Students Knowledge and Strategies for Solving Equations
|
|
- Nicholas Warren
- 7 years ago
- Views:
Transcription
1 Studets Kowledge ad Strategies for Solvig Equatios Chris Lisell Uiversity of Otago College of Educatio This paper presets results from the secod year of a ivestigatio ito studets algebraic thikig. The assessmet techiques parallel those used for ivestigatig umber i the Numeracy Developmet Projects. I this study of 621 year 7 10 studets, oral iterviews with supplemetary questios were used to ivestigate the strategies that studets used to solve equatios. Basic facts, umeracy strategy stage, ad kowledge of aspects of algebra were also assessed. Rasch aalysis was used to ivestigate the difficulty of the equatios ad studet ability, ad the the strategies associated with each questio were examied. The data provides strog evidece that there is a hierarchy of sophisticatio of strategies. A large umber of the studets were uable to solve may of the equatios because they were restricted to less sophisticated strategies. Clear relatioships were foud betwee the most sophisticated strategy a studet used ad their umeracy stage, basic facts kowledge, ad algebraic kowledge. Itroductio The success of the Numeracy Developmet Projects (NDP) i raisig New Zealad studets achievemet i umber (Thomas & Tagg, 07; Youg-Loveridge, 07) has prompted iitiatives to exted the NDP ito early algebra. The NDP are cetred o the Number Framework (Miistry of Educatio, 03), which describes the progressio of studets arithmetical strategies ad the kowledge associated with these strategies. The study reported o here examies studets strategies for solvig liear equatios ad the relatioship of these strategies to umeracy ad to algebraic kowledge. The goal is to cotribute to a research base that may allow the developmet of a algebra framework. Backgroud May studets struggle with itroductory algebra, ad teachers have little to guide them i desigig programmes of learig. Little is kow about the effect of studets umeracy o the learig of early algebra or about the strategies that studets use to solve equatios. However, a useful summary of strategies used by studets is provided by Kiera (1992), who describes the use of kow basic facts, coutig techiques, guess-ad-check, cover-up, workig backwards, ad formal operatios. I this paper, Kiera s classificatio of strategies is modified ad exteded ad trasformatios is the term used to describe Kiera s formal operatios. There is a wealth of research o studets errors ad miscoceptios i algebra, some of which was summarised i the 07 fidigs from the Secodary Numeracy Project (SNP) (Lisell, 08). These difficulties iclude uderstadig of arithmetical structure, iverse operatios, algebraic otatio ad covetios, operatig o ukows, lack of closure, the equals sig, ad treatig equatios as processes rather tha objects. It ca be argued that much of the research adopts a deficit model approach, detailig what studets ca t do. A alterative approach is to ivestigate what studets actually do whe preseted with equatios to solve ad to examie the kowledge ad skills associated with the various strategies that differet studets use. Teachig how to solve equatios has traditioally focused o the type of equatios preseted to studets rather tha o the strategies that they are usig. If a studet is successful at solvig a give 29
2 Fidigs from the Secodary Numeracy Project 08 type of equatio, the teacher will ofte preset them with harder equatios, irrespective of whether the studet is solvig by, for example, guess-ad-check or workig backwards. To move to a approach more cosistet with the NDP, i which studets are taught accordig to the highest strategy they have available to them, more iformatio is eeded about how studets solve equatios. The research questios addressed i this study were: What is the relative difficulty of equatios? What strategies do studets use, ad is there a hierarchy of strategies? What is the impact of cotext o studets solutio strategies? What prerequisite kowledge is associated with each strategy? What stage of umeracy is associated with each strategy? Method This study examied relatioships betwee studets strategies for solvig equatios ad their umeracy stage, basic facts kowledge, algebraic kowledge, ad whether the equatios were symbolic or i cotext. A structured diagostic iterview was admiistered to idividual studets by the researcher or by the studets classroom teacher. The studets resposes were coded ad the aalysed makig use of Rasch aalysis (Wright & Masters, 1982). Algebraic kowledge was assessed by a writte test, while umeracy stage ad basic