- Estimation methods for subgroup size > 1
- Select a method for estimating the within-subgroup standard deviation when you have multiple observations in each subgroup.
- Rbar: Rbar is the average of the subgroup ranges. This method is a common estimate of the standard deviation and works best with subgroup sizes from 2 to 8.
- Sbar: Sbar is the average of the subgroup standard deviations. This method provides a more precise estimate of the standard deviation than Rbar, especially with subgroup sizes > 8.
- Pooled standard
deviation: The pooled standard deviation is the weighted average of subgroup variances, which gives larger subgroups more influence on the overall estimate. This method provides the most precise estimate of standard deviation when the process is in control.
- Estimation methods for subgroup size = 1
- Select a method for estimating the within-subgroup standard deviation when you have individual observations. When the subgroup size is 1, sample standard deviations or ranges within subgroups cannot be calculated. Instead, Minitab estimates the standard deviation using moving ranges.
- Average moving
range: The average moving range is the average value of the moving range of two or more consecutive points. This method is commonly used when the subgroup size is 1.
- Median moving
range: The median moving range is the median value of the moving range of two or more consecutive points. This method is best to use when data have extreme ranges that could influence the moving range.
- Square root of
MSSD: The square root of MSSD is the square root of the mean of the squared differences between consecutive points. Use this method when you cannot reasonably assume that at least 2 consecutive points were collected under similar conditions.
- Use moving range of
- Enter the number of observations used to calculate the moving range. The length must be ≤ 100. The default length is 2 because consecutive values have the greatest chance of being alike.
- Unbiasing constants
- You can choose to use unbiasing constants in the calculations for the within and the overall standard deviation. Unbiasing constants reduce the bias that can occur when a parameter is estimated from a small number of observations. As the number of observations increases, unbiasing constants have less effect on the calculated results.
- Use unbiasing
constants: Use unbiasing constants in the estimate of the within-subgroup standard deviation. This option applies to the Sbar, pooled standard deviation, and square root of MSSD methods.
- Use unbiasing
constants to calculate overall standard deviation: Use unbiasing constants in the estimate of the overall standard deviation.
Often, the choice to use unbiasing constants depends on company policy or industry standards.