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learn about modern mathematics, Summaries of Mathematics

mathematics in modern world, business administration and engineering

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2023/2024

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FUNCTIONS AND RELATIONS
RELATIONS
- A relation is a set of ordered pairs
A relation may have more than 1 output for any
given input.
- The set whose elements are the first coordinates
in the ordered pairs is the domain of the relation.
- The set whose elements are the
second coordinates is the range.
- A = { (1, 1), (2, 3), (2,4)}
- Domain: {( 1, 2)} Range: {(1, 3, 4)}
RELATION IN THE REAL WORLD
- Money won after buying a lotto locket.
- The high temperature on July 1st in New York City.
Depends on the year.
- How many words your friend uses
when answering, โ€œHow are you?โ€
- The number of calories in a fast food hamburger.
- Places you can drive to with 1 gallon left in your
gas tank.
FUNCTION
-
It is a relation in which each element in
the domain is paired with exactly one element
in the range.
- A function can have no more than 1 output for
any given input.
EXAMPLES
- The amount of sodas that come out of a vending
machine. depending how much money you
insert.
- The amount of carbon left in a fossil after so
many years.
- The velocity of an object in freefall after being
dropped so many seconds, excluding air
resistance.
- The height of a person at a given time in their life.
- The intensity of a light as you slide its
dimmer switch.
FUNCTION NOTATION
- The notation f(x) defines a function named
f. This is read as โ€œy is a function of x.โ€ The
letter x represents the input value, or
independent variable. The letter y is
replaced by f(x) and represents the output
value, or dependent variable.
UNARY AND BINARY OPERATIONS
UNARY OPERATIONS
- It involves only one value or accepts one value
or operand.
BINARY OPERATIONA
- It can act on two operands โ€œ+โ€ and โ€œ โ€“ โ€
- It takes two values and include the
operations of addition,
subtraction,
multiplication, division and exponentiation.
PROPERTIES OF TWO BINARY OPERATIONS
CLOSURE OF BINARY OPERATIONS
- The product and the sum of any two real numbers
is also a real number.
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FUNCTIONS AND RELATIONS

RELATIONS

  • A relation is a set of ordered pairs A relation may have more than 1 output for any given input.
  • The set whose elements are the first coordinates in the ordered pairs is the domain of the relation.
  • The set whose elements are the second coordinates is the range.
  • A = { (1, 1), (2, 3), (2,4)}
  • Domain: {( 1, 2)} Range: {(1, 3, 4)} RELATION IN THE REAL WORLD
  • Money won after buying a lotto locket.
  • The high temperature on July 1st in New York City. Depends on the year.
  • How many words your friend uses when answering, โ€œHow are you?โ€
  • The number of calories in a fast food hamburger.
  • Places you can drive to with 1 gallon left in your gas tank. FUNCTION
  • It is a relation in which each element in the domain is paired with exactly one element in the range.
  • A function can have no more than 1 output for any given input.

EXAMPLES

  • The amount of sodas that come out of a vending machine. depending how much money you insert.
  • The amount of carbon left in a fossil after so many years.
  • The velocity of an object in freefall after being dropped so many seconds, excluding air resistance.
  • The height of a person at a given time in their life.
  • The intensity of a light as you slide its dimmer switch. FUNCTION NOTATION
  • The notation f(x) defines a function named f. This is read as โ€œy is a function of x.โ€ The letter x represents the input value, or independent variable. The letter y is replaced by f(x) and represents the output value, or dependent variable. UNARY AND BINARY OPERATIONS UNARY OPERATIONS
  • It involves only one value or accepts one value or operand. BINARY OPERATIONA
  • It can act on two operands โ€œ+โ€ and โ€œ โ€“ โ€
  • It takes two values and include the operations of addition, subtraction, multiplication, division and exponentiation. PROPERTIES OF TWO BINARY OPERATIONS CLOSURE OF BINARY OPERATIONS
  • The product and the sum of any two real numbers is also a real number.

