Grade 3. Strand: Number Specific Learning Outcomes It is expected that students will:

Size: px
Start display at page:

Download "Grade 3. Strand: Number Specific Learning Outcomes It is expected that students will:"

Transcription

1 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.N.1. 3.N.2. Strad: Number Specific Learig Outcomes It is expected that studets will: Say the umber sequece betwee ay two give umbers forward ad backward from 0 to 1000 by 10s or 100s, usig ay startig poit 5s, usig startig poits that are multiples of 5 25s, usig startig poits that are multiples of 25 from 0 to 100 by 3s, usig startig poits that are multiples of 3 4s, usig startig poits that are multiples of 4 [C, CN, ME] Represet ad describe umbers to 1000, cocretely, pictorially, ad symbolically. [C, CN, V] Geeral Learig Outcome: Develop umber sese. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Exted a skip-coutig sequece by 10s or 100s, forward ad backward, usig a give startig poit. Exted a skip-coutig sequece by 5s, forward ad backward, startig at a give multiple of 5. Exted a skip-coutig sequece by 25s, forward ad backward, startig at a give multiple of 25. Exted a give skip-coutig sequece by 3s, forward, startig at a give multiple of 3. Exted a give skip-coutig sequece by 4s, startig at a give multiple of 4. Idetify ad correct errors ad omissios i a skip-coutig sequece. Determie the value of a set of cois (ickels, dimes, quarters, looies) by usig skip coutig. Idetify ad explai the skip-coutig patter for a umber sequece. Read a 3-digit umeral without usig the word ad (e.g., 321 is three hudred twetyoe, NOT three hudred AND twety-oe). Read a umber word (0 to 1000). Represet a umber as a expressio (e.g., for 256 or ). Represet a umber usig maipulatives, such as base-10 materials. Represet a umber pictorially. Write umber words for multiples of te to 90. Write umber words for multiples of a hudred to 900. Determie compatible umber pairs for Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

2 Strad: Number (cotiued) Specific Learig Outcomes It is expected that studets will: 3.N.3. Compare ad order umbers to [CN, R, V] 3.N.4. 3.N.5. Estimate quatities less tha 1000 usig referets. [ME, PS, R, V] Illustrate, cocretely ad pictorially, the meaig of place value for umerals to [C, CN, R, V] [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio Geeral Learig Outcome: Develop umber sese. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Place a set of umbers i ascedig or descedig order, ad verify the result by usig a hudred chart (e.g., a oe hudred chart, a two hudred chart, a three hudred chart, a umber lie, or by makig refereces to place value). Create as may differet 3-digit umerals as possible, give three differet digits. Place the umbers i ascedig or descedig order. Idetify errors i a ordered sequece. Idetify missig umbers i parts of a hudred chart. Idetify errors i a hudred chart. Estimate the umber of groups of te i a quatity usig 10 as a referet (kow quatity). Estimate the umber of groups of a hudred i a quatity usig 100 as a referet. Estimate a quatity by comparig it to a referet. Select a estimate for a quatity by choosig amog three possible choices. Select ad justify a referet for determiig a estimate for a quatity. Record i more tha oe way the umber represeted by proportioal ad oproportioal cocrete materials. Represet a umber i differet ways usig proportioal ad o-proportioal cocrete materials, ad explai how they are equivalet (e.g., 351 ca be represeted as three 100s, five 10s ad oe 1, or as two 100s, fiftee 10s, ad oe 1, or as three 100s, four 10s, ad eleve 1s). Explai, ad show with couters, the meaig of each digit for a 3-digit umeral with all digits the same (e.g., for the umeral 222, the first digit represets two hudreds [two hudred couters] the secod digit represets two tes [twety couters], ad the third digit represets two oes [two couters]). Geeral ad Specific Learig Outcomes 77

3 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.N.6. 3.N.7. 3.N.8. Strad: Number (cotiued) Specific Learig Outcomes It is expected that studets will: Describe ad apply metal mathematics strategies for addig two 2-digit umerals, such as addig from left to right takig oe added to the earest multiple of te ad the compesatig usig doubles [C, ME, PS, R, V] Describe ad apply metal mathematics strategies for subtractig two 2-digit umerals, such as takig the subtrahed to the earest multiple of te ad the compesatig thikig of additio usig doubles [C, ME, PS, R, V] Apply estimatio strategies to predict sums ad differeces of two 2-digit umerals i a problem-solvig cotext. [C, ME, PS, R] Geeral Learig Outcome: Develop umber sese. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Add two 2-digit umerals usig a metal mathematics strategy, ad explai or model the strategy. Explai how to use the addig from left to right strategy (e.g., to determie the sum of , thik ad 3 + 6). Explai how to use the takig oe added to the earest multiple of te strategy (e.g., to determie the sum of , thik or ). Explai how to use the usig doubles strategy (e.g., to determie the sum of , thik ; to determie the sum of , thik or doubles plus 1). Apply a metal mathematics strategy for addig two 2-digit umerals. Subtract two 2-digit umerals usig a metal mathematics strategy, ad explai or model the strategy. Explai how to use the takig the subtrahed to the earest multiple of te ad the compesatig strategy (e.g., to determie the differece of 48 19, thik ). Explai how to use the thikig of additio strategy (e.g., to determie the differece of 62 45, thik , the , ad the ). Explai how to use the usig doubles strategy (e.g., to determie the differece of 24 12, thik ). Apply a metal mathematics strategy for subtractig two 2-digit umerals. Estimate the solutio for a story problem ivolvig the sum of two 2-digit umerals (e.g., to estimate the sum of , use ; the sum is close to 90). Estimate the solutio for a story problem ivolvig the differece of two 2-digit umerals (e.g., to estimate the differece of 56 23, use 50 20; the differece is close to 30). 78 Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

