Pre-U Further Mathematics CAIE

This subject is broken down into 47 topics in 4 modules:

  1. Pure Mathematics 13 topics
  2. Mechanics 11 topics
  3. Statistics 13 topics
  4. Discrete Mathematics 10 topics
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This page was last modified on 28 September 2024.

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Further Mathematics

Pure Mathematics

Proof

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Proof

Proof

Understanding Proof

  • The process of proof is a logical methodology applied in mathematics to verify the truth of an existing statement or theory.
  • A mathematical proof is a deductive argument for a mathematical statement which, theoretically, could be checked by a competent mathematician.
  • Using logic and assumptions, we can identify and systematically verify every operation.
  • The primary goal of proof is to establish absolute truth, independent of individual beliefs.

Direct Proof

  • A direct proof is the simplest form of proof, where you start at the premises and use logical operations to reach the conclusion.
  • Direct proofs most often use the properties of mathematics such as the properties of equality or definitions or theorems.
  • Direct proofs make use of simple, clear and logical steps that effectively lead to the proposition in question.
  • Establishing a series of these interconnected certainties can provide an absolute verification of the statement.

Indirect Proof

  • An indirect proof, also known as proof by contradiction, begins with an assumption that is the opposite of the statement to be proven.
  • If this assumption leads to a contradiction, then the original statement must be correct.
  • Contradiction is a powerful tool in indirect proof. It allows us to assume the reverse of our desired outcome, and then to demonstrate that this assumption inevitably leads to a logical inconsistency.

Existence Proof

  • An existence proof demonstrates that at least one instance of a particular statement is true.
  • This type of proof often uses construction or contradiction to prove that a mathematical entity with a certain property exists.
  • Existence proofs are often less specific, as they don't necessarily provide a method for finding the entity, just proving that it exists.

Uniqueness Proof

  • A uniqueness proof shows that only one instance of a particular mathematical statement is true.
  • Often used in geometry or calculus, these proofs usually assume that two objects exist and are the same, leading to a contradiction.
  • Ultimately, uniqueness proofs establish that a single, unique solution exists, which solidifies the statement's validity.

Proof by Induction

  • Proof by induction is a method of proof in mathematics where a statement is shown to be true for all natural numbers.
  • The process involves establishing the truth of a statement for an initial value (commonly 1 or 0) and then proving that if it holds true for a certain case, then it also holds true for the next immediate case.
  • This method is particularly useful for proving statements about sequences or series and often used with inequalities.

Mathematic Notations in Proof

  • Use of maths notations in proofs can vastly improve the clarity and conciseness.
  • Familiarising yourself with these notations — such as equalities, inequalities, summation, product notation, etc. — is critical to understanding and constructing mathematical proofs.

Course material for Further Mathematics, module Pure Mathematics, topic Proof

Further Mathematics

Statistics

Probability

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Probability

Probability

Definition and Basic Principles

  • Probability refers to the chance or likelihood of an event or a series of events occurring. It is a measure of the uncertainty of outcomes in different situations.
  • Probability can take any value from 0 to 1. A probability of 0 means an event will never occur, and a probability of 1 means an event will definitely occur.
  • Probabilities can be expressed as fractions, decimals, or percentages.

Calculating Probability

  • The probability of an event occurring can be calculated by dividing the number of ways an event can occur by the total number of possible outcomes.
  • For mutually exclusive events, the probability of either event happening can be calculated by adding the probabilities of each event. This is known as the addition rule for probabilities.
  • For independent events, the probability of both events happening can be calculated by multiplying the probabilities of each event. This is known as the multiplication rule for probabilities.

Probability Distributions

  • A probability distribution is a function or rule that assigns probabilities to each possible outcome of a random experiment.
  • The sum of the probabilities in a probability distribution must equal 1.
  • There are different types of probability distributions like Binomial Distribution, Normal Distribution etc.

Conditional Probability

  • Conditional probability is the probability of an event given that another event has occurred.
  • It is denoted by P(A|B), which is the probability of event A occurring given that event B has occurred. The formula to find it is P(A ∩ B) / P(B), if P(B) ≠ 0.

The Complementary Rule

  • The probability that an event does not occur is 1 minus the probability that it does occur. This is termed the complementary rule and can be written as P(A') = 1 - P(A), where A' is the complementary event of A.

The Law of Total Probability and Bayes' Theorem

  • The Law of Total Probability is a fundamental rule relating marginal probabilities and conditional probabilities. It provides a way to break up the probability of an event into a set of mutually exclusive scenarios.
  • Bayes' Theorem is a way to find a probability when we know certain other probabilities. It is used in numerous fields, including medicine, computer science, and statistics.

Experimental Probability

  • Experimental probability refers to the probability of an event occurring when an experiment was conducted. It is calculated by dividing the number of times the event occurred by the total number of trials.
  • As the number of trials increases, the experimental probability tends to approach the theoretical probability. This is called the Law of Large Numbers.

Course material for Further Mathematics, module Statistics, topic Probability

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