which you could conventionally use e.g.
Durbin-Watson.
To use something like your "streakedness" (not
streakiness?) measure is very difficult without some math
functions that SQLite doesn't have. Essentially, you want
sum( N * R^S )
where
R is the longest possible streak
"^" is exponentiation
S is the streak size
N is the number of streaks of length S
Using this table
select name, N, streak from cases;
name N streak
---------- ---------- ----------
A 1 13
B 1 7
B 1 6
C 1 7
C 1 6
D 1 7
D 1 3
D 1 2
E 1 7
E 1 3
F 1 7
in SQL Server, the query would be:
select name
, sum( N * power(biggest, streak) ) as rank
from cases
cross join (
select 1.0*max(streak) as biggest
from cases
) as A
group by name
order by rank desc;
name rank
---- -----------------------------------------
A 302875106592253.0
B 67575326.0
C 67575326.0
D 62750883.0
E 62750714.0
F 62748517.0
Without the power() function, you'd need a table of all possible values
of R^S, then
select name, sum(N * p.value) as rank
from cases
join powers as p
on cases.streak = p.S
where p.R = (
select 1.0*max(streak) as biggest
from cases
)
group by name, order by rank desc;
--jkl
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