Control Chart using R Integration
Summary: intapiuser initiated a discussion about creating a control chart using R Integration but provided no further details or context in their post.
Problem
You want to create a Control Chart in Sisense to study how a process changes over time. A control chart always has a central line for the average, an upper line for upper control limit and a lower control limit. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable.
Solution
Install “qicharts” package in R console.
install.packages(qicharts);
R script (Copy paste to Sisense Formula)
Center Line:
library(qicharts);
y<-c(do.call('cbind',args));
sisense_result<-qic(y,chart='i');
sisense_result$cl
Upper Control Limit:
library(qicharts);
y<-c(do.call('cbind',args));
sisense_result<-qic(y,chart='i');
sisense_result$ucl
Lower Control Limit:
library(qicharts);
y<-c(do.call('cbind',args));
sisense_result<-qic(y,chart='i');
sisense_result$lcl
Discussion
Control charts, also known as Shewhart charts or process-behavior charts, in statistical process control, are tools used to determine if a manufacturing or business process is in a state of statistical control.
References
https://www.isixsigma.com/tools-templates/control-charts/a-guide-to-control-charts
https://en.wikipedia.org/wiki/Control_chart
http://blog.minitab.com/blog/understanding-statistics/control-charts-show-you-variation-that-matters
