QlikView has a lot of statistical functions, please check your manual
Statistical Aggregation Functions in Script
correl(x-expression, y-expression)
Returns the aggregated correlation coefficient for a series of coordinates represented by paired numbers in xexpression
and y-expression iterated over a number of records as defined by a group by clause. Text values,
null values and missing values in any or both pieces of a data-pair will result in the entire data-pair to be disregarded.
Example:
Load Month, correl(X,Y) as CC from abc.csv group by Month;
stdev([distinct] expression)
Returns the standard deviation of expression over a number of records as defined by a group by clause. If the
word distinct occurs before the expression, all duplicates will be disregarded.
304 QlikView 11.20 SR8
25 Script Expressions
Example:
Load Month, stdev(Sales) as SalesStandardDeviation from abc.csv group
by Month;
linest_m (y-expression, x-expression [, y0 [, x0 ]])
returns the aggregated m value (slope) of a linear regression defined by the equation y=mx+b for a series of
coordinates represented by paired numbers in x-expression and y-expression iterated over a number of records
as defined by a group by clause. Text values, null values and missing values in any or both pieces of a datapair
will result in the entire data-pair to be disregarded.
An optional value y0 may be stated forcing the regression line to pass through the y-axis at a given point.
By stating both y0 and x0 it is possible to force the regression line to pass through a single fixed coordinate.
Unless both y0 and x0 are stated, the function requires at least two valid data-pairs to calculate. If y0 and x0
are stated, a single data pair will do.
Example:
Load Key, linest_m(Y,X) as Z from abc.csv group by Key;
linest_b (y-expression, x-expression [, y0 [, x0 ]])
returns the aggregated b value (y-intercept) of a linear regression defined by the equation y=mx+b for a series
of coordinates represented by paired numbers in x-expression and y-expression iterated over a number of records
as defined by a group by clause. Text values, null values and missing values in any or both pieces of a
data-pair will result in the entire data-pair to be disregarded.
An optional valye y0 may be stated forcing the regression line to pass through the y-axis at a given point.
By stating both y0 and x0 it is possible to force the regression line to pass through a single fixed coordinate.
Unless both y0 and x0 are stated, the function requires at least two valid data-pairs to calculate. If y0 and x0
are stated, a single data pair will do.
Example:
Load Key, linest_b(Y,X) as Z from abc.csv group by Key;
linest_r2 (y-expression, x-expression [, y0 [, x0 ]])
returns the aggregated r2 value (coefficient of determination) of a linear regression defined by the equation
y=mx+b for a series of coordinates represented by paired numbers in x-expression and y-expression iterated
over a number of records as defined by a group by clause. Text values, null values and missing values in
any or both pieces of a data-pair will result in the entire data-pair to be disregarded.
An optional valye y0 may be stated forcing the regression line to pass through the y-axis at a given point.
By stating both y0 and x0 it is possible to force the regression line to pass through a single fixed coordinate.
Unless both y0 and x0 are stated, the function requires at least two valid data-pairs to calculate. If y0 and x0
are stated, a single data pair will do.
Example:
Load Key, linest_r2(Y,X) as Z from abc.csv group by Key;
linest_sem (y-expression, x-expression [, y0 [, x0 ]])
returns the aggregated standard error of the m value of a linear regression defined by the equation y=mx+b
for a series of coordinates represented by paired numbers in x-expression and y-expression iterated over a
number of records as defined by a group by clause. Text values, null values and missing values in any or
both pieces of a data-pair will result in the entire data-pair to be disregarded.
An optional valye y0 may be stated forcing the regression line to pass through the y-axis at a given point.
By stating both y0 and x0 it is possible to force the regression line to pass through a single fixed coordinate.
Unless both y0 and x0 are stated, the function requires at least two valid data-pairs to calculate. If y0 and x0
are stated, a single data pair will do.
Example:
Load Key, linest_sem(Y,X) as Z from abc.csv group by Key;
linest_seb (y-expression, x-expression [, y0 [, x0 ]])
). Covariance would look something like:
