Differing P Values

[#1]

Hello! 

 I used the software for a fractional factorial screening design. I had three different factors to evaluate all of which were categorical. My data was collected/recorded using Pass or Fail for the one Response. I am trying to find the proper way to analyze this data. I am trying to get data that shows which factor had the most effect on the Pass or Fail Rate of the Response

 I saw a tutorial online that said to just right click model and hit run script. I then changed the personality to to Response Screening  After running the script I got a table which is Photo A below. I think for my purposes the Effect Size column is probably the most important. But I am confused because I followed another method one of my team members uses which is going to Analyze and Fit Model and I have included a screenshot below of what the Set Up looks like [Photo B] and the results are in photo C but there is a significant difference between the P Values recorded and I am unsure of why there is a significant different and which would be considered correct.  

Photo A

photo B 

Photo C

Thanks in advance!

[#2 · Accepted solution]

The Response Screening runs 3 independent analyses, where the Fit Model takes all 3 factors into account when analyzing the data.