PSYC 217 Lecture Notes - Lecture 13: Factorial Experiment
Document Summary
When you have more than one iv. Factors is any variable that you expect to be related to outcome, like iv. The impact of one condition versus the impact of another condition within a factor. Effect of one factor on the outcome depends on the other factor. Ex: dr. heine wants to train his dog to sit. Command: tell half to sit, the other nothing. Presence of food: holds a treat for half of the dogs, the other half nothing. This is an example of 2 way factorial design. Number of levels of first factor by number of levels of second factor. 20 dogs with command and no treat. 20 dogs with no command and no treat. 20 dogs with no command and treat. One condition of this command factor has a different/larger impact than the different condition of this command. Marginal mean of no command is 0. 12 vs. marginal mean of command is 0. 60.
