# Search results

1. ### Compare regression coefficients

I recommend looking at the Bland-Altman plot and the Youden plot.
2. ### Compare regression coefficients

Do you also have the true height value, or just the a & b measurements?
3. ### Nested/Hierarchical ANOVA

I hesitate to confirm this simply because I do not have full knowledge and understanding of all that you have done or not done in this study/analysis. I will say that there does not appear to be anything in this statement that contradicts what we discussed.
4. ### Best way to say something about the accuracy of a measurement

All measurement systems have an associated uncertainty, and repeatability and reproducibility variation.
5. ### Calculating Ppk and Cpk. Am I doing this right?

The control chart in Picture 2 is the standard Shewhart control chart with control limits based around the process mean (XdoubleBar). The control chart in Picture 1 is a specialized control chart with a lot of modifications: The control limits are based around the desired target value...
6. ### Calculating Ppk and Cpk. Am I doing this right?

Specifications only apply to the capability analysis (i.e., Pp/Ppk, Cp/Cpk). Tolerances have ABSOLUTELY NOTHING to do with the control charts. The control limits are based on the process variation NOT on the specifications. You can be: In control, in specification In control, out of...
7. ### Calculate required sample size

Short answer is No. Excellent idea.
8. ### Calculate required sample size

This is a link to a sample size calculator for comparing 2 independent means.
9. ### Calculate required sample size

95% confidence refers to Type 1 error (alpha risk), which is controlled by the alpha threshold you use to determine whether a p-value is statistically significant (e.g., 0.05 in your case). Power is another way of expressing the Type 2 error (beta risk), which is controlled by the sample size...
10. ### Nested/Hierarchical ANOVA

ANOVA is extremely robust against non-normality. With 100 data points, you have nothing to worry about. The only question that I would ask about this plot is the one point in the upper right. Since these are standardized residuals, that point is about 5.5 standard deviations from the predicted...
11. ### which statistical test do I need to conduct- (there are 3 variables)? *DISSERTATION HELP*

You need to provide more information. Are your variables attribute or continuous? If attribute, are they binary, ordinal, etc.?
12. ### Calculating Ppk and Cpk. Am I doing this right?

There is something to that, compared to a culture such as Japan. However, I am seeing changes in certain industry segments. For those in consumer goods that are under intense price pressure, I would agree with you. However, in industries where you must maintain high reputation to keep major...
13. ### Time Series Analysis

Has much been done since Box and Jenkins?
14. ### Calculating Ppk and Cpk. Am I doing this right?

Unfortunately, you are correct, but manufacturers are slowly coming around to realize that it is true. Trying to inspect quality in does increase costs, but designing quality in and taking variation out of the process does reduce costs.
15. ### Calculating Ppk and Cpk. Am I doing this right?

Higher quality reduces costs.
16. ### Nested/Hierarchical ANOVA

Correct. I would run the 1-way ANOVA first without transforming the data and look at the residuals plot. If the residuals vs. fitted values plot does not show an unusual dispersion pattern suggesting heteroskedacity (see plot), you do not need to transform the data. Transforms always result...
17. ### Calculating Ppk and Cpk. Am I doing this right?

Industrial statistics is all about reducing costs. Variation causes rejects, and rejects cost money. Therefore, reduce variation. Control charts identify the unusual variation (worthy of expending resources to reduce) from background variation. If the background variation is still too great...
18. ### Nested/Hierarchical ANOVA

Okay, I will refer back to my first response then. If you subtract the vehicle mean from the locations results for that specific vehicle, you will remove the vehicle to vehicle variation from the analysis. Yes, that will give you a lot of negative values, but that is not a problem because the...
19. ### Nested/Hierarchical ANOVA

So, your (HA) hypothesis is that there is a difference between locations? Vehicles are simply replicates?
20. ### Nested/Hierarchical ANOVA

I'm a little confused. In your first post, you analyzed the differences in location within a vehicle. Now you are saying that you are interested in the differences between vehicles. What is your study hypothesis?