Data & Causation Quiz
16 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is a critical factor for establishing causation in research?

  • Conducting surveys with open-ended questions
  • Analyzing historical data trends
  • Using a larger sample size
  • Running experiments with random assignment (correct)
  • Which of the following statements best illustrates the gambler's fallacy?

  • Investors choosing stocks that have consistently risen over the past year.
  • A consumer believing a product will likely go on sale after buying it at full price.
  • A teacher assuming students will perform poorly after a string of high test scores.
  • A player betting on red after five consecutive blacks at a roulette table. (correct)
  • What does 'random sampling' achieve in a study?

  • Allows for generalizability of results to a larger population (correct)
  • Controls for the influence of confounding variables
  • Improves the validity of the data collected
  • Ensures a diverse participant selection without bias
  • In high chance environments, how should outcomes be incentivized?

    <p>By rewarding consistent performance regardless of outcomes</p> Signup and view all the answers

    What correlation value indicates stability between two measures of the same phenomenon?

    <p>Greater than 0.7</p> Signup and view all the answers

    Which approach emphasizes specific recent conditions in forecasts?

    <p>This Time is Different</p> Signup and view all the answers

    Which of the following best describes the statement 'Chance does not even out'?

    <p>Past performances influence the perception of future outcomes.</p> Signup and view all the answers

    What should be considered when evaluating potential investments according to the 'What Usually Happens' approach?

    <p>Historical performance of similar funds</p> Signup and view all the answers

    What is the consequence of a smaller sample size in research?

    <p>Less reliable knowledge</p> Signup and view all the answers

    What phenomenon describes the tendency for extreme performances to normalize over time?

    <p>Regression to the mean</p> Signup and view all the answers

    What does the availability heuristic refer to?

    <p>Bias based on recent or frequently considered information</p> Signup and view all the answers

    Which bias involves the tendency to believe we could have predicted an outcome after it has occurred?

    <p>Hindsight bias</p> Signup and view all the answers

    What effect describes the phenomenon where better performance is expected after being publicly recognized?

    <p>Sports illustrated jinx</p> Signup and view all the answers

    What does overplacement refer to in the context of self-assessment?

    <p>Believing oneself to be better than the average in easy tasks</p> Signup and view all the answers

    What is the main issue with feedback that is insufficient for learning?

    <p>It increases overconfidence</p> Signup and view all the answers

    Which principle indicates that relationships at one level of aggregation may disappear or reverse at another level?

    <p>Simpsons Paradox</p> Signup and view all the answers

    Study Notes

    Data & Causation

    • Be wary of the data you see - make sure it is accurate and relevant to the question you are asking.
    • Correlation does not imply causation.
    • Decisions are forecasts of the future.
    • When trying to understand why something is performing well or poorly, look for data on consumer demand.
    • The best way to establish causation is to run an experiment - Random assignment is crucial.
    • Randomly assigning participants to condition groups allows for causality to be established.
    • Randomly sampling units to include in the study allows for generalizability to be established.

    Chance & Human-Generated Data

    • Chance is streakier than you think - we are usually wrong when it comes to chance.
    • Human-generated data is not streaky enough.
    • People tend to see patterns in chance events - the Gamblers Fallacy.
    • The Gamblers Fallacy: People are less likely to bet on numbers that just won.
    • When we believe that success/fail rate is unchanging, the probability of failure seems greater after a string of successes - the belief chance will correct itself.
    • Chance does not even out.

    Forecasts

    • Two approaches to forecasts:
      • This time is different: use as much information on the topic to determine why this situation is different and therefore a good reason to invest.
      • What Usually happens: Identify all similar funds with the same timeframe and see how they performed.
    • Start with "What Usually happens" and then adjust for the possibility that this time could be different.
    • To test whether you are in a high chance environment, correlate two measures of the same thing.
    • A correlation higher than .7 suggests a stable environment.
    • In high chance environments you should
      • Do not incentivize outcomes, but instead incentivise other indicators of competence.
      • Do not choose between options based on recent past outcomes.
      • Prioritize accumulating opportunities over trying to choose the best one.
    • The sample size is crucial for accurate results: Less sample size less reliable knowledge.

    Regression to the Mean

    • Good performers tend to decline, bad performers tend to improve.
    • When one side has extreme values, usually, on average, the other side has less extreme values.
    • Regression to the mean: If something is doing abnormally well or abnormally bad then it's bound to even out.
    • For a performance to be extremely good/bad luck has to be unusually good/bad.
    • Sports illustrated jinx: Athletes would think that once they are sponsored they do worse.

    Simpson's Paradox

    • Simpson's Paradox: A relationship at one level of aggregation disappears or reverses at a different level of aggregation.

    Beware of...

    • When looking at correlations beware of:
      • Regression to the mean
      • Selection (small range, selection distortion)
      • Aggregation (Simpsons Paradox)

    Heuristics

    • Heuristics are mental shortcuts or rules of thumb - good enough.
    • Heuristics are prone to systematic error
    • Availability: When prompted with an option it biases your original guess / opinion - Information that came to mind recently or frequently - or is the focus of our attention.
    • Anchoring: The estimates of unknown quantities are easily biased by what values they consider.
    • Representativeness: Given the base rate of a wanted group + how much they seem to be in that wanted group

    Cognitive Biases

    • Egocentric Bias: We fail to realize what life is like from others who do not share our knowledge or perspective.
    • Hindsight Bias: Once an outcome has occurred, we overestimate the likelihood that we would have predicted that outcome in advance.
    • Curse of Knowledge: When we have private information, we expect the uninformed to behave as if they know what we know
    • Overconfidence: Unwarranted confidence.
    • Overplacement: the "better than average effect" - Overplacement happens on easy tasks and underplacement happens on hard tasks.
    • OverPrecision: we often don't account for how much we don't know.
    • Knowledge in a domain does not easily or often translate into being able to make accurate predictions of uncertain events...But it does translate to unwarranted confidence in the ability

    Feedback

    • We need good feedback to learn.
    • Feedback must be:
      • Reliable:
      • Fast:
      • Detailed:

    Studying That Suits You

    Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

    Quiz Team

    Related Documents

    PSYC10 Study PDF

    Description

    Test your understanding of data accuracy, correlation vs causation, and the significance of random assignment in experiments. This quiz will challenge your knowledge of how to interpret human-generated data and the implications of chance in analysis. Dive into the concepts of decision-making based on data.

    More Like This

    week 1.1 IRM
    12 questions

    week 1.1 IRM

    LuckiestForethought avatar
    LuckiestForethought
    Data Analysis Flashcards
    10 questions
    Media Bias and Facebook User Data Analysis
    16 questions
    Use Quizgecko on...
    Browser
    Browser