DOCSLIB.ORG

Sections 2.1, 2.2, 2.3, 2.4 2.1 the Addition Property of Equality 2.2

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Sections 2.1, 2.2, 2.3, 2.4 2.1 the Addition Property of Equality 2.2 Sections 2.1, 2.2, 2.3, 2.4 2.1 The Addition Property of Equality 2.2 The Multiplication Property of Equality 2.3 More on Solving Linear Equations 2.4 An Introduction to Applications of Linear Equations The Addition Property of Equality In chapter 1, we saw that there was a difference between an expression and an equation. Linear Equations in one variable: Ax + B = C To solve a linear equation means to find the value of the variable that makes the equation true. Some basic properties that allow you to solve a linear equation First, think of any equation as a scale balance. Almost any mathematical operation is legitimate as long as you perform the same operation on BOTH SIDES of the equal sign. 1. The addition property of equality: If A = B, and if C is any real number, then A + C = B + C For example: if x = 5, then x + 2 = 5 + 2 But more useful: if x -2 = 3, then 2. The subtraction property of equality: if A = B and if C is any real number, then A – C = B – C For example: if x +2 = 7, then 3. The multiplication property of equality: If A, B, and C, (C ≠ 0) , represent real numbers, then if A = B, then AC =BC 1 For example: x = 8 4 4. The division property of equality: If A, B, and C, (C ≠ 0) represent A B real numbers, and A = B, then = C C For example: 3x = 18 ***The important thing to remember is that when you solve an equation is that you are trying to get all the variables on one side and all the numbers on the other. It doesn’t matter if the variable is left on the left or right side of the equation*** Examples: Addition/Subtraction Property of Equality 1. x – 8 = 9 2. x + 45 = 24 3. 8 + k = -4 4. 3 = z + 17 5. 3x = 2x + 17 6. 8t +5 = 7t Examples of Multiplication/Division Property of Equality 7. 8x = 24 8. -8x = -64 9. 5x = 0 10. –t = 14 k 11. = −3 8 5 4 12. −d = 6 9 13. 9p – 13p= 24 Using the rules together: 1. Simplify the expression. What I mean by that is distribute and remove any parentheses in the problem. Another thing to be aware of: If you have a coefficient that is a fraction, you can multiply by the least common multiple to “Clear the fractions”. We will do an example that involves this. 2. Add/subtract any constants to remove them from one side of the equation. Remember to perform the operation on both sides of the equation 3. Add/subtract any variables so that they are on the other side of the equation from the constants. Again, remember to perform the operation on both sides of the equation. 4. Multiply or divide both sides of the equation by a constant that makes the coefficient on the variable a 1. 5. When you make it to 1x = #, you have your solution! Examples: Examples of using the rules together 14. −5()() 3w − 3 + 1 + 16w = 0 15. -5p + 4 = 19 16. 2q + 3 = 4q – 9 17. 7()p− 2 + p = 2 p + 4 18. 2− 3())( 2 + 6z = 4 z + 1 + 18 1 2 19. ()x+3 −() x +1 = − 2 4 3 Section 2.4 is an introduction to Applications of Linear Equations Application problems are what you may think of as “word problems”. First we will discuss a good general approach to setting up application problems as equations and then we will work on solving them. 6-step method to solving application problems Examples: 1. If 5 is added to the product of 9 and a number, the result is 19 less than the number. Find the number. 2. In the 2006 Winter Olympics in Torino, Italy, Canada won 5 more medals than Norway. The two countries won a total of 43 medals. How many medals did each country win? 3. A piece of pipe is 50 in. long. It is cut into three pieces. The longest piece is 10 in. longer than the middle sized piece and the shortest piece measures 5 in. less than the middle sized piece. Find the length of the three pieces. 4. Find two consecutive even integers such that 6 times the lesser added to the greater gives a sum of 86. .