COMMUTATIVITY OF BINARY OPERATIONS

  • Addition and multiplication of any two real numbers is commutative as seen in their mathematical symbols: Example: x + y = y + x and x โ— y = y โ— x ASSOCIATIVITY OF BINARY OPERATIONS
  • Given any three real numbers you may take any two and perform addition or multiplication as the case maybe and you will end with the same answer. DISTRIBUTIVITY OF BINARY OPERATIONS
  • Distributivity applies when multiplication is performed on a group of two numbers added or subtracted together. Example: z(x ยฑ y) = zx ยฑ zy IDENTITY ELEMENTS OF BINARY FUNCTIONS
  • An element of the set of real numbers is an identity element for addition / multiplication if x + e = e + x = x and x โ— e = e โ— x = x This means that the identity is the number that you add to any real number and the result will be the same real number. INVERSES OF BINARY OPERATIONS

OPERATION ON

FUNCTIONS SUM OF

FUNCTIONS

  • The sum of two functions is found by adding the two functions together. We can add two functions as: (f + g)(x) = f(x) + g(x) Example: f(x) = 2x2 + 3x โ€“ 4 and g(x) = 2x + 3 (f + g)(x) = (2x2 + 3x โ€“ 4) + (2x + 3) = 2x2 + 5x โ€“ 1 DIFFERENCE OF FUNCTION (f โ€“ g)(x) = f(x) โ€“ g(x) Example: f(x) = 2x2 + 3x โ€“ 4 and g(x) = 2x + 3 (f โ€“ g)(x) = (2x2 + 3x โ€“ 4) โ€“ (2x + 3) = 2x2 + x โ€“ 7 PRODUCT OF FUNCTION (fโ€ขg)(x) = f(x)โ€ขg(x) Example: f(x) = 3x โ€“ 5 and g(x) = x (fโ€ขg)(x) = (3x โ€“ 5)โ€ข(x) = 3x2 โ€“ 5x QUOTIENT OF FUNCTION (f/g)(x) = f(x)/g(x) Example: f(x) = 3x2 + 4x โ€“ 3 and g(x) = x (f/g) (x) = (3x2 + 4x โ€“ 3)/x = 3x + 4 โ€“ 3/x PROBLEM SOLVING STRATEGIES GEORGE POLYA 1887-
  • The father of problem-solving
  • A mathematics educator who strongly believed that the skill of problem solving can be taught
  • To use the guess-check strategy, one follows these steps:
  • Continuing the procedure until the correct answer is obtained
  • Note: Use logical reasoning to minimize the number of trials. STRATEGY 4: ACT IT OUT
  • Acting out the Problem is a strategy in which people physically act out what is taking place in a word problem.
  • One may use people or objects exactly as described in the problem, or you might use items that represent the people or objects.
  • Using this strategy, people visualize and simulate the actions described in the problem. STRATEGY 5: WORK BACKWARDS
  • The โ€œWork Backwardโ€ method works well for problems where a series of operations is done on an unknown number and youโ€™re only given the result.
  • To use this method, start with the result and apply the operations in reverse order until you find the starting number. PROBLEM SOLVING AND REASONING INDUCTIVE REASONING
  • It is a type of reasoning that uses specific examples to reach a general conclusion.
  • The conclusion formed by using inductive reasoning is called a conjecture. Note: A conjecture is an idea that may or may not be correct. COUNTEREXAMPLE
  • Note: Not all conjectures turn out to be true. You can prove that a conjecture is false by finding one counterexample.
  • A counterexample to a conjecture is an example for which the conjecture is incorrect. DEDUCTIVE REASONING
  • It is a type of reasoning that uses general procedures and principles to reach a conclusion. - It is the process of reaching a general conclusion by applying general assumptions, procedures, or principles. SOME GENERALIZED PRINCIPLES - PEMDAS - Property of Real Numbers - Property of Inequality - Postulates - Theorems LOGIC PUZZLE - Logic puzzles can be solved by using deductive reasoning and a chart that enables us to display the given information in a visual manner.