facts kowledge were assessed through routie procedures i place i the schools. Further details of the assessmet tools are provided by Lisell (08). Subjects The study took place i two itermediate schools (years 7 ad 8), two high schools (years 9 ad 10 oly) ad oe college (years 7 9 oly). There was o attempt at represetative samplig, but istead the aim was to collect data from a wide rage of studets. The iterview was admiistered to a total of 621 studets i year 7 ( = 196), year 8 ( = 3), year 9 ( = 25), ad year 10 ( = 137). Clearly, year 8 studets are uderrepreseted, but this is mitigated by the fact that iterviews took place throughout the school year, so studets at the begiig of year 9 ad the ed of year 7 were icluded. I the two schools i which there was streamig, all classes from each year level were icluded ad i all schools, o studets were excluded o the basis of ability. Diagostic Iterview The diagostic iterview was developed i a previous study (Lisell, McAuslad, Bell, et al., 06) ad was guided by the literature o studets strategies for solvig equatios (Herscovics & Lichevski, 199; Kiera, 1992). The iterview cosisted of a series of icreasigly complex equatios, which the studets were asked to solve alog with a explaatio of their thikig. The series icluded 12 pairs of parallel questios: oes that were i cotext (that is, word problems) ad oes that were purely symbolic. The questios were preseted o cards so that the more difficult questios could be omitted as required without suggestig to the studet that they were ot copig. Each questio was read to the studet to miimise the impact of readig difficulties, icludig difficulties with readig symbolic equatios. Calculators ad pecil ad paper were available for the studets to use, but it was stressed to the studets that they could use whatever method they chose. The iterviewer recorded what the studet did ad said ad the classified the strategy used accordig to Table 1. Note that there has bee a chage i termiology sice last year s report (Lisell, 08): strategy i, previously 30
3 Studets Kowledge ad Strategies for Solvig Equatios called formal operatios/equatio as object, is ow called trasformatios/equatio as object. This is i order to clarify that the strategy ivolves trasformig a equatio ito a ew equatio oe or more times ad is ot simply the followig of some give formal procedure. Table 1 Classificatio of Strategies for Solvig Equatios Code Strategy 0 Uable to aswer questio a b c d e f g h i Kow basic facts Coutig techiques Iverse operatio Guess-ad-check Cover up Workig backwards, the guess-ad-check Workig backwards, the kow fact Workig backwards Trasformatios/equatio as object Kowledge Test The assessmet of algebraic kowledge was admiistered as a writte test because supplemetary questios were ot required. The areas ivestigated i this sectio were: kowledge of covetios ad otatio, uderstadig of the equals sig, uderstadig of arithmetical structure, uderstadig of iverse operatios, ad acceptace of lack of closure. Numeracy Assessmet All the schools i this study were either NDP or SNP schools ad therefore routiely collected umeracy data o their studets. I istaces where this data was ot available, stage of umeracy was assessed usig a modified GloSS (Global Strategy Stage) ad kowledge of basic facts was assessed usig a modified sectio from NumPA (the Numeracy Project Assessmet tool). Data Aalysis The first stage i the aalysis was to determie the difficulty of the equatios ad the ability of the studets. I Rasch models, the probability of a specified respose (that is, a right/wrog aswer) is modelled as a logistic fuctio of the differece betwee the perso ad the item parameter. Before applyig this model to the data, it was therefore ecessary to ascertai that the variable of item difficulty was uidimesioal. Factor aalysis was iitially employed to verify that a oe-factor model was a adequate fit to the data from the strategy iterview. Followig this, Rasch aalysis was used to determie item difficulty ad studet ability. These scores were the related to the strategies that idividual studets used for each questio. A proposed hierarchy of strategies was the developed by examiig the distributios of ability of studets, usig each strategy o each questio. This permitted each studet to be classified accordig to the most sophisticated strategy they used o ay questio. From the umeracy assessmet ad algebraic kowledge test, each studet was assiged a score for umeracy, basic facts, covetios ad otatio, equivalece, arithmetical structure, iverse operatios, 31
