1. Checking the data and assumptions before the final analysis.
Cleaning up your act
Checking the data and assumptions before the final analysis.
4/5/2019
AGR206

2. Topics Detection of problems: Fixing problems:
Population represented by sample.
Missing data.
Normality of errors.
Linearity and Lack of Fit.
Homogeneity of variance.
Outliers.
Univariate
Multivariate
Multicollinearity.
Fixing problems:
Transformations
4/5/2019
AGR206

3. Population and sample. Scope of regression.
4/5/2019
AGR206

4. Normality.
Usually, it is assumed that errors are normally distributed.
In JMP, obtain errors (residuals) and then use the Analyze Distributions platform.
Example: xmpl_Pyield.jmp
4/5/2019
AGR206

5. Linearity/Lack of Fit
Lack of Fit compares the variance within replicated X values to the variance around the model.
4/5/2019
AGR206

6. Lack of Fit ANOVA Table
Example: xmpl_Pyield.jmp
4/5/2019
AGR206

7. Homogeneity of Variance
Variance of errors are assumed equal.
Plot errors vs. Yhat and X’s.
Use UnEqual variance test in the Fit Y by X platform.
Example: xmpl_Pyield
4/5/2019
AGR206

8. Outliers Univariate: Multivariate: Check the studentized residual.
Compare to t(n-p, 0.001).
Or correct by Bonferroni.
Check X dimension: hii<2(m+1)/n
hii is the leverage
m is the number of X variables
n is the number of observations
Multivariate:
Mahalanobis squared distance ~ 2(m) if variables are normal.
4/5/2019
AGR206

9. Outliers Example: xmpl_UVoutl.jmp Example: xmpl_MVoutl.jmp 4/5/2019
AGR206