These studies show correlation it depends on the study design Causality One of

# These studies show correlation it depends on the

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These studies show correlation, it depends on the study design • Causality: - One of the main reasons stats is used to answer questions about causality/causation • two-way tables: - Also known as a contingency table: is a frequency table that summarizes two potentially related categorical variables by displaying how many times each combination of categories occurs in the data • conditional proportions: - How to calculate conditional proportions • association: - The relationship between two variables which make them statistically dependent • confounding variable: - Is associated to both the explanatory variable and the response variable - Its effects on the response cannot be separated from those of the explanatory variable - Thus, we can’t draw any cause and effect conclusions when confounding variables are present
- Can be found in observational studies → can’t conclude causation from these kinds of studies - Doesn’t mean that explanatory isn’t influencing the response - Association may not imply causation, but can be a pretty big hint • Experiments (treatment vs control group): - Researcher deliberately manipulates the treatment variable and assigns the subject to those treatments, usually at random - Treatment group: the variable/treatment is applied to them - Control group: unaffected by the variable • random assignment: - Control confounding variables - Randomly assign people into groups, so variables that could have an effect on the response should be equalized between the two groups and therefore should not be confounding - Cause and effect are possible -

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• Spring '20

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