4 Fidigs from the Secodary Numeracy Project 08 ad lack of closure. Relatioships betwee each of these measures ad the most sophisticated strategy used were the examied. Item Difficulty Results For equatios that were preseted symbolically, there was a huge variatio amog the studets i the umber of equatios that they were able to solve, with some questios beig much harder tha others (see Table 2). Table 2 Item Difficulty (Symbolic Equatios) Number of Studets Percetage of Studets Equatio with Correct Resposes with Correct Resposes Rasch Score (Item Difficulty) 3 = = = = = = = = = = = = Rearrage v = u + at I geeral, oe-step equatios were easier to solve tha two-step equatios, which i tur were easier to solve tha equatios with ukows o both sides. However, it should also be oted that equatios ivolvig divisio were harder to solve tha similar equatios with other operators. Nevertheless, oe-step equatios ivolvig divisio were easier to solve tha two-step equatios ivolvig divisio. Strategies Used Two strategies (trasformatios ad guess-ad-check) could be used to solve ay equatio, while others (for example, iverse operatio for oe-step equatios, workig backwards for two-step equatios) could be used for oly a limited umber of equatios. For every equatio (except for the fial oe) there was a rage of strategies successfully used by studets, but the distributio of strategies varied from questio to questio. Resposes to three questios are show i Figure 1 to illustrate the rages of strategies used. 32
5 Studets Kowledge ad Strategies for Solvig Equatios + 6 = Frequecy No successful Coutig Iverse Guess- Trasformatios strategy techiques operatio ad-check Strategy used 3 8 = Frequecy No successful Guess- Cover Workig Workig Workig Trasformatios strategy ad-check up backwards backwards backwards the guess- the kow ad-check fact Strategy used 5 2 = Frequecy No successful strategy Guess-ad-check Trasformatios Strategy used Figure 1. Studets strategies for three equatios 33
6 Fidigs from the Secodary Numeracy Project 08 Hierarchy of Strategies To establish a hierarchy of strategies was ot straightforward because the patter of strategy use varied from equatio to equatio, with some equatios ledig themselves to beig solved by oe strategy rather tha by aother. Aother difficulty was that able studets ofte reverted to guessad-check for difficult questios, eve though they used other strategies for easier equatios. Less able studets, i cotrast, used guess-ad-check for easy equatios ad were uable to solve more difficult equatios by ay strategy. Therefore, the approach used was to examie the strategies used o a questio-by-questio basis. For each questio, the ability of studets usig a particular strategy was ivestigated. Figure 2 shows the results 1 for the same three equatios show i Figure = Ability of studets (logits) No successful Coutig Iverse Guess- Trasformatios strategy techiques operatio ad-check Strategy used 3 8 = Ability of studets (logits) No successful Guess- Cover Workig Workig Workig Trasformatios strategy ad-check up backwards backwards backwards the guess- the kow ad-check fact Strategy used 1 Rasch aalysis calculates item difficulty ad studet ability o the same scale. 3
7 Studets Kowledge ad Strategies for Solvig Equatios 5 2 = Ability of studets (logits) No successful strategy Guess-ad-check Trasformatios Strategy used Figure 2. Ability of studets usig each strategy For each equatio, it was the possible to place the strategies i order accordig to the mea ability of studets usig each strategy. For example, the equatio 5 2 = was solved usig either guessad-check or trasformatios. The mea ability of studets usig trasformatios was higher tha that of studets usig guess-ad-check, idicatig that trasformatios was the more sophisticated strategy. The picture that emerged usig this approach was fairly cosistet, i that the order is the same for early all the equatios (see Table 3, i cojuctio with the explaatio of umbers i Table ). Table 3 Rak Order of Mea Abilities of Studets Usig Each Strategy for Each Equatio Strategy a b c d e f g h i Equatio 3 = = = = = = = = = = = = v = u + at 1 35