4 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.N.9. 3.N.10. Strad: Number (cotiued) Specific Learig Outcomes It is expected that studets will: Demostrate a uderstadig of additio ad subtractio of umbers with aswers to 1000 (limited to 1-, 2-, ad 3-digit umerals) by usig persoal strategies for addig ad subtractig with ad without the support of maipulatives creatig ad solvig problems i cotexts that ivolve additio ad subtractio of umbers cocretely, pictorially, ad symbolically. [C, CN, ME, PS, R] Apply metal math strategies to determie additio facts ad related subtractio facts to 18 (9 + 9). [C, CN, ME, R, V] Recall of additio ad related subtractio facts to 18 is expected by the ed of Grade 3. Geeral Learig Outcome: Develop umber sese. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Model the additio of two or more umbers usig cocrete or visual represetatios, ad record the process symbolically. Model the subtractio of two umbers usig cocrete or visual represetatios, ad record the process symbolically. Create a additio or subtractio story problem for a solutio. Determie the sum of two umbers usig a persoal strategy (e.g., for , record ). Determie the differece of two umbers usig a persoal strategy (e.g., for , record or ). Solve a problem ivolvig the sum or differece of two umbers. Describe a metal mathematics strategy that could be used to determie a give basic fact, such as Q doubles (e.g., for 6 + 8, thik 7 + 7) Q doubles plus oe (e.g., for 6 + 7, thik ) Q doubles take away oe (e.g., for 6 + 7, thik ) Q doubles plus two (e.g., for 6 + 8, thik ) Q doubles take away two (e.g., for 6 + 8, thik ) Q makig 10 (e.g., for 6 + 8, thik or ) Q commutative property (e.g., for 3 + 9, thik 9 + 3) Q additio to subtractio (e.g., for 13 7, thik 7 + o = 13) Provide a rule for determiig aswers for addig ad subtractig zero. Geeral ad Specific Learig Outcomes 79

5 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.N N.12. Strad: Number (cotiued) Specific Learig Outcomes It is expected that studets will: Demostrate a uderstadig of multiplicatio to 5 5 by represetig ad explaiig multiplicatio usig equal groupig ad arrays creatig ad solvig problems i cotext that ivolve multiplicatio modellig multiplicatio usig cocrete ad visual represetatios, ad recordig the process symbolically relatig multiplicatio to repeated additio relatig multiplicatio to divisio [C, CN, PS, R] Demostrate a uderstadig of divisio by represetig ad explaiig divisio usig equal sharig ad equal groupig creatig ad solvig problems i cotext that ivolve equal sharig ad equal groupig modellig equal sharig ad equal groupig usig cocrete ad visual represetatios, ad recordig the process symbolically relatig divisio to repeated subtractio relatig divisio to multiplicatio (limited to divisio related to multiplicatio facts up to 5 5). [C, CN, PS, R] Geeral Learig Outcome: Develop umber sese. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. (It is iteded that studets show their uderstadig of strategies usig maipulatives, pictorial represetatios, ad/or patters whe determiig products.) Idetify evets from experiece that ca be described as multiplicatio. Represet a story problem (orally, shared readig, writte) usig maipulatives or diagrams, ad record i a umber setece. Skip-cout by 2s, 3s, 4s, ad 5s to determie the aswer to a multiplicatio problem represeted as equal groups. Represet a multiplicatio expressio as repeated additio. Represet a repeated additio as multiplicatio. Create ad illustrate a story problem for a umber setece. Represet, cocretely or pictorially, equal groups for a umber setece. Represet a multiplicatio expressio usig a array. Create a array to model the commutative property of multiplicatio. Relate multiplicatio to divisio by usig arrays ad by writig related umber seteces. Solve a problem i cotext ivolvig multiplicatio. (It is iteded that studets show their uderstadig of strategies usig maipulatives, pictorial represetatios, ad/or patters whe determiig quotiets.) Idetify evets from experiece that ca be described as equal sharig. Idetify evets from experiece that ca be described as equal groupig. Illustrate, with couters or a diagram, a story problem ivolvig equal sharig, preseted orally or through shared readig, ad solve the problem. Illustrate, with couters or a diagram, a story problem ivolvig equal groupig, preseted orally or through shared readig, ad solve the problem. Liste to a story problem, represet the umbers usig maipulatives or a sketch, ad record the problem with a umber setece. Create, ad illustrate with couters, a story problem for a umber setece. Represet a divisio expressio as repeated subtractio. Represet a repeated subtractio as a divisio expressio. Relate divisio to multiplicatio by usig arrays ad by writig related umber seteces. Solve a problem ivolvig divisio. 80 Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

6 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.N.13. Strad: Number (cotiued) Specific Learig Outcomes It is expected that studets will: Demostrate a uderstadig of fractios by explaiig that a fractio represets a portio of a whole divided ito equal parts describig situatios i which fractios are used comparig fractios of the same whole with like deomiators [C, CN, ME, R, V] Geeral Learig Outcome: Develop umber sese. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Idetify commo characteristics of a set of fractios. Describe everyday situatios where fractios are used. Cut or fold a whole ito equal parts, or draw a whole i equal parts; demostrate that the parts are equal ad ame the parts. Sort a set of diagrams of regios ito those that represet equal parts ad those that do ot, ad explai the sortig. Represet a fractio cocretely or pictorially. Name ad record the fractio represeted by the shaded ad o-shaded parts of a regio. Compare fractios with the same deomiator usig models. Idetify the umerator ad deomiator for a fractio. Model ad explai the meaig of umerator ad deomiator. Geeral ad Specific Learig Outcomes 81

7 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.PR.1. Strad: Patters ad Relatios (Patters) Specific Learig Outcomes It is expected that studets will: Demostrate a uderstadig of icreasig patters by describig extedig comparig creatig patters usig maipulatives, diagrams, ad umbers (to 1000). [C, CN, PS, R, V] Geeral Learig Outcome: Use patters to describe the world ad solve problems. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Describe a icreasig patter by statig a patter rule that icludes the startig poit ad a descriptio of how the patter cotiues. Idetify the patter rule of a icreasig patter, ad exted the patter for the ext three terms. Idetify ad explai errors i a icreasig patter. Idetify ad describe various icreasig patters foud o a hudred chart, such as horizotal, vertical, ad diagoal patters. Compare umeric patters of coutig by 2s, 3s, 4s, 5s, 10s, 25s, ad 100s. Create a cocrete, pictorial, or symbolic represetatio of a icreasig patter for a patter rule. Create a cocrete, pictorial, or symbolic icreasig patter, ad describe the patter rule. Solve a problem usig icreasig patters. Idetify ad describe icreasig patters i the eviromet. Idetify ad apply a patter rule to determie missig elemets for a patter. Describe the strategy used to determie missig elemets i a icreasig patter. 82 Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

