Lattice Models and Fractal Measures
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Second Grade C CCSS M Math Vo Ocabular Ry Word D List
Second Grade CCSS Math Vocabulary Word List *Terms with an asterisk are meant for teacher knowledge only—students do not need to learn them. Add To combine; put together two or more quantities. Addend Any number being added a.m. The half of the day from midnight to midday Analog clock Clock with hands: a clock that shows the time by means of hands on a dial Angle is formed by two rays with a common enndpoint (called the vertex) Array an orderly arrangement in rows and columns used in multiplication and division to show how multiplication can be shown as repeated addition and division can be shown as fair shares. *Associative Property of Addition When three or more numbers are added, the sum is the same regardless of the grouping of the addends. For example (2 + 3) + 4 = 2 + (3 + 4) Attribute A characteristic of an object such as color, shape, size, etc Bar graph A graph drawn using rectangular barrs to show how large each value is Bar Model a visual model used to solve word problems in the place of guess and check. Example: *Cardinality-- In mathematics, the cardinality of a set is a measure of the "number of elements of the set". For example, the set A = {2, 4, 6} contains 3 elements, and therefore A has a cardinality of 3. Category A collection of things sharing a common attribute Cent The smallest money value in many countries. 100 cents equals one dollar in the US. Centimeter A measure of length. There are 100 centimeters in a meter Circle A figure with no sides and no vertices. -
Measure Theory and Probability Theory
Measure Theory and Probability Theory Stéphane Dupraz In this chapter, we aim at building a theory of probabilities that extends to any set the theory of probability we have for finite sets (with which you are assumed to be familiar). For a finite set with N elements Ω = {ω1, ..., ωN }, a probability P takes any n positive numbers p1, ..., pN that sum to one, and attributes to any subset S of Ω the number (S) = P p . Extending this definition to infinitely countable sets such as P i/ωi∈S i N poses no difficulty: we can in the same way assign a positive number to each integer n ∈ N and require that P∞ 1 P n=1 pn = 1. We can then define the probability of a subset S ⊆ N as P(S) = n∈S pn. Things get more complicated when we move to uncountable sets such as the real line R. To be sure, it is possible to assign a positive number to each real number. But how to get from these positive numbers to the probability of any subset of R?2 To get a definition of a probability that applies without a hitch to uncountable sets, we give in the strategy we used for finite and countable sets and start from scratch. The definition of a probability we are going to use was borrowed from measure theory by Kolmogorov in 1933, which explains the title of this chapter. What do probabilities have to do with measurement? Simple: assigning a probability to an event is measuring the likeliness of this event. -
Results Real Analysis I and II, MATH 5453-5463, 2006-2007
Main results Real Analysis I and II, MATH 5453-5463, 2006-2007 Section Homework Introduction. 1.3 Operations with sets. DeMorgan Laws. 1.4 Proposition 1. Existence of the smallest algebra containing C. 2.5 Open and closed sets. 2.6 Continuous functions. Proposition 18. Hw #1. p.16 #9, 11, 17, 18; p.19 #19. 2.7 Borel sets. p.49 #40, 42, 43; p.53 #53*. 3.2 Outer measure. Proposition 1. Outer measure of an interval. Proposition 2. Subadditivity of the outer measure. Proposition 5. Approximation by open sets. 3.3 Measurable sets. Lemma 6. Measurability of sets of outer measure zero. Lemma 7. Measurability of the union. Hw #2. p.55 #1-4; p.58 # 7, 8. Theorem 10. Measurable sets form a sigma-algebra. Lemma 11. Interval is measurable. Theorem 12. Borel sets are measurable. Proposition 13. Sigma additivity of the measure. Proposition 14. Continuity of the measure. Proposition 15. Approximation by open and closed sets. Hw #3. p.64 #9-11, 13, 14. 3.4 A nonmeasurable set. 3.5 Measurable functions. Proposition 18. Equivalent definitions of measurability. Proposition 19. Sums and products of measurable functions. Theorem 20. Infima and suprema of measurable functions. Hw #4. p.70 #18-22. 3.6 Littlewood's three principles. Egoroff's theorem. Lusin's theorem. 4.2 Prop.2. Lebesgue's integral of a simple function and its props. Lebesgue's integral of a bounded measurable function. Proposition 3. Criterion of integrability. Proposition 5. Properties of integrals of bounded functions. Proposition 6. Bounded convergence theorem. 4.3 Lebesgue integral of a nonnegative function and its properties. -
Ground and Explanation in Mathematics
