When the operator and interaction term are included, there are two possible calculation methods. Minitab first calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses the Satterthwaite approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
When the operator and interaction term are included, there are two possible calculation methods. Minitab first calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses the Satterthwaite approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
Term | Description |
---|---|
the α *100 percentile of the chi-square distribution with n_{q }degrees of freedom | |
J | the number of operators |
I | the number of parts |
K | the number of replicates |
There are two possible calculation methods. First, Minitab calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses an alternate approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
There are two possible calculation methods. First, Minitab calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses an alternate approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
Term | Description |
---|---|
the α *100 percentile of the chi-square distribution with n_{q }degrees of freedom | |
J | the number of operators |
I | the number of parts |
K | the number of replicates |
a | I |
b | J |
c | (IJ – I –J) |
d | IJ(K-1) |
e | I – 1 |
There are two possible calculation methods. First, Minitab calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses an alternate approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
Term | Description |
---|---|
the α *100 percentile of the chi-square distribution with n_{q }degrees of freedom | |
J | the number of operators |
I | the number of parts |
K | the number of replicates |
There are two possible calculation methods. First, Minitab calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses an alternate approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
Term | Description |
---|---|
the α *100 percentile of the chi-square distribution with n_{q }degrees of freedom | |
J | the number of operators |
I | the number of parts |
K | the number of replicates |
There are two possible calculation methods. First, Minitab calculates the bounds using the modified large-sample (MLS) method. If certain conditions are not met during the calculations, then Minitab uses an alternate approximation. To calculate the one-sided confidence bounds, replace α/2 with α in H and G.
Lower bound = 1 – (the lower bound for the ratio of the repeatability variance and the total variance)
Upper bound = 1 – (the upper bound for the ratio of the repeatability variance and the total variance)
Term | Description |
---|---|
the α *100 percentile of the chi-square distribution with n_{q }degrees of freedom | |
J | the number of operators |
I | the number of parts |
K | the number of replicates |
Lower bound = 1 – (lower bound of the CI for the ratio of the part variance and the total variance)
Upper bound = 1 – (upper bound of the CI for the ratio of the part variance and the total variance)