Aggregated (Advanced) Operators
First
calculates the first value of a measure based on chronological order. The first
parameter specifies the measure. The second parameter specifies the sequence
data item that is used to determine the chronological order. The sequence data item can be
either a date or time data item or a
numeric data item. The third parameter specifies whether missing values are included. Select _IncludeMissing_
to include missing values or select _ExcludeMissing_ to exclude missing values.
Note: If there are multiple measure
values for the first value of the sequence data item, then the minimum
measure value is selected.
Note: The First aggregation always
calculates measure values by using the sequence data item that you
specify. If your visualization or report object uses a different date
or time data item, then the results might be misleading to viewers
who do not know the expression for the aggregated data item.
Kurtosis
calculates the kurtosis
of a measure. The kurtosis value indicates how peaked the distribution
is. A larger value indicates a more sharply peaked distribution. A
smaller value indicates a flatter distribution.
Last
calculates the last value of a measure based on chronological order. The first parameter
specifies the measure. The second parameter specifies the sequence data item that
is used to determine the chronological order. The sequence data item can be
either a date or time data item or a numeric data item. The third parameter specifies
whether missing values are included. Select _IncludeMissing_
to include missing values or select _ExcludeMissing_ to exclude missing values.
Note: If there are multiple measure
values for the last value of the sequence data item, then the minimum
measure value is selected.
Note: The Last aggregation always
calculates measure values by using the sequence data item that you
specify. If your visualization or report object uses a different date
or time data item, then the results might be misleading to viewers
who do not know the expression for the aggregated data item.
Percentile
calculates the specified
percentile of a measure. Specify a number between 0 and 100. For example, 85 specifies the 85th
percentile, the value for which 85% of the values are lower.
PvalT
calculates the probability
of observing the t statistic
value or a more extreme value. A small value indicates that the mean
is likely not equal to zero.
Skewness
calculates the
skewness of a measure. Skewness indicates the distribution of values. A positive value indicates
that the distribution is heavier for values greater than the mean. A negative value
indicates that the distribution is heavier for values less than the mean.
TStat
calculates the Student’s t statistic
for a measure, assuming a mean value of zero.
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Last updated: January 8, 2019