8 3.PR.2. Grade 3 Strad: Patters ad Relatios (Patters) (cotiued) Specific Learig Outcomes It is expected that studets will: Demostrate a uderstadig of decreasig patters by describig extedig comparig creatig patters usig maipulatives, diagrams, ad umbers (startig from 1000 or less). [C, CN, PS, R, V] Geeral Learig Outcome: Use patters to describe the world ad solve problems. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Describe a decreasig patter by statig a patter rule that icludes the startig poit ad a descriptio of how the patter cotiues. Idetify the patter rule of a decreasig patter, ad exted the patter for the ext three terms. Idetify ad explai errors i a decreasig patter. Idetify ad describe various decreasig patters foud o a hudred chart, such as horizotal, vertical, ad diagoal patters. Compare decreasig umeric patters of coutig backward by 2s, 3s, 4s, 5s, 10s, 25s, ad 100s. [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio Create a cocrete, pictorial, or symbolic decreasig patter for a patter rule. Create a cocrete, pictorial, or symbolic decreasig patter, ad describe the patter rule. Solve a problem usig decreasig patters. Idetify ad describe decreasig patters i the eviromet. Idetify ad apply a patter rule to determie missig elemets for a patter. Describe the strategy used to determie missig elemets i a decreasig patter. Geeral ad Specific Learig Outcomes 83

9 3.PR.3. Grade 3 Strad: Patters ad Relatios (Variables ad Equatios) Specific Learig Outcomes It is expected that studets will: Solve oe-step additio ad subtractio equatios ivolvig symbols represetig a ukow umber. [C, CN, PS, R, V] [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio Geeral Learig Outcome: Represet algebraic expressios i multiple ways. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Explai the purpose of the symbol, such as a triagle or a circle, i a additio or a subtractio equatio with oe ukow. Create a additio or subtractio equatio with oe ukow to represet a combiatio or separatio actio. Provide a alterative symbol for the ukow i a additio or subtractio equatio. Solve a additio or subtractio equatio that represets combiig or separatig actios with oe ukow, usig maipulatives. Solve a additio or subtractio equatio with oe ukow usig a variety of strategies icludig guess ad test. Explai why the ukow i a additio or subtractio equatio has oly oe value. 84 Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

10 3.SS.1. 3.SS.2. Grade 3 Strad: Shape ad Space (Measuremet) Specific Learig Outcomes It is expected that studets will: Relate the passage of time to commo activities usig ostadard ad stadard uits (miutes, hours, days, weeks, moths, years). [CN, ME, R] Relate the umber of secods to a miute, the umber of miutes to a hour, ad the umber of days to a moth i a problem-solvig cotext. [C, CN, PS, R, V] 3.SS.3. Demostrate a uderstadig of measurig legth (cm, m) by selectig ad justifyig referets for the uits cm ad m modellig ad describig the relatioship betwee the uits cm ad m estimatig legth usig referets measurig ad recordig legth, width, ad height [C, CN, ME, PS, R, V] [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio Geeral Learig Outcome: Use direct or idirect measuremet to solve problems. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Select ad use a o-stadard uit of measure, such as televisio shows or pedulum swigs, to measure the passage of time, ad explai the choice. Idetify activities that ca or caot be accomplished i miutes, hours, days, moths, ad years. Provide persoal referets for miutes ad hours. Determie the umber of days i ay moth usig a caledar. Solve a problem ivolvig the umber of miutes i a hour or the umber of days i a give moth. Create a caledar that icludes days of the week, dates, ad evets. Provide a persoal referet for oe cetimetre ad explai the choice. Provide a persoal referet for oe metre ad explai the choice. Match a stadard uit to a referet. Show that 100 cetimetres is equivalet to 1 metre by usig cocrete materials. Estimate the legth of a object usig persoal referets. Determie ad record the legth or width of a 2-D shape. Determie ad record the legth, width, or height of a 3-D object. Draw a lie segmet of a give legth usig a ruler. Sketch a lie segmet of a give legth without usig a ruler. Geeral ad Specific Learig Outcomes 85

11 3.SS.4. 3.SS.5. Grade 3 Strad: Shape ad Space (Measuremet) (cotiued) Specific Learig Outcomes It is expected that studets will: Demostrate a uderstadig of measurig mass (g, kg) by selectig ad justifyig referets for the uits g ad kg modellig ad describig the relatioship betwee the uits g ad kg estimatig mass usig referets measurig ad recordig mass [C, CN, ME, PS, R, V] Demostrate a uderstadig of perimeter of regular ad irregular shapes by estimatig perimeter usig referets for cetimetre or metre measurig ad recordig perimeter (cm, m) costructig differet shapes for a give perimeter (cm, m) to demostrate that may shapes are possible for a perimeter [C, ME, PS, R, V] [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio Geeral Learig Outcome: Use direct or idirect measuremet to solve problems. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Provide a persoal referet for oe gram ad explai the choice. Provide a persoal referet for oe kilogram ad explai the choice. Match a stadard uit to a referet. Explai the relatioship betwee 1000 grams ad 1 kilogram usig a model. Estimate the mass of a object usig persoal referets. Determie ad record the mass of a 3-D object. Measure, usig a scale, ad record the mass of everyday objects usig the uits g ad kg. Provide examples of 3-D objects that have a mass of approximately 1g, 100g, ad 1kg. Determie the mass of two similar objects with differet masses, ad explai the results. Determie the mass of a object, chage its shape, re-measure its mass, ad explai the results. Measure ad record the perimeter of a regular shape, ad explai the strategy used. Measure ad record the perimeter of a irregular shape, ad explai the strategy used. Costruct a shape for a give perimeter (cm, m). Costruct or draw more tha oe shape for the same perimeter. Estimate the perimeter of a shape (cm, m) usig persoal referets. 86 Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

12 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.SS.6. 3.SS.7. Strad: Shape ad Space (3-D Objects ad 2-D Shapes) Specific Learig Outcomes It is expected that studets will: Describe 3-D objects accordig to the shape of the faces, ad the umber of edges ad vertices. [C, CN, PS, R, V] Sort regular ad irregular polygos, icludig triagles quadrilaterals petagos hexagos octagos accordig to the umber of sides. [C, CN, R, V] Geeral Learig Outcome: Describe the characteristics of 3-D objects ad 2-D shapes, ad aalyze the relatioships amog them. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Idetify the faces, edges, ad vertices of a 3-D object, icludig cubes, spheres, coes, cyliders, pyramids, ad prisms. Idetify the shape of the faces of a 3-D object. Determie the umber of faces, edges, ad vertices of a 3-D object. Costruct a skeleto of a 3-D object, ad describe how the skeleto relates to the 3-D object. Sort a set of 3-D objects accordig to the umber of faces, edges, or vertices. Classify a set of regular ad irregular polygos accordig to the umber of sides. Idetify regular ad irregular polygos havig differet dimesios. Idetify regular ad irregular polygos havig differet orietatios. Geeral ad Specific Learig Outcomes 87

