This dashboard page describes basic statistical discrete distribution views of a selected population. It lets the user dynamically define the number of buckets to use for statistical distribution, as well as the grain in the population, and provides several dynamic representations in the results.
This report is useful to understand how the individuals of a population are distributed between the minimum and the maximum values, and to suggest the probabilities of where an individual may fall in a specific bucket. The report applies to numerous business situations:
It allows visualizing skewness of a given population versus typical distribution.
FLOOR [ (Metric Value - MIN(Metric)) / (MAX(Metric)*1.0001-MIN(Metric)) * {NumBands} ] + 1
FLOOR( ((@{Met01}{Measures.default} ) - MIN(@{Met01}{Measures.Default)) /
((MAX(@{Met01}{Measures.Default})*1.0001 - MIN(@{Met01}{Measures.Default})) * @{NumBands}{10})) + 1
[ Bin Number for Current Record * Range of the Metric / Total number of Bins ) + Value of Bottom Individual ]
Concatenated with ' - ' and
[ (Bin Number for Current Record + 1) * Range of the Metric / Total number of Bins ) + Value of Bottom Individual ]
cast(cast((
/* Bin Number for Current Record */
FLOOR(((@{Met01}{Measures.Default}) - MIN(@{Met01}{Measures.Default})) /
( (MAX(@{Met01}{Measures.Default})*1.0001 - MIN(@{Met01}{Measures.Default}))
/@{NumBands}{10} ) )
/* Range of Metrics */
* ((MAX(cast(@{Met01}{Measures.Default} as double))*1.0001 - MIN(cast(@{Met01}{Measures.Default} as double)))
/* Total Number of Bins */
/@{NumBands}{10})
/* Value of Bottom Individual */
+ MIN(cast(@{Met01}{Measures.Default} as double)))/@{Denominator}{1}
as int) as varchar(50))
/* Concatenated with */
||' - '||
cast(cast((
/* Bin Number for Current Record + 1*/
FLOOR(((cast(@{Met01}{Measures.Default} as double)) - MIN(cast(@{Met01}{Measures.Default} as double))) /
( (MAX(@{Met01}{Measures.Default})*1.0001 - MIN(@{Met01}{Measures.Default}))
/@{NumBands}{10} ) +1)
/* Range of Metrics */
* ((MAX(cast(@{Met01}{Measures.Default} as double))*1.0001 - MIN(cast(@{Met01}{Measures.Default} as double)))
/* Total Number of Bins */
/@{NumBands}{10})
/* Value of Bottom Individual */
+ MIN(cast(@{Met01}{Measures.Default} as double)))/@{Denominator}{1}
as int) as varchar(50))
Metric value divided by denominator Presentation Variable
From ((Quintile of metric )-1 ) * 20% To (Quintile of metric ) * 20%
'From' || cast ((ntile(@{Met01}{Measures.Default},5)-1)*20 as varchar (2))||' % to '|| cast ((ntile(@{Met01}
{Measures.Default},5))*20 as varchar(3)) ||'% Interval'
Rolling Sum (Metric)
rsum(@{Met01}{Measures.Default}/@{Denominator}{1})
1 (constant value)
Rolling sum (1)
Metric value / Sum(Metric Value) * 100
Rolling sum [ Metric value / Sum(Metric Value) * 100 ]
Case when (distance between metric value for current record and Avg (metric)) is minimum,
then mark all individuals in the bin with 0 else null.
max(
case when rank(-abs(avg(@{Met01}{Measures.Default} by 1)-@{Met01}{Measures.Default})) = 1 then 0 end
by
/* BIN */
(FLOOR(((cast(@{Met01}{Measures.Default} as double)) - MIN(@{Met01}{Measures.Default})) /
((MAX(@{Met01}{Measures.Default})*1.0001 - MIN(@{Met01}{Measures.Default}))/@{NumBands}{10})) + 1)
)
Median (Metric)
median(@{Met01}{Measure.Default})/@{Denominator}{1}
3 * [ mean (metric) - median(metric) ]/ standard deviation(metric)
3 * ( AVG(@{Met01}{Measures.Default})- MEDIAN(@{Met01}{Measures.Default}) ) / stddev(@{Met01}{Measures.Default})
Max (Metric) - Min (Metric)
(MAX (@{Met01}{Measures.default})-Min (@{Met01}{Measures.default}))/@{Denominator}{1}
Standard Deviation (Metric) / Mean (Metric)
stddev(@{Met01}{Measures.Default})/avg(@{Met01}{Measures.Default})*100
[Max (Metric) - Min (Metric)] / Number of Bins in the whole population
(( MAX (@{Met01}{Measures.Default})-Min (@{Met01}{Measures.Measures.Default} )) / @{NumBands}{10})/@{Denominator}{1}