INDUCTIVE VS DEDUCTIVE

Inductive

  • Reaching conclusions based on a series of observations.
  • Conjecture may or may not be valid or uncertain. EXAMPLES For the last two years, you gave your dad socks as a Christmas present, and he was happy with them. This year, you have bought your dad more socks and conclude that he is going to be happy with the gift. A stockbroker notices that a company's stock decreased significantly during the summer for the last four years. Therefore, he advises his clients not to invest in that company during the summer. Deductive
  • Reaching conclusions based on previously known facts.
  • Conjecture are correct and valid or certain EXAMPLES You know that all doctors hold a doctorate. You meet someone called Dr Jones and conclude that Dr Jones has a doctorate. People from France speak French. You have a new colleague who you know is from France. Therefore, you greet them in French. FORMS OF DEDUCTIVE REASONING
  1. Hypothetical syllogism
  2. Categorical Syllogism HYPOTHETICAL SYLLOGISM
  • It is a type of deductive reasoning consisting of a conditional major premise, an unconditional minor premise, and an unconditional conclusion. Types of hypothetical syllogism
  • Modus Ponens
  • It is a hypothetical syllogism with the form If ๐‘ then ๐‘ž, and ๐‘, Therefore, ๐‘ž. where ๐‘ and ๐‘ž are distinct statements. EXAMPLE: If Allison vacations in Paris, she will have to win a scholarship. Allison is vacationing in Paris. Therefore, Allison won a scholarship.
    • Modus Tollens
    • It is a hypothetical syllogism with the form If ๐‘ then ๐‘ž, and ยฌ๐‘ž, Therefore, ยฌ๐‘. where ๐‘ and ๐‘ž are distinct statements. EXAMPLE: If the traffic is bad, Jim will be late to the movie. Jim was not late for the movie. Therefore, the traffic was not bad. CATEGORICAL SYLLOGISM
    • It is a form of deductive reasoning wherein a categorical conclusion is based on two categorical premises.
    • There are four types of propositions that are used in the syllogism:
      • Positive Universal: โ€œAll are...โ€ (A)
      • Negative Universal: โ€œNone are...โ€ (E)
      • Positive Existential: โ€œSome are...โ€ (I)
      • Negative Existential: โ€œSome are not...โ€ (O)
    • There are three types of propositions will be used to create an argument in the following standard form as defined by:
      • Major premise (universal quantifier)
      • Minor premise (existential quantifier)
      • Conclusion (universal or existential)
    • It is also denoted by All ๐‘ are ๐‘ž. ๐‘Ÿ is ๐‘. Therefore, ๐‘Ÿ is ๐‘ž. EXAMPLE: All fish are sea creatures. Every shark is a fish. Therefore, every shark is a sea creature.

Independent Variable (IV)

  • Is the variable that is systematically manipulated by the investigator Dependent Variable (DV)
  • Is the variable that the investigator measures to determine the effects of the independent variable Example : A science student wants to know the amount of water needed for the growth of a specific plant. Independent Variable : amount of water exposed to the plant Dependent Variable : growth of the specific plant A scientist studies the impact of Drug A on cancer cells. Independent Variable : use of Drug A Dependent Variable : impact on cancer cells A pathologist studies the reaction of Salmonella bacteria to a new antibiotic developed. Independent Variable : use of the new antibiotic Dependent Variable : reaction of Salmonella Bacteria Descriptive Statistics
  • It involves the collection and classification of data. Keywords - AVERAGE & PERCENTAGE Example:
    • A teacher wishes to determine the percentage of students who passed the examination
    • A bowler wants to find his bowling average for the past 10 games Inferential Statistics
    • It involves the analysis and interpretation of data. Keywords - PREDICT & ESTIMATE Example:
    • A manager would like to predict based on previous yearsโ€™ sales, the sales performance of a company for the next five years. - A politician would like to estimate, based on an opinion poll, his chance for winning in the upcoming senatorial election. POPULATION AND SAMPLE Population
  • Set of measurements corresponding to the entire collection of units about which the information is sought; group of objects/subjects about which conclusions are to be drawn. Sample
  • Set of individuals selected from a population, usually intended to represent the population in a research study Identify the population and the sample. In a recent survey, 614 small business owners in the National Capital Region were asked whether they thought their companyโ€™s Facebook presence was valuable. Population : The set of all business owners in the National Capital Region. Sample : The participating 614 business owners in the National Capital Region. SAMPLE SIZE

Data

  • Are measurements or observations. A data set is a collection of measurements or observations. Datum
  • Is a single measurement or observation and is commonly called a score or raw score. Qualitative Data
  • Data that deal with categories or attributes Quantitative Data
  • Data that deals with numerical values Examples Qualitative Data : (1) Color of skin (2) Courses in Computer Engineering Quantitative Data : (3) Number of units in one semester (4) Grade point average Discrete Data
  • Data that are obtained by counting Continuous Data
  • Data that are obtained by measuring EXAMPLES Discrete Data (1) number of students in the classroom (2) number of cars in the parking lot