Load more

Recommended publications
  • Reasoning About Equations Using Equality
    Mathematics Instructional Plan – Grade 4 Reasoning About Equations Using Equality Strand: Patterns, Functions, Algebra Topic: Using reasoning to assess the equality in closed and open arithmetic equations Primary SOL: 4.16 The student will recognize and demonstrate the meaning of equality in an equation. Related SOL: 4.4a Materials: Partners Explore Equality and Equations activity sheet (attached) Vocabulary equal symbol (=), equality, equation, expression, not equal symbol (≠), number sentence, open number sentence, reasoning Student/Teacher Actions: What should students be doing? What should teachers be doing? 1. Activate students’ prior knowledge about the equal sign. Formally assess what students already know and what misconceptions they have. Ask students to open their notebooks to a clean sheet of paper and draw lines to divide the sheet into thirds as shown below. Create a poster of the same graphic organizer for the room. This activity should take no more than 10 minutes; it is not a teaching opportunity but simply a data- collection activity. Equality and the Equal Sign (=) I know that- I wonder if- I learned that- 1 1 1 a. Let students know they will be creating a graphic organizer about equality and the equal sign; that is, what it means and how it is used. The organizer is to help them keep track of what they know, what they wonder, and what they learn. The “I know that” column is where they can write things they are pretty sure are correct. The “I wonder if” column is where they can write things they have questions about and also where they can put things they think may be true but they are not sure.
    [Show full text]
  • First-Order Logic
    Chapter 5 First-Order Logic 5.1 INTRODUCTION In propositional logic, it is not possible to express assertions about elements of a structure. The weak expressive power of propositional logic accounts for its relative mathematical simplicity, but it is a very severe limitation, and it is desirable to have more expressive logics. First-order logic is a considerably richer logic than propositional logic, but yet enjoys many nice mathemati- cal properties. In particular, there are finitary proof systems complete with respect to the semantics. In first-order logic, assertions about elements of structures can be ex- pressed. Technically, this is achieved by allowing the propositional symbols to have arguments ranging over elements of structures. For convenience, we also allow symbols denoting functions and constants. Our study of first-order logic will parallel the study of propositional logic conducted in Chapter 3. First, the syntax of first-order logic will be defined. The syntax is given by an inductive definition. Next, the semantics of first- order logic will be given. For this, it will be necessary to define the notion of a structure, which is essentially the concept of an algebra defined in Section 2.4, and the notion of satisfaction. Given a structure M and a formula A, for any assignment s of values in M to the variables (in A), we shall define the satisfaction relation |=, so that M |= A[s] 146 5.2 FIRST-ORDER LANGUAGES 147 expresses the fact that the assignment s satisfies the formula A in M. The satisfaction relation |= is defined recursively on the set of formulae.
    [Show full text]
  • Part 3: First-Order Logic with Equality
    Part 3: First-Order Logic with Equality Equality is the most important relation in mathematics and functional programming. In principle, problems in first-order logic with equality can be handled by, e.g., resolution theorem provers. Equality is theoretically difficult: First-order functional programming is Turing-complete. But: resolution theorem provers cannot even solve problems that are intuitively easy. Consequence: to handle equality efficiently, knowledge must be integrated into the theorem prover. 1 3.1 Handling Equality Naively Proposition 3.1: Let F be a closed first-order formula with equality. Let ∼ 2/ Π be a new predicate symbol. The set Eq(Σ) contains the formulas 8x (x ∼ x) 8x, y (x ∼ y ! y ∼ x) 8x, y, z (x ∼ y ^ y ∼ z ! x ∼ z) 8~x,~y (x1 ∼ y1 ^ · · · ^ xn ∼ yn ! f (x1, : : : , xn) ∼ f (y1, : : : , yn)) 8~x,~y (x1 ∼ y1 ^ · · · ^ xn ∼ yn ^ p(x1, : : : , xn) ! p(y1, : : : , yn)) for every f /n 2 Ω and p/n 2 Π. Let F~ be the formula that one obtains from F if every occurrence of ≈ is replaced by ∼. Then F is satisfiable if and only if Eq(Σ) [ fF~g is satisfiable. 2 Handling Equality Naively By giving the equality axioms explicitly, first-order problems with equality can in principle be solved by a standard resolution or tableaux prover. But this is unfortunately not efficient (mainly due to the transitivity and congruence axioms). 3 Roadmap How to proceed: • Arbitrary binary relations. • Equations (unit clauses with equality): Term rewrite systems. Expressing semantic consequence syntactically. Entailment for equations. • Equational clauses: Entailment for clauses with equality.