13 [C] Commuicatio [PS] Problem Solvig [CN] Coectios [R] Reasoig [ME] Metal Mathematics [T] Techology ad Estimatio [V] Visualizatio 3.SP.1. 3.SP.2. Strad: Statistics ad Probability (Data Aalysis) Specific Learig Outcomes It is expected that studets will: Collect first-had data ad orgaize it usig tally marks lie plots charts lists to aswer questios. [C, CN, V] Costruct, label, ad iterpret bar graphs to solve problems. [PS, R, V] Geeral Learig Outcome: Collect, display, ad aalyze data to solve problems. Achievemet Idicators The followig set of idicators may be used to determie whether studets have met the correspodig specific outcome. Record the umber of objects i a set usig tally marks. Determie the attributes of lie plots. Orgaize a set of data usig tally marks, lie plots, charts, or lists. Collect ad orgaize data usig tally marks, lie plots, charts, or lists. Aswer questios arisig from a lie plot, chart, or list. Aswer questios usig collected data. Determie the attributes of bar graphs. Create bar graphs from a set of data icludig labellig the title ad axes. Draw coclusios from a bar graph to solve problems. Solve problems by costructig ad iterpretig a bar graph. 88 Kidergarte to Grade 8 Mathematics: Maitoba Curriculum Framework of Outcomes (2013)

FOUNDATIONS OF MATHEMATICS AND PRE-CALCULUS GRADE 10

FOUNDATIONS OF MATHEMATICS AND PRE-CALCULUS GRADE 10 FOUNDATIONS OF MATHEMATICS AND PRE-CALCULUS GRADE 10 [C] Commuicatio Measuremet A1. Solve problems that ivolve liear measuremet, usig: SI ad imperial uits of measure estimatio strategies measuremet strategies.

More information

Mathematical goals. Starting points. Materials required. Time needed

Mathematical goals. Starting points. Materials required. Time needed Level A1 of challege: C A1 Mathematical goals Startig poits Materials required Time eeded Iterpretig algebraic expressios To help learers to: traslate betwee words, symbols, tables, ad area represetatios

More information

G r a d e. 2 M a t h e M a t i c s. statistics and Probability

G r a d e. 2 M a t h e M a t i c s. statistics and Probability G r a d e 2 M a t h e M a t i c s statistics ad Probability Grade 2: Statistics (Data Aalysis) (2.SP.1, 2.SP.2) edurig uderstadigs: data ca be collected ad orgaized i a variety of ways. data ca be used

More information

Laws of Exponents Learning Strategies

Laws of Exponents Learning Strategies Laws of Epoets Learig Strategies What should studets be able to do withi this iteractive? Studets should be able to uderstad ad use of the laws of epoets. Studets should be able to simplify epressios that

More information

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction THE ARITHMETIC OF INTEGERS - multiplicatio, expoetiatio, divisio, additio, ad subtractio What to do ad what ot to do. THE INTEGERS Recall that a iteger is oe of the whole umbers, which may be either positive,

More information

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is 0_0605.qxd /5/05 0:45 AM Page 470 470 Chapter 6 Additioal Topics i Trigoometry 6.5 Trigoometric Form of a Complex Number What you should lear Plot complex umbers i the complex plae ad fid absolute values

More information

Grade 7 Mathematics. Support Document for Teachers

Grade 7 Mathematics. Support Document for Teachers Grade 7 Mathematics Support Documet for Teachers G r a d e 7 M a t h e m a t i c s Support Documet for Teachers 2012 Maitoba Educatio Maitoba Educatio Cataloguig i Publicatio Data Grade 7 mathematics

More information

Solving equations. Pre-test. Warm-up

Solving equations. Pre-test. Warm-up Solvig equatios 8 Pre-test Warm-up We ca thik of a algebraic equatio as beig like a set of scales. The two sides of the equatio are equal, so the scales are balaced. If we add somethig to oe side of the

More information

7.1 Finding Rational Solutions of Polynomial Equations

7.1 Finding Rational Solutions of Polynomial Equations 4 Locker LESSON 7. Fidig Ratioal Solutios of Polyomial Equatios Name Class Date 7. Fidig Ratioal Solutios of Polyomial Equatios Essetial Questio: How do you fid the ratioal roots of a polyomial equatio?

More information

G r a d e. 5 M a t h e M a t i c s. Number

G r a d e. 5 M a t h e M a t i c s. Number G r a d e 5 M a t h e M a t i c s Number Grade 5: Number (5.N.1) edurig uderstadigs: the positio of a digit i a umber determies its value. each place value positio is 10 times greater tha the place value

More information

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here).

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here). BEGINNING ALGEBRA Roots ad Radicals (revised summer, 00 Olso) Packet to Supplemet the Curret Textbook - Part Review of Square Roots & Irratioals (This portio ca be ay time before Part ad should mostly

More information

Basic Elements of Arithmetic Sequences and Series

Basic Elements of Arithmetic Sequences and Series MA40S PRE-CALCULUS UNIT G GEOMETRIC SEQUENCES CLASS NOTES (COMPLETED NO NEED TO COPY NOTES FROM OVERHEAD) Basic Elemets of Arithmetic Sequeces ad Series Objective: To establish basic elemets of arithmetic

More information

BINOMIAL EXPANSIONS 12.5. In this section. Some Examples. Obtaining the Coefficients

BINOMIAL EXPANSIONS 12.5. In this section. Some Examples. Obtaining the Coefficients 652 (12-26) Chapter 12 Sequeces ad Series 12.5 BINOMIAL EXPANSIONS I this sectio Some Examples Otaiig the Coefficiets The Biomial Theorem I Chapter 5 you leared how to square a iomial. I this sectio you

More information

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,

More information

hands-on mathematics Geometry, Mental Math, Measurement, Number Concepts, Number Operations, Patterns and Relations, Statistics and Probability

hands-on mathematics Geometry, Mental Math, Measurement, Number Concepts, Number Operations, Patterns and Relations, Statistics and Probability 4 hads-o mathematics Geometry, Metal Math, Measuremet, Number Cocepts, Number Operatios, Patters ad Relatios, Statistics ad Probability Program Implemetatio Program Resources Hads-O Mathematics is arraged

More information

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig

More information

GCSE STATISTICS. 4) How to calculate the range: The difference between the biggest number and the smallest number.