volume 19, no. 33 ncreased attention has recently been paid to the fact that in math- august 2019 ematical practice, certain mathematical proofs but not others are I recognized as explaining why the theorems they prove obtain (Mancosu 2008; Lange 2010, 2015a, 2016; Pincock 2015). Such “math- ematical explanation” is presumably not a variety of causal explana- tion. In addition, the role of metaphysical grounding as underwriting a variety of explanations has also recently received increased attention Ground and Explanation (Correia and Schnieder 2012; Fine 2001, 2012; Rosen 2010; Schaffer 2016). Accordingly, it is natural to wonder whether mathematical ex- planation is a variety of grounding explanation. This paper will offer several arguments that it is not. in Mathematics One obstacle facing these arguments is that there is currently no widely accepted account of either mathematical explanation or grounding. In the case of mathematical explanation, I will try to avoid this obstacle by appealing to examples of proofs that mathematicians themselves have characterized as explanatory (or as non-explanatory). I will offer many examples to avoid making my argument too dependent on any single one of them. I will also try to motivate these characterizations of various proofs as (non-) explanatory by proposing an account of what makes a proof explanatory. In the case of grounding, I will try to stick with features of grounding that are relatively uncontroversial among grounding theorists. But I will also Marc Lange look briefly at how some of my arguments would fare under alternative views of grounding. I hope at least to reveal something about what University of North Carolina at Chapel Hill grounding would have to look like in order for a theorem’s grounds to mathematically explain why that theorem obtains. -
M.EE.4.NF.1-2 Subject: Mathematics Number and Operations—Fractions (NF) Grade: 4
Mini-Map for M.EE.4.NF.1-2 Subject: Mathematics Number and Operations—Fractions (NF) Grade: 4 Learning Outcome DLM Essential Element Grade-Level Standard M.EE.4.NF.1-2 Identify models of one half (1/2) and one fourth M.4.NF.1 Explain why a fraction a/b is equivalent to a fraction (1/4). (n × a)/(n × b) by using visual fraction models, with attention to how the number and size of the parts differ even though the two fractions themselves are the same size. Use this principle to recognize and generate equivalent fractions. M.4.NF.2 Compare two fractions with different numerators and different denominators, e.g., by creating common denominators or numerators, or by comparing to a benchmark fraction such as 1/2. Recognize that comparisons are valid only when the two fractions refer to the same whole. Record the results of comparisons with symbols >, =, or <, and justify the conclusions, e.g., by using a visual fraction model. Linkage Level Descriptions Initial Precursor Distal Precursor Proximal Precursor Target Successor Communicate Divide familiar shapes, Divide familiar shapes, Identify the model that Identify the area model understanding of such as circles, such as circles, squares, represents one half or that is divided into "separateness" by triangles, squares, and/or rectangles, into one fourth of a familiar halves or fourths. recognizing objects that and/or rectangles, into two or more equal shape or object. are not joined together. two or more distinct parts. Communicate parts. These parts may understanding of or may not be equal. -
Abelian Group, 521, 526 Absolute Value, 190 Accumulation, Point Of
Index Abelian group, 521, 526 A-set. SeeAnalytic set Absolutevalue, 190 Asymptoticallyequal. 479 Accumulation, point of, 196 Atlas , 231; of holomorphically related Adjoint differentialform, 157, 167 charts, 245 Adjoint operator, 403 Atomic theory, 415 Adjoint space, 397 Automorphism group, 510, 511 Algebra, 524; Boolean, 91, 92; Axiomatic method, in geometry, 507-508 fundamentaltheorem of, 195-196; homo logical, 519-520; normed, 516 BAIREclasses, 460; first, 460, 462, 463; Almost all, 479 of functions, 448 Almost continuous, 460 BAIREcondition, 464 Almost equal, 479 BAIREfunction, 464, 473; non-, 474 Almost everywhere, 70 BAIREspace, 464 Almost linear equation, 321, 323 BAIREsystem, of functions, 459, 460 Alternating differentialform, 185; BAIREtheorem, 448, 460, 462 differentialoperations for, 159-165; BANACH, S., 516 theory of, vi, 143 BANACHfixed point theorem, 423 Alternative theorem, 296, 413 BANACHspace, 338, 340, 393, 399, 432, Analysis, v, 1; axiomaticmethod in, 435,437, 516; adjoint, 400; 512-518; complex, vi ; functional, conjugate, 400; dual, 400; theory of, vi 391; harmonic, 518; and number BANACHtheorem, 446, 447 theory, 500-501 Band spectra, 418 Analytic function, definedby function BAYES theorem, 109 element, 242 BELTRAMIdifferential equation, 325 Analytic numbertheory, 480 BERNOULLI, DANIEL, 23 Analytic operation, 468 BERNOULLI, JACOB, 89, 360 Analytic set, 448, 458, 465, 468, 469; BERNOULLI, JOHANN, 23 linear, 466 BERNOULLIdistribution, 96 Angle-preservingtransformation, 194 BERNOULLIlaw, of large numbers, 116 a-points, -
Instructional Routines for Mathematic Intervention-Modules 1-23
