5 Questions
What is the main idea behind the three observations presented in the text?
To illustrate the concept of causation in unrelated trends
What is a possible explanation for the observed relationship between two trends?
A third variable is causing the apparent relationship
What is the key takeaway from the rule 'correlation does not imply causation'?
Correlation is necessary but not sufficient for causation
What is the purpose of well-designed empirical research, according to the text?
To establish causation between variables
What is the author's main concern when presenting the three observations?
The danger of misinterpreting correlations as causal relationships
Study Notes
Independent and Dependent Variables
- Independent variable (X): the variable that is changed, controlled in the experiment, and is not affected by other variables
- Synonyms: predictors, factors, treatment variables, explanatory variables, input variables
- Dependent variable (Y): the variable being measured, explained, or predicted, and its values depend on other variables
- Synonyms: outcome or response variable
Examples of Independent and Dependent Variables
- Independent variable: Time spent sleeping before the exam
- Dependent variable: Test Score
- Independent variable: Consumption of fast food
- Dependent variable: Blood Pressure
- Independent variable: the amount of caffeine consumed
- Dependent variable: Sleep
- Independent variable: length of work week
- Dependent variable: rate of employees quitting
Association vs. Causation
- Association does not imply causation
- Causation can only be inferred from a randomized experiment
- A strong statistical relationship between two variables does not necessarily mean that one variable causes the other
Correlation vs. Causation
- Correlation: a statistical relationship between two variables, but does not imply causation
- Rule: correlation does not imply causation
- Possible explanations for correlations:
- Random chance
- A third, lurking variable that affects both variables
- Well-designed empirical research, including randomization, controlled experiments, and predictive models with multiple variables, can establish causation
Learn about inferential statistics and trend analysis with Dr. Krisztina Soreg. This quiz covers the basics of independent and dependent variables in statistical models.
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