GCSE STATISTICS. 4) How to calculate the range: The difference between the biggest number and the smallest number. GCSE STATISTICS You should kow: 1) How to draw a frequecy diagram: e.g. NUMBER TALLY FREQUENCY 1 3 5 ) How to draw a bar chart, a pictogram, ad a pie chart. 3) How to use averages: a) Mea - add up all

More information

AP Calculus BC 2003 Scoring Guidelines Form B

AP Calculus BC 2003 Scoring Guidelines Form B AP Calculus BC Scorig Guidelies Form B The materials icluded i these files are iteded for use by AP teachers for course ad exam preparatio; permissio for ay other use must be sought from the Advaced Placemet

More information

PUBLIC RELATIONS PROJECT 2016

PUBLIC RELATIONS PROJECT 2016 PUBLIC RELATIONS PROJECT 2016 The purpose of the Public Relatios Project is to provide a opportuity for the chapter members to demostrate the kowledge ad skills eeded i plaig, orgaizig, implemetig ad evaluatig

More information

2-3 The Remainder and Factor Theorems

2-3 The Remainder and Factor Theorems - The Remaider ad Factor Theorems Factor each polyomial completely usig the give factor ad log divisio 1 x + x x 60; x + So, x + x x 60 = (x + )(x x 15) Factorig the quadratic expressio yields x + x x

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern.

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern. 5.5 Fractios ad Decimals Steps for Chagig a Fractio to a Decimal. Simplify the fractio, if possible. 2. Divide the umerator by the deomiator. d d Repeatig Decimals Repeatig Decimals are decimal umbers

More information

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008 I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces

More information

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized?

5.4 Amortization. Question 1: How do you find the present value of an annuity? Question 2: How is a loan amortized? 5.4 Amortizatio Questio 1: How do you fid the preset value of a auity? Questio 2: How is a loa amortized? Questio 3: How do you make a amortizatio table? Oe of the most commo fiacial istrumets a perso

More information

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n We will cosider the liear regressio model i matrix form. For simple liear regressio, meaig oe predictor, the model is i = + x i + ε i for i =,,,, This model icludes the assumptio that the ε i s are a sample

More information

Biology 171L Environment and Ecology Lab Lab 2: Descriptive Statistics, Presenting Data and Graphing Relationships

Biology 171L Environment and Ecology Lab Lab 2: Descriptive Statistics, Presenting Data and Graphing Relationships Biology 171L Eviromet ad Ecology Lab Lab : Descriptive Statistics, Presetig Data ad Graphig Relatioships Itroductio Log lists of data are ofte ot very useful for idetifyig geeral treds i the data or the

More information

Your organization has a Class B IP address of 166.144.0.0 Before you implement subnetting, the Network ID and Host ID are divided as follows:

Your organization has a Class B IP address of 166.144.0.0 Before you implement subnetting, the Network ID and Host ID are divided as follows: Subettig Subettig is used to subdivide a sigle class of etwork i to multiple smaller etworks. Example: Your orgaizatio has a Class B IP address of 166.144.0.0 Before you implemet subettig, the Network

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

I. Chi-squared Distributions

I. Chi-squared Distributions 1 M 358K Supplemet to Chapter 23: CHI-SQUARED DISTRIBUTIONS, T-DISTRIBUTIONS, AND DEGREES OF FREEDOM To uderstad t-distributios, we first eed to look at aother family of distributios, the chi-squared distributios.

More information

3. Greatest Common Divisor - Least Common Multiple

3. Greatest Common Divisor - Least Common Multiple 3 Greatest Commo Divisor - Least Commo Multiple Defiitio 31: The greatest commo divisor of two atural umbers a ad b is the largest atural umber c which divides both a ad b We deote the greatest commo gcd

More information

Measures of Spread and Boxplots Discrete Math, Section 9.4

Measures of Spread and Boxplots Discrete Math, Section 9.4 Measures of Spread ad Boxplots Discrete Math, Sectio 9.4 We start with a example: Example 1: Comparig Mea ad Media Compute the mea ad media of each data set: S 1 = {4, 6, 8, 10, 1, 14, 16} S = {4, 7, 9,

More information

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals

Overview. Learning Objectives. Point Estimate. Estimation. Estimating the Value of a Parameter Using Confidence Intervals Overview Estimatig the Value of a Parameter Usig Cofidece Itervals We apply the results about the sample mea the problem of estimatio Estimatio is the process of usig sample data estimate the value of

More information

Working with numbers

Working with numbers 4 Workig with umbers this chapter covers... This chapter is a practical guide showig you how to carry out the types of basic calculatio that you are likely to ecouter whe workig i accoutig ad fiace. The

More information

NATIONAL SENIOR CERTIFICATE GRADE 11

NATIONAL SENIOR CERTIFICATE GRADE 11 NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS P EXEMPLAR 007 MARKS: 50 TIME: 3 hours This questio paper cosists of pages, 4 diagram sheets ad a -page formula sheet. Please tur over Mathematics/P DoE/Exemplar

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

NATIONAL SENIOR CERTIFICATE GRADE 12

NATIONAL SENIOR CERTIFICATE GRADE 12 NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS P EXEMPLAR 04 MARKS: 50 TIME: 3 hours This questio paper cosists of 8 pages ad iformatio sheet. Please tur over Mathematics/P DBE/04 NSC Grade Eemplar INSTRUCTIONS

More information

1 Computing the Standard Deviation of Sample Means

1 Computing the Standard Deviation of Sample Means Computig the Stadard Deviatio of Sample Meas Quality cotrol charts are based o sample meas ot o idividual values withi a sample. A sample is a group of items, which are cosidered all together for our aalysis.

More information

How To Solve The Homewor Problem Beautifully

How To Solve The Homewor Problem Beautifully Egieerig 33 eautiful Homewor et 3 of 7 Kuszmar roblem.5.5 large departmet store sells sport shirts i three sizes small, medium, ad large, three patters plaid, prit, ad stripe, ad two sleeve legths log

More information

CHAPTER 7: Central Limit Theorem: CLT for Averages (Means)

CHAPTER 7: Central Limit Theorem: CLT for Averages (Means) CHAPTER 7: Cetral Limit Theorem: CLT for Averages (Meas) X = the umber obtaied whe rollig oe six sided die oce. If we roll a six sided die oce, the mea of the probability distributio is X P(X = x) Simulatio:

More information

INDEPENDENT BUSINESS PLAN EVENT 2016

INDEPENDENT BUSINESS PLAN EVENT 2016 INDEPENDENT BUSINESS PLAN EVENT 2016 The Idepedet Busiess Pla Evet ivolves the developmet of a comprehesive proposal to start a ew busiess. Ay type of busiess may be used. The Idepedet Busiess Pla Evet

More information

Listing terms of a finite sequence List all of the terms of each finite sequence. a) a n n 2 for 1 n 5 1 b) a n for 1 n 4 n 2