8 Fidigs from the Secodary Numeracy Project 08 For all equatios (except for = 5), trasformatios was the strategy used by the most able studets ad guess-ad-check by the least able. For oe-step equatios, it was ot possible to discer betwee coutig strategies ad kow basic facts because, although studets used a rage of strategies over all the equatios, for ay particular equatio this rage ever icluded both coutig ad kow basic facts. However, for three of the four oe-step equatios, iverse operatios were used by the more able studets rather tha by studets usig either coutig strategies or kow basic facts. The exceptio was = 5, which was far more difficult tha the other oe-step equatios. For this equatio, the most able studets solved it usig a kow basic fact. Cover up was used by such a small umber of studets that o clear relatioship to the other strategies emerged. For five of the six two-step equatios, workig backwards was used by the more able studets rather tha by those usig workig backwards, the kow fact, which i tur was used by the more able studets rather tha by those usig workig backwards, the guess-ad-check. The exceptio was + 12 = 18, but the umber of studets usig ay strategy other tha workig backwards was too small to draw ay coclusios. The strategies used oly o oe-step equatios clearly could ot be compared directly with those used oly o two-step equatios. However, two-step equatios are much harder tha oe-step, ad workig backwards ivolves usig iverse operatios. The order of sophisticatio of strategies idicated by this aalysis (see Table 3) is show i Table. Table Rak Order of Strategies Rak Strategy 1 No successful strategy 2 Guess-ad-check 3 Coutig techiques / Kow basic facts Iverse operatios 5 Workig backwards, the guess-ad-check 6 Workig backwards, the kow fact 7 Workig backwards 8 Trasformatios The studets were the classified accordig to the most sophisticated strategy they used o ay symbolic equatio (see Figure 3). 300 Frequecy Noe Guess- Coutig Iverse Workig Workig Workig Trasformatios ad-check or basic operatios backwards backwards backwards facts (guess- (kow fact) ad-check) Highest strategy 36 Figure 3. Most sophisticated strategy used o ay symbolic equatio
9 Studets Kowledge ad Strategies for Solvig Equatios The umber of studets able to solve equatios by performig trasformatios was very low (38). It is also worth otig that a sigificat umber of studets (89) were ot eve able to use iverse operatios. Also of ote is the umber of studets (65) who could solve some two-step equatios but who were ot fully workig backwards. Impact of Cotext The picture that emerged i relatio to studets solutios of equatios that were give to them as word problems i cotext was very similar to that of symbolic equatios. The diagostic iterview icluded 12 pairs of parallel questios. Table 5 shows the item difficulty of each questio. Note that the table shows the structure of the word problems, but the problems read to studets did ot iclude these equatios. For example, the first problem (show i the table as 5 = 17) was I left home this morig with some moey, spet $5, ad have $17 left. How much did I start with? Table 5 Item Difficulty (Rasch Scores) Symbolic I cotext Symbolic I cotext Equatio % correct Item difficulty % correct Item difficulty 1 3 = 12 5 = = 3 2 = = = = 5 = = = = = = = = = = = = = = 2 = Rearrage v = u + at (v + u)t Rearrage s = The harder equatios (with ukows o both sides) were slightly easier whe preseted symbolically. However, early all oe-step ad two-step equatios were easier whe preseted i cotext. There was oe exceptio (the secod pair of equatios) ad a few dramatic differeces i difficulty that will be commeted o whe the strategies that studets used are examied. For all of the oe-step equatios that were i cotext, compared with their symbolic couterparts, there was a greater use of iverse operatios tha of coutig strategies, kow facts, or guess-ad-check. This was true eve for the secod pair of equatios, i which the order of difficulty was reversed. The cotext was I have 2 CDs. This is three times as may as my brother has. How may CDs does he have? May more studets tha expected got this wrog by multiplyig 2 by 3 rather tha dividig. It would appear that the words three times cofused them. For the fourth, seveth, ad ith pairs of equatios, studets foud the symbolic form much more difficult tha oe might expect. All these equatios ivolved a divisio structure. The cotexts for 37
10 Fidigs from the Secodary Numeracy Project 08 the fourth ad seveth were: Whe I shared a packet of lollies roud my class of studets, they got each. How may lollies were i the packet? ad Our kapa haka group is made up of some Màori studets ad 11 Pàkehà studets. The whole group is divided ito equal-sized groups for practices. Each of the practice groups has 19 studets i it. How may Màori studets are there i our kapa haka group? It would appear that studets saw these as multiplicatio rather tha divisio problems ad foud them much easier tha the symbolic equivalets. For all of the two-step equatios, there was a greater proportio of studets usig the workig backwards strategy for equatios that were