INCLUSION IN TEXAS Instructional Routines for Mathematics Intervention The purpose of these mathematics instructional routines is to provide educators with materials to use when providing intervention to students who experience difficulty with mathematics. The routines address content included in the grades 2-8 Texas Essential Knowledge and Skills (TEKS). There are 23 modules that include routines and examples – each focused on different mathematical content. Each of the 23 modules include vocabulary cards and problem sets to use during instruction. These materials are intended to be implemented explicitly with the aim of improving mathematics outcomes for students. Copyright © 2021. Texas Education Agency. All Rights Reserved. Notwithstanding the foregoing, the right to reproduce the copyrighted work is granted to Texas public school districts, Texas charter schools, and Texas education service centers for non- profit educational use within the state of Texas, and to residents of the state of Texas for their own personal, non-profit educational use, and provided further that no charge is made for such reproduced materials other than to cover the out-of-pocket cost of reproduction and distribution. No other rights, express or implied, are granted hereby. For more information, please contact [email protected]. Instructional Routines for Mathematics Intervention MODULE 15 Division of Rational Numbers Module 15: Division of Rational Numbers Mathematics Routines A. Important Vocabulary with Definitions Term Definition algorithm A procedure or description of steps that can be used to solve a problem. computation The action used to solve a problem. decimal A number based on powers of ten. denominator The term in a fraction that tells the number of equal parts in a whole. -
8Ratio and Percentages
8 Ratio and percentages 1 Ratio A ratio is a comparison of two numbers. We generally separate the two numbers in the ratio with a colon (:) or as a fraction. Suppose we want to write the ratio of 8 and 12. We can write this as 8:12 or as 8/12, and we say the ratio is eight to twelve . Examples: Janet has a bag with 4 pens, 3 sweets, 7 books, and 2 sandwiches. 1. What is the ratio of books to pens? Expressed as a fraction, the answer would be 7/4. Two other ways of writing the ratio are 7 to 4, and 7:4. 2. What is the ratio of sweets to the total number of items in the bag? There are 3 candies, and 4 + 3 + 7 + 2 = 16 items total. The answer can be expressed as 3/16, 3 to 16, or 3:16. 2 Comparing Ratios To compare ratios, write them as fractions. The ratios are equal if they are equal when written as fractions. We can find ratios equivalent to other ratios by multiplying/ dividing both sides by the same number. Example: Are the ratios 2 to 7 and 4:14 equal? The ratios are equal because 2/7 = 4/14. The process of finding the simplest form of a ratio is the same as the process of finding the simplest form of a fraction. 1 : 3.5 or 2 : 7 could be given as more simple forms of the ratio 4 : 14. 1 I.E.S. “Andrés de Vandelvira” Sección Europea Mathematics Exercise 1 Simplify the following ratios: 3:6 25:50 40:100 9:21 11:121 For some purposes the best is to reduce the numbers to the form 1 : n or n : 1 by dividing both numbers by either the left hand side or the right-hand side number. -
Fractured Fractions
1 1 6 4 1 1 2 8 Fractured Fractions 1 1 5 3 Strands: In this game for 2 to 4 players, work your way around the game board by using visual representations to fracture fractions and Number & whole numbers. X Quantity Set -Up: Algebra • To begin, place one marker for each player on START on the Round 1 board. Functions Object of the Game: Solve whole number and unit fraction division problems using visual representations. Explain your drawings. Geometry Pre-Game Play: • Before Round 1, represent whole numbers divided by unit fractions using the Statistics & # Fractured Fractions Workspace. For example, represent 3 ÷ by identifying 3 Probability $ wholes and examining how many one-half pieces there are in 3 wholes. In # this example, 3 is the dividend and is the divisor. $ • Before Round 2, represent unit fractions divided by whole numbers using the Materials Needed: Fractured Fractions Workspace. For example, represent # ÷ 3 by identifying 1 • Fractured $ Fractions game whole, finding half, of it, then determining the size of the region when # is $ boards (Round 1 # divided into 3 parts. In this example, is the dividend and 3 is the divisor. & Round 2) $ • Game piece, 1 per Playing the Game: player • Fractured Round 1: Whole number ÷ Fraction = Whole number Fractions Dividend ÷ Divisor = Quotient 1. Use the game board showing whole numbers on each space. Workspace, 1 per 2. On your turn, use the die to determine the whole number dividend and the player • Fractured spinner to determine the fraction divisor. Fractions spinner 3. Use the Fractured Fractions Workspace to solve the fraction division problem. -