Listing terms of a finite sequence List all of the terms of each finite sequence. a) a n n 2 for 1 n 5 1 b) a n for 1 n 4 n 2 74 (4 ) Chapter 4 Sequeces ad Series 4. SEQUENCES I this sectio Defiitio Fidig a Formula for the th Term The word sequece is a familiar word. We may speak of a sequece of evets or say that somethig is

More information

Modified Line Search Method for Global Optimization

Modified Line Search Method for Global Optimization Modified Lie Search Method for Global Optimizatio Cria Grosa ad Ajith Abraham Ceter of Excellece for Quatifiable Quality of Service Norwegia Uiversity of Sciece ad Techology Trodheim, Norway {cria, ajith}@q2s.tu.o

More information

Chapter 7: Confidence Interval and Sample Size

Chapter 7: Confidence Interval and Sample Size Chapter 7: Cofidece Iterval ad Sample Size Learig Objectives Upo successful completio of Chapter 7, you will be able to: Fid the cofidece iterval for the mea, proportio, ad variace. Determie the miimum

More information

1 Correlation and Regression Analysis

1 Correlation and Regression Analysis 1 Correlatio ad Regressio Aalysis I this sectio we will be ivestigatig the relatioship betwee two cotiuous variable, such as height ad weight, the cocetratio of a ijected drug ad heart rate, or the cosumptio

More information

Non-life insurance mathematics. Nils F. Haavardsson, University of Oslo and DNB Skadeforsikring

Non-life insurance mathematics. Nils F. Haavardsson, University of Oslo and DNB Skadeforsikring No-life isurace mathematics Nils F. Haavardsso, Uiversity of Oslo ad DNB Skadeforsikrig Mai issues so far Why does isurace work? How is risk premium defied ad why is it importat? How ca claim frequecy

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES Chapter 9 SEQUENCES AND SERIES Natural umbers are the product of huma spirit. DEDEKIND 9.1 Itroductio I mathematics, the word, sequece is used i much the same way as it is i ordiary Eglish. Whe we say

More information

CS100: Introduction to Computer Science

CS100: Introduction to Computer Science Review: History of Computers CS100: Itroductio to Computer Sciece Maiframes Miicomputers Lecture 2: Data Storage -- Bits, their storage ad mai memory Persoal Computers & Workstatios Review: The Role of

More information

Maximum Likelihood Estimators.

Maximum Likelihood Estimators. Lecture 2 Maximum Likelihood Estimators. Matlab example. As a motivatio, let us look at oe Matlab example. Let us geerate a radom sample of size 00 from beta distributio Beta(5, 2). We will lear the defiitio

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

Analyzing Longitudinal Data from Complex Surveys Using SUDAAN

Analyzing Longitudinal Data from Complex Surveys Using SUDAAN Aalyzig Logitudial Data from Complex Surveys Usig SUDAAN Darryl Creel Statistics ad Epidemiology, RTI Iteratioal, 312 Trotter Farm Drive, Rockville, MD, 20850 Abstract SUDAAN: Software for the Statistical

More information

CHAPTER 3 DIGITAL CODING OF SIGNALS

CHAPTER 3 DIGITAL CODING OF SIGNALS CHAPTER 3 DIGITAL CODING OF SIGNALS Computers are ofte used to automate the recordig of measuremets. The trasducers ad sigal coditioig circuits produce a voltage sigal that is proportioal to a quatity

More information

hp calculators HP 12C Statistics - average and standard deviation Average and standard deviation concepts HP12C average and standard deviation

hp calculators HP 12C Statistics - average and standard deviation Average and standard deviation concepts HP12C average and standard deviation HP 1C Statistics - average ad stadard deviatio Average ad stadard deviatio cocepts HP1C average ad stadard deviatio Practice calculatig averages ad stadard deviatios with oe or two variables HP 1C Statistics

More information

5.3. Generalized Permutations and Combinations

5.3. Generalized Permutations and Combinations 53 GENERALIZED PERMUTATIONS AND COMBINATIONS 73 53 Geeralized Permutatios ad Combiatios 53 Permutatios with Repeated Elemets Assume that we have a alphabet with letters ad we wat to write all possible

More information

Lesson 17 Pearson s Correlation Coefficient

Lesson 17 Pearson s Correlation Coefficient Outlie Measures of Relatioships Pearso s Correlatio Coefficiet (r) -types of data -scatter plots -measure of directio -measure of stregth Computatio -covariatio of X ad Y -uique variatio i X ad Y -measurig

More information

MEP Pupil Text 9. The mean, median and mode are three different ways of describing the average.

MEP Pupil Text 9. The mean, median and mode are three different ways of describing the average. 9 Data Aalysis 9. Mea, Media, Mode ad Rage I Uit 8, you were lookig at ways of collectig ad represetig data. I this uit, you will go oe step further ad fid out how to calculate statistical quatities which

More information

CREATIVE MARKETING PROJECT 2016

CREATIVE MARKETING PROJECT 2016 CREATIVE MARKETING PROJECT 2016 The Creative Marketig Project is a chapter project that develops i chapter members a aalytical ad creative approach to the marketig process, actively egages chapter members

More information

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed.

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed. This documet was writte ad copyrighted by Paul Dawkis. Use of this documet ad its olie versio is govered by the Terms ad Coditios of Use located at http://tutorial.math.lamar.edu/terms.asp. The olie versio

More information

Multiple Representations for Pattern Exploration with the Graphing Calculator and Manipulatives

Multiple Representations for Pattern Exploration with the Graphing Calculator and Manipulatives Douglas A. Lapp Multiple Represetatios for Patter Exploratio with the Graphig Calculator ad Maipulatives To teach mathematics as a coected system of cocepts, we must have a shift i emphasis from a curriculum

More information

WindWise Education. 2 nd. T ransforming the Energy of Wind into Powerful Minds. editi. A Curriculum for Grades 6 12

WindWise Education. 2 nd. T ransforming the Energy of Wind into Powerful Minds. editi. A Curriculum for Grades 6 12 WidWise Educatio T rasformig the Eergy of Wid ito Powerful Mids A Curriculum for Grades 6 12 Notice Except for educatioal use by a idividual teacher i a classroom settig this work may ot be reproduced

More information

Determining the sample size

Determining the sample size Determiig the sample size Oe of the most commo questios ay statisticia gets asked is How large a sample size do I eed? Researchers are ofte surprised to fid out that the aswer depeds o a umber of factors

More information

A Guide to the Pricing Conventions of SFE Interest Rate Products

A Guide to the Pricing Conventions of SFE Interest Rate Products A Guide to the Pricig Covetios of SFE Iterest Rate Products SFE 30 Day Iterbak Cash Rate Futures Physical 90 Day Bak Bills SFE 90 Day Bak Bill Futures SFE 90 Day Bak Bill Futures Tick Value Calculatios

More information

Definition. A variable X that takes on values X 1, X 2, X 3,...X k with respective frequencies f 1, f 2, f 3,...f k has mean

Definition. A variable X that takes on values X 1, X 2, X 3,...X k with respective frequencies f 1, f 2, f 3,...f k has mean 1 Social Studies 201 October 13, 2004 Note: The examples i these otes may be differet tha used i class. However, the examples are similar ad the methods used are idetical to what was preseted i class.

