Calculation of the R2

Nique — Mon, 26 Jan 2026 18:19:17 GMT

Hi All,

I am looking for suggestions to solve this problem.

There are 1.313 distinct lanes (based on the below criteria):

Objective is R2= correlation of determination > 0.6 for each lane (this means also the above aggregation can be changed and outliners data points can be excluded.

But the hard rules are:

Minimum of 20 shipments per lane
Minimum 6 Months data or 9 months data or 12 months data or 18 months data;
The Key lane needs to have at least: “Origin”, “ Destination” and LT_set, Type, service, color;

The R2 is calculated for each of the 1.313 lanes as following:

LinEst_R2(Cost,KG)
LinEst_B(Cost,KG)
LinEst_M (Cost,KG)

First Problem to be solved:

I need to Identify and Exclude the outliers shipments data points (with weight or costs) to make sure the R2 is < 0.6

Not sure if this can work or how to do this but I could calculate the distance between the data point and the R2 (in a chart) and Identify and Exclude the outliers shipments data points.

2. Second Problem to be solved: To increase the chance of R2>0.6 I need to:

reduce the 1.313 distinct lanes If the R2 does not reach >0.6

This means I could eliminate some fields to aggregate the Key Lanes having a higher number of cost and weight increases the chance for an R2> 0.6

Increase or decrease the date range (months) to reach an R2>0.6 with a preferred small number of months between 6 and 18 months.

Appreciate it if you have any suggestions to solve the above points 1 or 2 or both.

Thank you,

Re: Calculation of the R2

David_Friend — Thu, 20 Oct 2022 14:32:46 GMT

@Nique did you figure this out? If not, this question may be better posted in the QlikView App Dev Community

topic Re: Calculation of the R2 in QlikView

Calculation of the R2

Re: Calculation of the R2