A-Level Maths OCR B (MEI) H640

14: Probability

#14.1

Be able to calculate the probability of an event.

*Using modelling assumptions such as equally likely outcomes.

Notation: P(A)*

#14.10

Be able to calculate conditional probabilities by formula, from tree diagrams, two-way tables, Venn diagrams or sample space diagrams.

*P(AB)=P(AB)P(B)P(A|B) = \dfrac{P(A∩B)}{P(B)}

Excludes: Finding reverse conditional probability i.e. calculating P(BA)P(B|A) given P(AB)P(A|B) and additional information.*

#14.11

Know that P(BA)=P(B)    BP(B|A) = P(B) \iff B and AA are independent.

In this case P(AB)=P(A)P(B)P(A ∩ B) = P(A)⋅P(B).

#14.2

Understand the concept of a complementary event and know that the probability of an event may be found by means of finding that of its complementary event.

Notation: AA' is the event “not-AA”.

#14.3

Be able to calculate the expected frequency of an event given its probability.

Notation: Expected frequency =nP(A)= nP(A)

#14.4

Be able to use appropriate diagrams to assist in the calculation of probabilities.

E.g. tree diagrams, sample space diagrams, Venn diagrams.

#14.5

Understand and use mutually exclusive events and independent events.

#14.6

Know to add probabilities for mutually exclusive events.

E.g. to find P(A or B)P(A~or~B) .

#14.7

Know to multiply probabilities for independent events.

E.g. to find P(A and B)P(A~and~B). Including the use of complementary events, e.g. finding the probability of at least one 6 in five throws of a dice.

#14.8

Understand and use mutually exclusive events and independent events and associated notation and definitions.

For mutually exclusive events P(AB)=0P(A ∩ B) = 0 for any pair of events.

#14.9

Be able to use Venn diagrams to assist in the calculations of probabilities. Know how to calculate probabilities for two events which are not mutually exclusive.

*Venn diagrams for up to three events. Learners should understand the relation: P(AB)=P(A)+P(B)P(AB)P(A ∪ B) = P(A) + P(B) - P(A ∩ B).

Excludes: Probability of a general or infinite number of events. Formal proofs.*

13
Data presentation and interpretation
15
Probability distributions