More information

The following example will help us understand The Sampling Distribution of the Mean. C1 C2 C3 C4 C5 50 miles 84 miles 38 miles 120 miles 48 miles

The following example will help us understand The Sampling Distribution of the Mean. C1 C2 C3 C4 C5 50 miles 84 miles 38 miles 120 miles 48 miles The followig eample will help us uderstad The Samplig Distributio of the Mea Review: The populatio is the etire collectio of all idividuals or objects of iterest The sample is the portio of the populatio

More information

Systems Design Project: Indoor Location of Wireless Devices

Systems Design Project: Indoor Location of Wireless Devices Systems Desig Project: Idoor Locatio of Wireless Devices Prepared By: Bria Murphy Seior Systems Sciece ad Egieerig Washigto Uiversity i St. Louis Phoe: (805) 698-5295 Email: bcm1@cec.wustl.edu Supervised

More information

Hypergeometric Distributions

Hypergeometric Distributions 7.4 Hypergeometric Distributios Whe choosig the startig lie-up for a game, a coach obviously has to choose a differet player for each positio. Similarly, whe a uio elects delegates for a covetio or you

More information

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the.

Confidence Intervals. CI for a population mean (σ is known and n > 30 or the variable is normally distributed in the. Cofidece Itervals A cofidece iterval is a iterval whose purpose is to estimate a parameter (a umber that could, i theory, be calculated from the populatio, if measuremets were available for the whole populatio).

More information

Approximating Area under a curve with rectangles. To find the area under a curve we approximate the area using rectangles and then use limits to find

Approximating Area under a curve with rectangles. To find the area under a curve we approximate the area using rectangles and then use limits to find 1.8 Approximatig Area uder a curve with rectagles 1.6 To fid the area uder a curve we approximate the area usig rectagles ad the use limits to fid 1.4 the area. Example 1 Suppose we wat to estimate 1.

More information

INVESTMENT PERFORMANCE COUNCIL (IPC)

INVESTMENT PERFORMANCE COUNCIL (IPC) INVESTMENT PEFOMANCE COUNCIL (IPC) INVITATION TO COMMENT: Global Ivestmet Performace Stadards (GIPS ) Guidace Statemet o Calculatio Methodology The Associatio for Ivestmet Maagemet ad esearch (AIM) seeks

More information

Escola Federal de Engenharia de Itajubá

Escola Federal de Engenharia de Itajubá Escola Federal de Egeharia de Itajubá Departameto de Egeharia Mecâica Pós-Graduação em Egeharia Mecâica MPF04 ANÁLISE DE SINAIS E AQUISÇÃO DE DADOS SINAIS E SISTEMAS Trabalho 02 (MATLAB) Prof. Dr. José

More information

Building Blocks Problem Related to Harmonic Series

Building Blocks Problem Related to Harmonic Series TMME, vol3, o, p.76 Buildig Blocks Problem Related to Harmoic Series Yutaka Nishiyama Osaka Uiversity of Ecoomics, Japa Abstract: I this discussio I give a eplaatio of the divergece ad covergece of ifiite

More information

GCE Further Mathematics (6360) Further Pure Unit 2 (MFP2) Textbook. Version: 1.4

GCE Further Mathematics (6360) Further Pure Unit 2 (MFP2) Textbook. Version: 1.4 GCE Further Mathematics (660) Further Pure Uit (MFP) Tetbook Versio: 4 MFP Tetbook A-level Further Mathematics 660 Further Pure : Cotets Chapter : Comple umbers 4 Itroductio 5 The geeral comple umber 5

More information

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature.

*The most important feature of MRP as compared with ordinary inventory control analysis is its time phasing feature. Itegrated Productio ad Ivetory Cotrol System MRP ad MRP II Framework of Maufacturig System Ivetory cotrol, productio schedulig, capacity plaig ad fiacial ad busiess decisios i a productio system are iterrelated.

More information

Confidence Intervals for One Mean

Confidence Intervals for One Mean Chapter 420 Cofidece Itervals for Oe Mea Itroductio This routie calculates the sample size ecessary to achieve a specified distace from the mea to the cofidece limit(s) at a stated cofidece level for a

More information

FM4 CREDIT AND BORROWING

FM4 CREDIT AND BORROWING FM4 CREDIT AND BORROWING Whe you purchase big ticket items such as cars, boats, televisios ad the like, retailers ad fiacial istitutios have various terms ad coditios that are implemeted for the cosumer

More information

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009)

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009) 18.409 A Algorithmist s Toolkit October 27, 2009 Lecture 13 Lecturer: Joatha Keler Scribe: Joatha Pies (2009) 1 Outlie Last time, we proved the Bru-Mikowski iequality for boxes. Today we ll go over the

More information

Learning objectives. Duc K. Nguyen - Corporate Finance 21/10/2014

Learning objectives. Duc K. Nguyen - Corporate Finance 21/10/2014 1 Lecture 3 Time Value of Moey ad Project Valuatio The timelie Three rules of time travels NPV of a stream of cash flows Perpetuities, auities ad other special cases Learig objectives 2 Uderstad the time-value

More information

3. If x and y are real numbers, what is the simplified radical form

3. If x and y are real numbers, what is the simplified radical form lgebra II Practice Test Objective:.a. Which is equivalet to 98 94 4 49?. Which epressio is aother way to write 5 4? 5 5 4 4 4 5 4 5. If ad y are real umbers, what is the simplified radical form of 5 y

More information

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations CS3A Hadout 3 Witer 00 February, 00 Solvig Recurrece Relatios Itroductio A wide variety of recurrece problems occur i models. Some of these recurrece relatios ca be solved usig iteratio or some other ad

More information

NATIONAL SENIOR CERTIFICATE GRADE 11

NATIONAL SENIOR CERTIFICATE GRADE 11 NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS P NOVEMBER 007 MARKS: 50 TIME: 3 hours This questio paper cosists of 9 pages, diagram sheet ad a -page formula sheet. Please tur over Mathematics/P DoE/November

More information

This document contains a collection of formulas and constants useful for SPC chart construction. It assumes you are already familiar with SPC.

