XmR Trend Chart Formulas

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The XmR Trend chart can help you evaluate process performance using variable data when there is only one measurement per period and the data may contain trends (e.g increasing cost due to inflation, decreasing cost due to technology, etc).

Here is the formula used to calculate the Trend chart in the QI Macros.

(Source: Statistical Methods for the Process Industries, W McNeese and R Klein, ASQ Press, Milwaukee, pg. 280-290)

UCL and LCL are the same as for the XmR chart formulas.

The only difference is how the X center line (CL) is calculated using linear regression to give you the slope of the trend and a y-intercept value: "b", calculated as follows:

time(i)=t_i=1,2,3,4....k for each X value
m=slope
b=intercept

The XmR trend then calculates the linear correlation coefficient (R_yx) for the degrees of freedom (df=k-2).

If R_yx is greater than the probability for this degree of freedom, you have a "significant correlation" between x and y. (Probability that you will conclude there is no correlation when there is one = alpha = 0.05).

If R_yx² is greater than 0.80, then the correlation indicates a "useful fit."

What does this mean?

Significant correlation - A measure of x versus y. Is the relationship between x and y statistically significant? This is a measure of how well the trend line reflects the relationship between x and y.

Usefit Fit - Even if there is a significant correlation above this asks the question - Is it useful? Can I make an assumption or prediction about y based on past history?

A measure of the variation in x vs the variation in y.
This is a measure of how the points vary within the control limits.

(Source: Statistical Methods for the Process Industries, W. McNeese, ASQ Quality Press, Milwaukee)

Other control chart formulas

The XmR Trend chart is just one of the tools included in the QI Macros for Excel SPC Software for Excel.

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