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- https://stats.libretexts.org/Workbench/Introduction_to_Statistical_Methods_(Yuba_College)/05%3A_Probability/5.08%3A_Chapter_5_FormulasComplement Rules: P(A) + P(A C ) = 1 P(A) = 1 – P(A C ) P(A C ) = 1 – P(A) Mutually Exclusive Events: P(A ∩ B) = 0 Union Rule: P(A U B) = P(A) + P(B) – P(A ∩ B) Independent Events: P(A ∩ B) = P(A) ‧ P...Complement Rules: P(A) + P(A C ) = 1 P(A) = 1 – P(A C ) P(A C ) = 1 – P(A) Mutually Exclusive Events: P(A ∩ B) = 0 Union Rule: P(A U B) = P(A) + P(B) – P(A ∩ B) Independent Events: P(A ∩ B) = P(A) ‧ P(B) Intersection Rule: P(A ∩ B) = P(A) ‧ P(B|A) Conditional Probability Rule: \(P(A \mid B)=\frac{P(A \cap B)}{P(B)}\) Fundamental Counting Rule: m 1 ·m 2 ···m n Factorial Rule: n! = n·(n – 1)·(n – 2)···3·2·1 Combination Rule: \({ }_{\mathrm{n}} \mathrm{C}_{\mathrm{r}}=\frac{n !}{(r !(n-r) !)}\)
- https://stats.libretexts.org/Courses/Fullerton_College/Math_120%3A__Introductory_Statistics_(Ikeda)/03%3A_Probability/3.08%3A_Chapter_3_Formulastheoretical probability (classical approach): the probability calculated from the number of favorable outcomes divided by the total number of outcomes when each outcome has an equal probability indepe...theoretical probability (classical approach): the probability calculated from the number of favorable outcomes divided by the total number of outcomes when each outcome has an equal probability independent events: two events that are not related and the outcome of one event does not affect the probability of the other event dependent events: two events that are related and the outcome of one event does affect the probability of the other event
- https://stats.libretexts.org/Workbench/Statistics_for_Behavioral_Science_Majors/03%3A_Probability/3.08%3A_Probability_FormulasComplement Rules: P(A) + P(A C ) = 1 P(A) = 1 – P(A C ) P(A C ) = 1 – P(A) Mutually Exclusive Events: P(A ∩ B) = 0 Union Rule: P(A U B) = P(A) + P(B) – P(A ∩ B) Independent Events: P(A ∩ B) = P(A) ‧ P...Complement Rules: P(A) + P(A C ) = 1 P(A) = 1 – P(A C ) P(A C ) = 1 – P(A) Mutually Exclusive Events: P(A ∩ B) = 0 Union Rule: P(A U B) = P(A) + P(B) – P(A ∩ B) Independent Events: P(A ∩ B) = P(A) ‧ P(B) Intersection Rule: P(A ∩ B) = P(A) ‧ P(B|A) Conditional Probability Rule: \(P(A \mid B)=\frac{P(A \cap B)}{P(B)}\) Fundamental Counting Rule: m 1 ·m 2 ···m n Factorial Rule: n! = n·(n – 1)·(n – 2)···3·2·1 Combination Rule: \({ }_{\mathrm{n}} \mathrm{C}_{\mathrm{r}}=\frac{n !}{(r !(n-r) !)}\)