    [Show full text]
  • Logic, Sets, and Proofs David A
    Logic, Sets, and Proofs David A. Cox and Catherine C. McGeoch Amherst College 1 Logic Logical Statements. A logical statement is a mathematical statement that is either true or false. Here we denote logical statements with capital letters A; B. Logical statements be combined to form new logical statements as follows: Name Notation Conjunction A and B Disjunction A or B Negation not A :A Implication A implies B if A, then B A ) B Equivalence A if and only if B A , B Here are some examples of conjunction, disjunction and negation: x > 1 and x < 3: This is true when x is in the open interval (1; 3). x > 1 or x < 3: This is true for all real numbers x. :(x > 1): This is the same as x ≤ 1. Here are two logical statements that are true: x > 4 ) x > 2. x2 = 1 , (x = 1 or x = −1). Note that \x = 1 or x = −1" is usually written x = ±1. Converses, Contrapositives, and Tautologies. We begin with converses and contrapositives: • The converse of \A implies B" is \B implies A". • The contrapositive of \A implies B" is \:B implies :A" Thus the statement \x > 4 ) x > 2" has: • Converse: x > 2 ) x > 4. • Contrapositive: x ≤ 2 ) x ≤ 4. 1 Some logical statements are guaranteed to always be true. These are tautologies. Here are two tautologies that involve converses and contrapositives: • (A if and only if B) , ((A implies B) and (B implies A)). In other words, A and B are equivalent exactly when both A ) B and its converse are true.
    [Show full text]
  • Tool 1: Gender Terminology, Concepts and Definitions
    TOOL 1 Gender terminology, concepts and def initions UNESCO Bangkok Office Asia and Pacific Regional Bureau for Education Mom Luang Pin Malakul Centenary Building 920 Sukhumvit Road, Prakanong, Klongtoei © Hadynyah/Getty Images Bangkok 10110, Thailand Email: [email protected] Website: https://bangkok.unesco.org Tel: +66-2-3910577 Fax: +66-2-3910866 Table of Contents Objectives .................................................................................................. 1 Key information: Setting the scene ............................................................. 1 Box 1: .......................................................................................................................2 Fundamental concepts: gender and sex ...................................................... 2 Box 2: .......................................................................................................................2 Self-study and/or group activity: Reflect on gender norms in your context........3 Self-study and/or group activity: Check understanding of definitions ................3 Gender and education ................................................................................. 4 Self-study and/or group activity: Gender and education definitions ...................4 Box 3: Gender parity index .....................................................................................7 Self-study and/or group activity: Reflect on girls’ and boys’ lives in your context .....................................................................................................................8
    [Show full text]
  • Comparison Identity Vs. Equality Identity Vs. Equality for Strings Notions of Equality Order
    Comparison Comparisons and the Comparable • Something that we do a lot Interface • Can compare all kinds of data with respect to all kinds of comparison relations . Identity . Equality Lecture 14 . Order CS211 – Spring 2006 . Lots of others Identity vs. Equality Identity vs. Equality for Strings • For primitive types (e.g., int, long, float, double, boolean) . == and != are equality tests • Quiz: What are the results of the following tests? • For reference types (i.e., objects) . "hello".equals("hello") true . == and != are identity tests . In other words, they test if the references indicate the same address . "hello" == "hello" true in the Heap . "hello" == new String("hello") false • For equality of objects: use the equals( ) method . equals( ) is defined in class Object . Any class you create inherits equals from its parent class, but you can override it (and probably want to) Notions of equality Order • A is equal to B if A can be substituted for B anywhere • For numeric primitives • For all other reference . Identical things must be equal: == implies equals (e.g., int, float, long, types double) • Immutable values are equal if they represent same value! . <, >, <=, >= do not work . Use <, >, <=, >= • Not clear you want them . (new Integer(2)).equals(new Integer(2)) to work: suppose we . == is not an abstract operation compare People • For reference types that Compare by name? • Mutable values can be distinguished by assignment. correspond to primitive Compare by height? class Foo { int f; Foo(int g) { f = g; } } weight? types Compare by SSN? Foo x = new Foo(2); . As of Java 5.0, Java does CUID? Foo y = new Foo(2); Autoboxing and Auto- .
