Explain conditional probability and independence in everyday language and situations.
Measure how conditioning changes likelihood
Problem
For two draws without replacement from \(3\) red and \(2\) blue marbles, compare \(P(\text{second}~\text{red})=3/5\) with \(P(\text{second}~\text{red}~|~\text{first}~\text{red})=2/4\). Classify the events without claiming causation.
Big Picture
What this problem is really about
Without replacement, the first outcome changes both favorable and total counts for the second draw. We’ll compute the original second-red probability, update the bag after a first red, compute the conditional rate, measure the percentage-point change, and interpret that change as dependence rather than causation.
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