Experiment Decisions

Think of the research question you were assigned to on Monday. You can read on the project page if you'd like.

1. What is a potential response variable for a study that answers this question? How could you measure it on a ratio or interval scale?
2. What is a potential explanatory variable? What conditions could you create to study this variable?
3. What might be the material you assign to these conditions?

• HW 2 grades up on Moodle
  • Plus 2 points for everyone, 13a, 16, and 17, were often missed.
  • I will be dropping the lowest HW grade at the end.
• HW 3 due Friday by midnight on Moodle! (due to snow day)

• Get into project groups and start discussing
• Informal Analysis and Six Fisher Assumptions

Categorical

• nominal: alcohol drinking (yes/no) of college students

Numerical

• ordinal: “small,” “medium,” and “large” size drinks at a movie theater.
• interval: scores on a “self-esteem” scale of middle- and upper-level managers
• ratio: students’ individual times to complete cognitive task (e.g., 2:15, 2: 21, 2:33, etc.)

See project schedule

• Simulation code/lecture.
• Get into pairs.
• Talk about where the six assumptions are present in the simulation.

We assume every observation in a similar condition is affected exactly the same. (Gets the same true score).

animals_sim <- animals %>%
  mutate(benchmark = mean(calm)) %>%
  group_by(animal) %>%
  mutate(animal_mean = mean(calm),
         aminal_effect = animal_mean - benchmark)

We add the effects as we go down the assembly line.

The interaction effect captures the possibility that conditions have non-additive effects, but it is also added to everythign else.

calm_sim = benchmark 
         + aminal_effect 
         + cue_effect 
         + interaction_effect 
         + student_effect 

The peice of code for adding error is not dependent on which condition the observations is in.

 + rnorm(64, 0, 0.65)

Takes 64 independent draws from a normal distribution.

 + rnorm(64, 0, 0.65)

It's rnorm(), and not rbinom() or rpois()…

 + rnorm(64, 0, 0.65)

The second argument is the mean.

 + rnorm(64, 0, 0.65)

• Due on Friday
• Detailed instructions HERE