    [Show full text]
  • Dismantling Racism in Mathematics Instruction Exercises for Educators to Reflect on Their Own Biases to Transform Their Instructional Practice
    A Pathway to MAY 2021 Equitable Math Instruction Dismantling Racism in Mathematics Instruction Exercises for educators to reflect on their own biases to transform their instructional practice STRIDE 1 Dismantling Racism STRIDE 1 in Mathematics Instruction This tool provides teachers an opportunity to examine THEMES their actions, beliefs, and values around teaching math- Teacher Beliefs ematics. The framework for deconstructing racism in GUIDING PRINCIPLES mathematics offers essential characteristics of antiracist Culturally relevant curricula and math educators and critical approaches to dismantling practices designed to increase access for students of color. white supremacy in math classrooms by making visi- Promoting antiracist ble the toxic characteristics of white supremacy culture mathematics instruction. (Jones and Okun 2001; dismantling Racism 2016) with respect to math. Building on the framework, teachers engage with critical praxis in order to shift their instruc- CONTENT DEVELOPERS tional beliefs and practices towards antiracist math ed- Sonia Michelle Cintron ucation. By centering antiracism, we model how to be Math Content Specialist UnboundEd antiracist math educators with accountability. Dani Wadlington Director of Mathematics Education Quetzal Education Consulting Andre ChenFeng HOW TO USE THIS TOOL Ph.D. Student Education at Claremont Graduate While primarily for math educa- • Teachers should use this work- University tors, this text advocates for a book to self-reflect on individual collective approach to dismantling
    [Show full text]
  • Quantum Set Theory Extending the Standard Probabilistic Interpretation of Quantum Theory (Extended Abstract)
    Quantum Set Theory Extending the Standard Probabilistic Interpretation of Quantum Theory (Extended Abstract) Masanao Ozawa∗ Graduate School of Information Science, Nagoya University Nagoya, Japan [email protected] The notion of equality between two observables will play many important roles in foundations of quantum theory. However, the standard probabilistic interpretation based on the conventional Born formula does not give the probability of equality relation for a pair of arbitrary observables, since the Born formula gives the probability distribution only for a commuting family of observables. In this paper, quantum set theory developed by Takeuti and the present author is used to systematically extend the probabilistic interpretation of quantum theory to define the probability of equality relation for a pair of arbitrary observables. Applications of this new interpretation to measurement theory are discussed briefly. 1 Introduction Set theory provides foundations of mathematics. All the mathematical notions like numbers, functions, relations, and structures are defined in the axiomatic set theory, ZFC (Zermelo-Fraenkel set theory with the axiom of choice), and all the mathematical theorems are required to be provable in ZFC [15]. Quan- tum set theory instituted by Takeuti [14] and developed by the present author [11] naturally extends the logical basis of set theory from classical logic to quantum logic [1]. Accordingly, quantum set theory extends quantum logical approach to quantum foundations from propositional logic to predicate logic and set theory. Hence, we can expect that quantum set theory will provide much more systematic inter- pretation of quantum theory than the conventional quantum logic approach [3]. The notion of equality between quantum observables will play many important roles in foundations of quantum theory, in particular, in the theory of measurement and disturbance [9, 10].
    [Show full text]
  • Concepts Associated with the Equality Symbol1
    CONCEPTS ASSOCIATED WITH THE EQUALITY SYMBOL1 ABSTRACT. This paper looks at recent research dealing with uses of the equal sign ana underlying notions of equivalence or non-equivalence among preschoolers (their intuitive notions of equality), elementary and secondary school children, and college students. The idea that the equal sign is a "do something signal"2 (an operator symbol) persists through- out elementary school and even into junior high school. High schoolers' use of the equal sign in algebraic equations as a symbol for equivalence may be concealing a fairly tenuous grasp of the underlying relationship between the equal sign and the notion of equivalence, as indicated by some of the "shortcut" errors they make when solving equations. 1. INTRODUCTION On the topic of equivalence, Gattegno (1974) has stated: We can see that identity is a very restrictive kind of relationship concerned with actual sameness, that equality points at an attribute which does not change, and that equivalence is concerned with a wider relationship where one agrees that for certain purposes it is possible to replace one item by another. Equivalence being the most comprehensive relationship it will also be the most flexible, and therefore the most useful (p. 83). However, the symbol which is used to show equivalence, the equal sign, is not always interpreted in terms of equivalence by the learner. In fact, as will be seen, an equivalence interpretation of the equal sign does not seem to come easily or quickly to many students. 2. PRESCHOOL CONCEPTS OF EQUALITY Once preschoolers begin to tag objects with number words in a systematic and consistent fashion, they seem, at some time after that, to be able to determine the numerical equality of two sets.
