Check-In : Anchoring Data

Load the Anchoring Dataset; use R to define two (separate) linear models to determine whether people’s experience in the class (DV = howclass) is better predicted by:

  1. how students are doing in life (IV1 = howgo)
  2. how students are doing on the final project (IV2 = howproject).

Check-In Review (see Prof. R Script)

Experimental Methods

The Definition of Causality

  1. The cause and effect are contiguous in space and time.
  2. The cause must be prior to the effect. (no reverse causation)
  3. There must be a constant union betwixt the cause and effect. (“Tis chiefly this quality, that constitutes the relation.”) (no random chance)
  4. The same cause always produces the same effect, and the same effect never arises but from the same cause. (not “just” some third variable)

Manipulation : Watch out for Misleading Control Variables

RECAP : the manipulation (A/B Testing) :

  • researchers create multiple groups (conditions) and change ONE THING (the IV) about a person’s experience in each group & observe the result (the DV).

    • treatment / experimental condition : the IV is present (the change happens)

    • control / comparison condition : the IV is absent (the default experience / no change)

  • KEY IDEA : the comparison group matters!

    • a 3 hour stats class DECREASES boredom compared to…

    • a 3 hour stats class INCREASES boredom compared to…

Real-Life Examples of Difficult Control Conditions

Power Posing Study. Is this a fair comparison / manipulation? Why / why not?

Carney, D. R., Cuddy, A. J., & Yap, A. J. (2010). Power posing: Brief nonverbal displays affect neuroendocrine levels and risk tolerance. Psychological science, 21(10), 1363-1368.

Carney, D. R., Cuddy, A. J., & Yap, A. J. (2010). Power posing: Brief nonverbal displays affect neuroendocrine levels and risk tolerance. Psychological science, 21(10), 1363-1368.

Gratitude Study

Read the prompt below. Answer the following questions.

  1. ICE-BREAKER : What’s something that you are grateful for?
  2. What did the experimenters manipulate? Which of these were experimental and control conditions?
  3. What are some other things that differ between the experimental and control conditions (potential confounds)?
  4. What are some other (better) control conditions that you might include in this study?

Anchoring as an Experiment

Experimental Design : The Manipulation

High Condition Low Condition Control Condition

Experimental Design (Other Terms)

High Condition Low Condition Control Condition

  • outcome = THE DV = what was being measured after the manipulation?

  • manipulation = THE IV = what were ALL the things that the researcher changed about a person’s experience (across experimental conditions)?

  • random assignment = were all possible confound variables balanced across conditions?

  • double-blind = did the study avoid demand characteristics (where experimenter might have influenced behavior when giving the study) & placebo effects (where participants might have acted in a certain way because they knew they were being experimented on)?

  • generalizability = did the study have external validity? what was the effect size (\(R^2\))?

  • ethics = should researchers do this type of study? (Predict & Control)

Anchoring : Question –> Theory –> Data

  • Question : Will the number that people see BEFORE making their own rating influence their decision?

  • Theory :

    • OPTION A: People who see a HIGHER number before making their own rating will make a HIGHER number than people who see the LOWER number.
    • OPTION B : People who see a LOWER number before making their own rating will make a HIGHER number than people who see the HIGHER number.
    • OPTION C : There will be NO DIFFERENCES between the groups.

Linear Models

See Prof. R Code :)

Milestone 3 : Launch Your Study & Draft Your Measures

Milestone 3 : Launch Your Study

Milestone 3 : Draft Your Measures

Guidelines

Use Related Research as Examples

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THE END.