A technique to compare the F value of the factor/level with a F distribution value is called:
A) fraction factorials
B) orthogonal design
C) analysis of variance
D) full factorials

Question

Quizplus · Accepted Answer

Analysis of variance (ANOVA) involves testing the significance of the variation in a response variable that is attributable to different factors or levels. The F-value is the ratio of two variances, one representing the variation between the groups or treatments and the other representing the variation within the groups or treatments. To determine whether the F-value is statistically significant, it is compared to a critical value from an F distribution, which depends on the degrees of freedom and the level of significance. Therefore, ANOVA involves comparing F-values to F-distribution values. Fractional factorials, orthogonal designs, and full factorials are different experimental design strategies that can be used to plan the levels and combinations of different variables, but they do not directly involve comparing F-values to F-distribution values.

A Technique to Compare the F Value of the Factor/level