1 / 13

Assumptions: In addition to the assumptions that we already talked about this design assumes:

Completely Randomized Factorial Design With Two Factors. Assumptions: In addition to the assumptions that we already talked about this design assumes: Two or more factors, each factor having two or more levels.

susane
Download Presentation

Assumptions: In addition to the assumptions that we already talked about this design assumes:

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Completely Randomized Factorial Design With Two Factors • Assumptions: • In addition to the assumptions that we already talked about this design assumes: • Two or more factors, each factor having two or more levels. • All levels of each factor are investigated in combination with all levels of every other factor. If there are a (= 3) levels of factor A and b (= 3) levels of factor B then the experiment contains a x b(= 3 x 3 = 9) combinations. (the treatment levels are completely crossed). • Random assignment of experimental units to treatment combinations. Each experimental unit must be assigned to only one combination.

  2. Completely Randomized Factorial Design With Two Factors Assignment of Experimental Units: Assume we have 2 factors. Factor A has three levels a1 , a2 and a3 and factor B has three levels b1, b2, and b3 then the layout of the completely randomized design is as follows: Total sample is nab = n(3)(3) randomly assigned to the different combinations, with a minimum n = 1 (in this case we have to assume no interaction between the different factor levels).

  3. Completely Randomized Factorial Design With Two Factors Linear Model

  4. Completely Randomized Factorial Design With Two Factors

  5. Completely Randomized Factorial Design With Two Factors Means

  6. Completely Randomized Factorial Design With Two Factors Hypotheses:

  7. Completely Randomized Factorial Design With Two Factors Means

  8. Completely Randomized Factorial Design With Two Factors What are we comparing?

  9. Completely Randomized Factorial Design With Two Factors Hypotheses:

  10. Completely Randomized Factorial Design With Two Factors Means Where

  11. Completely Randomized Factorial Design With Two Factors

  12. Completely Randomized Factorial Design With Two Factors (Fixed Effects)

  13. Completely Randomized Factorial Design With Two Factors (Fixed Effects)

More Related