    [Show full text]
  • Critical Mathematical Inquiry
    Critical Mathematical Inquiry Introduction Steven Greenstein Mark Russo Essays by Fahmil Shah Mary Raygoza Debasmita Basu Frances K. Harper Lynette Guzmán Jeffrey Craig Elinor J. Albin Gretchen Vice Cathery Yeh Brande M. Otis Theodore Chao Maya Marlowe Laurie Rubel Andrea McCloskey 03. 2019 41 Occasional Paper Series Occasional Paper OCCASIONAL PAPER SERIES | 1 Table of Contents Introduction Teaching for Social Justice through Critical Mathematical Inquiry Steven Greenstein and Mark Russo 4 Re-designing Mathematics Education for Social Justice: A Vision Fahmil Shah 15 Quantitative Civic Literacy Mary Raygoza 26 Cultivating a Space for Critical Mathematical Inquiry through Knowledge-Eliciting Mathematical Activity Debasmita Basu & Steven Greenstein 32 Collaboration and Critical Mathematical Inquiry: Negotiating Mathematics Engagement, Identity, and Agency Frances K. Harper 45 The World in Your Pocket: Digital Media as Invitations for Transdisciplinary Inquiry in Mathematics Classrooms Lynette DeAun Guzmán and Jeffrey Craig 59 Power to Change: Math as a Social-Emotional Language in a Classroom of Four- and Five-Year-Olds Elinor J. Albin and Gretchen Vice 76 Mathematics for Whom: Reframing and Humanizing Mathematics Cathery Yeh and Brande M. Otis 85 Elementary Mathematics and #BlackLivesMatter Theodore Chao and Maya Marlowe 99 The “Soft Bigotry of Low Expectations” and Its Role in Maintaining White Supremacy through Mathematics Education Laurie Rubel and Andrea McCloskey 113 Occasional Paper Series 41 Critical Mathematical Inquiry Introduction
    [Show full text]
  • Combinatorial Species and Labelled Structures Brent Yorgey University of Pennsylvania, [email protected]
    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 1-1-2014 Combinatorial Species and Labelled Structures Brent Yorgey University of Pennsylvania, [email protected] Follow this and additional works at: http://repository.upenn.edu/edissertations Part of the Computer Sciences Commons, and the Mathematics Commons Recommended Citation Yorgey, Brent, "Combinatorial Species and Labelled Structures" (2014). Publicly Accessible Penn Dissertations. 1512. http://repository.upenn.edu/edissertations/1512 This paper is posted at ScholarlyCommons. http://repository.upenn.edu/edissertations/1512 For more information, please contact [email protected]. Combinatorial Species and Labelled Structures Abstract The theory of combinatorial species was developed in the 1980s as part of the mathematical subfield of enumerative combinatorics, unifying and putting on a firmer theoretical basis a collection of techniques centered around generating functions. The theory of algebraic data types was developed, around the same time, in functional programming languages such as Hope and Miranda, and is still used today in languages such as Haskell, the ML family, and Scala. Despite their disparate origins, the two theories have striking similarities. In particular, both constitute algebraic frameworks in which to construct structures of interest. Though the similarity has not gone unnoticed, a link between combinatorial species and algebraic data types has never been systematically explored. This dissertation lays the theoretical groundwork for a precise—and, hopefully, useful—bridge bewteen the two theories. One of the key contributions is to port the theory of species from a classical, untyped set theory to a constructive type theory. This porting process is nontrivial, and involves fundamental issues related to equality and finiteness; the recently developed homotopy type theory is put to good use formalizing these issues in a satisfactory way.
    [Show full text]
  • Gender Equality: Glossary of Terms and Concepts
    GENDER EQUALITY: GLOSSARY OF TERMS AND CONCEPTS GENDER EQUALITY Glossary of Terms and Concepts UNICEF Regional Office for South Asia November 2017 Rui Nomoto GENDER EQUALITY: GLOSSARY OF TERMS AND CONCEPTS GLOSSARY freedoms in the political, economic, social, a cultural, civil or any other field” [United Nations, 1979. ‘Convention on the Elimination of all forms of Discrimination Against Women,’ Article 1]. AA-HA! Accelerated Action for the Health of Adolescents Discrimination can stem from both law (de jure) or A global partnership, led by WHO and of which from practice (de facto). The CEDAW Convention UNICEF is a partner, that offers guidance in the recognizes and addresses both forms of country context on adolescent health and discrimination, whether contained in laws, development and puts a spotlight on adolescent policies, procedures or practice. health in regional and global health agendas. • de jure discrimination Adolescence e.g., in some countries, a woman is not The second decade of life, from the ages of 10- allowed to leave the country or hold a job 19. Young adolescence is the age of 10-14 and without the consent of her husband. late adolescence age 15-19. This period between childhood and adulthood is a pivotal opportunity to • de facto discrimination consolidate any loss/gain made in early e.g., a man and woman may hold the childhood. All too often adolescents - especially same job position and perform the same girls - are endangered by violence, limited by a duties, but their benefits may differ. lack of quality education and unable to access critical health services.i UNICEF focuses on helping adolescents navigate risks and vulnerabilities and take advantage of e opportunities.
    [Show full text]