This document contains a collection of formulas and constants useful for SPC chart construction. It assumes you are already familiar with SPC. SPC Formulas ad Tables 1 This documet cotais a collectio of formulas ad costats useful for SPC chart costructio. It assumes you are already familiar with SPC. Termiology Geerally, a bar draw over a symbol

More information

PUBLIC RELATIONS PROJECT 2015

PUBLIC RELATIONS PROJECT 2015 PUBLIC RELATIONS PROJECT 2015 Supported by MARKETING The purpose of the Public Relatios Project is to provide a opportuity for the chapter members to demostrate the kowledge ad skills eeded i plaig, orgaizig,

More information

5: Introduction to Estimation

5: Introduction to Estimation 5: Itroductio to Estimatio Cotets Acroyms ad symbols... 1 Statistical iferece... Estimatig µ with cofidece... 3 Samplig distributio of the mea... 3 Cofidece Iterval for μ whe σ is kow before had... 4 Sample

More information

MATHEMATICS P1 COMMON TEST JUNE 2014 NATIONAL SENIOR CERTIFICATE GRADE 12

MATHEMATICS P1 COMMON TEST JUNE 2014 NATIONAL SENIOR CERTIFICATE GRADE 12 Mathematics/P1 1 Jue 014 Commo Test MATHEMATICS P1 COMMON TEST JUNE 014 NATIONAL SENIOR CERTIFICATE GRADE 1 Marks: 15 Time: ½ hours N.B: This questio paper cosists of 7 pages ad 1 iformatio sheet. Please

More information

Descriptive Statistics

Descriptive Statistics Descriptive Statistics We leared to describe data sets graphically. We ca also describe a data set umerically. Measures of Locatio Defiitio The sample mea is the arithmetic average of values. We deote

More information

Professional Networking

Professional Networking Professioal Networkig 1. Lear from people who ve bee where you are. Oe of your best resources for etworkig is alumi from your school. They ve take the classes you have take, they have bee o the job market

More information

Chapter XIV: Fundamentals of Probability and Statistics *

Chapter XIV: Fundamentals of Probability and Statistics * Objectives Chapter XIV: Fudametals o Probability ad Statistics * Preset udametal cocepts o probability ad statistics Review measures o cetral tedecy ad dispersio Aalyze methods ad applicatios o descriptive

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

Week 3 Conditional probabilities, Bayes formula, WEEK 3 page 1 Expected value of a random variable

Week 3 Conditional probabilities, Bayes formula, WEEK 3 page 1 Expected value of a random variable Week 3 Coditioal probabilities, Bayes formula, WEEK 3 page 1 Expected value of a radom variable We recall our discussio of 5 card poker hads. Example 13 : a) What is the probability of evet A that a 5

More information

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling

Taking DCOP to the Real World: Efficient Complete Solutions for Distributed Multi-Event Scheduling Taig DCOP to the Real World: Efficiet Complete Solutios for Distributed Multi-Evet Schedulig Rajiv T. Maheswara, Milid Tambe, Emma Bowrig, Joatha P. Pearce, ad Pradeep araatham Uiversity of Souther Califoria

More information

CS100: Introduction to Computer Science

CS100: Introduction to Computer Science I-class Exercise: CS100: Itroductio to Computer Sciece What is a flip-flop? What are the properties of flip-flops? Draw a simple flip-flop circuit? Lecture 3: Data Storage -- Mass storage & represetig

More information

Mathematical Studies and Applications: Mathematics, Business Studies

Mathematical Studies and Applications: Mathematics, Business Studies POST-PRIMARY Mathematical Studies ad Applicatios: Mathematics, Busiess Studies Guidelies for Teachers of Studets with MILD Geeral Learig Disabilities Cotets Itroductio 3 Approaches ad methodologies 4 Exemplars

More information

CS103X: Discrete Structures Homework 4 Solutions

CS103X: Discrete Structures Homework 4 Solutions CS103X: Discrete Structures Homewor 4 Solutios Due February 22, 2008 Exercise 1 10 poits. Silico Valley questios: a How may possible six-figure salaries i whole dollar amouts are there that cotai at least

More information

Baan Service Master Data Management

Baan Service Master Data Management Baa Service Master Data Maagemet Module Procedure UP069A US Documetiformatio Documet Documet code : UP069A US Documet group : User Documetatio Documet title : Master Data Maagemet Applicatio/Package :

More information

COMPUTER LABORATORY IMPLEMENTATION ISSUES AT A SMALL LIBERAL ARTS COLLEGE. Richard A. Weida Lycoming College Williamsport, PA 17701 weida@lycoming.

COMPUTER LABORATORY IMPLEMENTATION ISSUES AT A SMALL LIBERAL ARTS COLLEGE. Richard A. Weida Lycoming College Williamsport, PA 17701 weida@lycoming. COMPUTER LABORATORY IMPLEMENTATION ISSUES AT A SMALL LIBERAL ARTS COLLEGE Richard A. Weida Lycomig College Williamsport, PA 17701 weida@lycomig.edu Abstract: Lycomig College is a small, private, liberal

More information

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection

The analysis of the Cournot oligopoly model considering the subjective motive in the strategy selection The aalysis of the Courot oligopoly model cosiderig the subjective motive i the strategy selectio Shigehito Furuyama Teruhisa Nakai Departmet of Systems Maagemet Egieerig Faculty of Egieerig Kasai Uiversity

More information

Elementary Theory of Russian Roulette

Elementary Theory of Russian Roulette Elemetary Theory of Russia Roulette -iterestig patters of fractios- Satoshi Hashiba Daisuke Miematsu Ryohei Miyadera Itroductio. Today we are goig to study mathematical theory of Russia roulette. If some

More information

A GUIDE TO LEVEL 3 VALUE ADDED IN 2013 SCHOOL AND COLLEGE PERFORMANCE TABLES

A GUIDE TO LEVEL 3 VALUE ADDED IN 2013 SCHOOL AND COLLEGE PERFORMANCE TABLES A GUIDE TO LEVEL 3 VALUE ADDED IN 2013 SCHOOL AND COLLEGE PERFORMANCE TABLES Cotets Page No. Summary Iterpretig School ad College Value Added Scores 2 What is Value Added? 3 The Learer Achievemet Tracker

More information