2.1.3 Outer Measures and Construction of Measures Recall the Construction of Lebesgue Measure on the Real Line
CHAPTER 2. THE LEBESGUE INTEGRAL I 11 2.1.3 Outer measures and construction of measures Recall the construction of Lebesgue measure on the real line. There are various approaches to construct the Lebesgue measure on the real line. For example, consider the collection of finite union of sets of the form ]a; b]; ] − 1; b]; ]a; 1[ R: This collection is an algebra A but not a sigma-algebra (this has been discussed on p.7). A natural measure on A is given by the length of an interval. One attempts to measure the size of any subset S of R covering it by countably many intervals (recall also that R can be covered by countably many intervals) and we define this quantity by 1 1 X [ m∗(S) = inff jAkj : Ak 2 A;S ⊂ Akg (2.7) k=1 k=1 where jAkj denotes the length of the interval Ak. However, m∗(S) is not a measure since it is not additive, which we do not prove here. It is only sigma- subadditive, that is k k [ X m∗ Sn ≤ m∗(Sn) n=1 n=1 for any countable collection (Sn) of subsets of R. Alternatively one could choose coverings by open intervals (see the exercises, see also B.Dacorogna, Analyse avanc´eepour math´ematiciens)Note that the quantity m∗ coincides with the length for any set in A, that is the measure on A (this is surprisingly the more difficult part!). Also note that the sigma-subadditivity implies that m∗(A) = 0 for any countable set since m∗(fpg) = 0 for any p 2 R. -
Income Tax Booklet
2020 Individual Income Tax For a fast refund, file electronically! Balance due? Pay electronically and choose your payment date. See back cover for details. ksrevenue.org in Kansas. For individuals, it is usually the home. For businesses, In This Booklet it is where the items are used (office, shop, etc). General Information .................................. 3 Do I owe this tax? Kansans that buy goods in other states or K-40 Instructions....................................... 6 through catalogs, internet, mail-order companies, or from TV, Form K-40................................................. 11 magazine and newspaper ads must pay Kansas use tax on the Schedule S ............................................... 13 purchases if the goods are used, stored or consumed in Kansas Schedule K-210 ........................................ 15 and the seller does not charge a sales tax rate equal to or greater Schedule S Instructions ........................... 17 than the Kansas retailers’ sales tax rate in effect where the item is Tax Table.................................................. 20 delivered or first used. EXAMPLE: An Anytown, KS resident goes Tax Computation Worksheet .................... 27 to Missouri to purchase a laptop computer during a Missouri sales Taxpayer Assistance .................. Back cover tax “Holiday.” The cost of the computer is $2,000. The Anytown Electronic Options ...................... Back cover resident will owe Kansas use tax of 8.95% (current Anytown rate) on the total charge of $2,000 when that resident brings the laptop Important Information computer back to Anytown, KS. ($2,000 X 0.0895 = $179.00). How do I pay the Compensating Use Tax? To pay Kansas use CHILD AND DEPENDENT CARE CREDIT. tax on your untaxed out-of-state purchases made during calendar This credit is for child and dependent care year 2020, refer to the instructions for line 20 of Form K-40. -
REU 2007 · Transfinite Combinatorics · Lecture 1
REU 2007 · Transfinite Combinatorics · Lecture 1 Instructor: L´aszl´oBabai Scribe: Damir Dzhafarov July 23, 2007. Partially revised by instructor. Last updated July 26, 12:00 AM 1.1 Transfinite Combinatorics and Toy Problems Lamp and switches. Imagine a lamp which is always on, and which assumes one of three different colors. The particular color of the lamp at a given time is completely determined by the configuration, at that time, of a row of three-way switches (i.e., switches that can each occupy one of three different states). If there are n switches, any such configuration can be represented by an n-tuple (x1, . , xn), where xi ∈ {0, 1, 2} for all i, that is, by an element of {0, 1, 2}n. If we let the set of possible colors of the lamp be {0, 1, 2}, we can thus regard the lamp’s color as a function of the configurations of the switches, i.e., as a function f : {0, 1, 2}n → {0, 1, 2}. The system of the lamp and switches is subject to a single rule, that if the position of each switch be changed, the color of the lamp changes as well. In other words, if (x1, . , xn) 0 0 0 and (x1, . , xn) are configurations of switches with xi 6= xi for all i, then f(x1, . , xn) 6= 0 0 f(x1, . , xn). Exercise 1.1.1. Prove that if there are only finitely many switches, then there must exist a dictator switch, meaning one which makes all other switches redundant in that all of its positions induce different colors of the lamp, and each of its positions always induces the same color, regardless of the configuration of the other switches.