i cotext compared with those usig this strategy for symbolic equatios. Coversely, there was a greater proportio of studets usig less sophisticated strategies for symbolic equatios compared with those usig these strategies for equatios i cotext. There was also a small umber of studets who used trasformatios for two-step symbolic equatios. Prerequisite Skills ad Kowledge The relatioships betwee each studet s prerequisite kowledge ad skills ad the most sophisticated strategy that they were able to employ was the ivestigated. For these aalyses, those studets whose most sophisticated strategy was guess-ad-check, coutig, kow basic fact, or o successful strategy were grouped together as primitive strategies. Those studets whose most sophisticated strategy was either workig backwards, the guess-ad-check, or workig backwards, the kow fact, were grouped together as partially workig backwards. The relatioship betwee umeracy strategy stage ad highest algebraic strategy is show i Figure Highest algebraic strategy Primitive Iverse operatios Partial workig backwards Workig backwards Trasformatios Frequecy Coutig Advace Early Advaced Advaced Advaced strategies coutig additive additive multiplicative proportioal Numeracy strategy stage Figure. Relatioship betwee studets umeracy ad their most sophisticated strategy for solvig equatios It is clear that studets with poor umeracy skills were largely restricted to less sophisticated strategies. The great majority of studets with good umeracy skills were able to use more sophisticated strategies, with very few of them usig oly less sophisticated strategies. A very similar picture to this emerged for studets kowledge of basic facts. Studets with poor kowledge of basic facts 38
11 Studets Kowledge ad Strategies for Solvig Equatios were largely restricted to less sophisticated strategies, while most studets with good kowledge of basic facts were able to use the more sophisticated strategies. The relatioship betwee uderstadig of arithmetical structure ad highest algebraic strategy is show i Figure Highest algebraic strategy Primitive Iverse operatios Partial workig backwards Workig backwards Trasformatios Frequecy Very poor Poor Average Good Uderstadig of arithmetical structure Figure 5. Relatioship betwee studets uderstadig of arithmetical structure ad their most sophisticated strategy for solvig equatios Studets uderstadig of arithmetical structure had a dramatic impact o the most sophisticated strategy they were able to use. As their uderstadig of arithmetical structure icreased, so did their use of more sophisticated algebraic strategies. The pictures for uderstadig of iverse operatios, acceptace of lack of closure, ad uderstadig of equivalece were very similar. The oly area of kowledge that did ot have such a clear relatioship with sophisticatio of algebraic strategy was algebraic otatio ad covetio. Studets with good kowledge i this area used slightly more sophisticated strategies, but the relatioship was ot so covicig. Of particular ote is the impact of studets uderstadig of equivalece ad, to a slightly lesser extet, their acceptace of lack of closure (see Figure 6). 39
12 Fidigs from the Secodary Numeracy Project Highest algebraic strategy Primitive Iverse operatios Partial workig backwards Workig backwards Trasformatios Frequecy Very poor Poor Average Good Very good Excellet Uderstadig of equivalece Figure 6. Relatioship betwee studets uderstadig of equivalece ad their most sophisticated strategy for solvig equatios As studets uderstadig of equivalece icreased, the ratio of the umber of studets usig trasformatios to those usig workig backwards also icreased. Of those studets with a excellet uderstadig of equivalece, there was a greater umber usig trasformatios tha usig workig backwards. This differece i proportio betwee those usig workig backwards ad those usig trasformatios was ot so marked for the other areas of prerequisite kowledge ivestigated, although it was also large for acceptace of lack of closure. Discussio This study has demostrated how icredibly difficult some equatios are to solve compared with others. It has bee kow for a log time that studets fid equatios with ukows o both sides very difficult (Herscovics & Lichevski, 199), ad Sfard (1991) has eve suggested that viewig equatios as objects may be beyod the grasp of may studets. However, this study is the first to compare item difficulty o a Rasch scale. Rasch scores of item difficulty follow a approximately ormal distributio, ad to fid that some items have a difficulty score over two stadard deviatios above the mea cofirms their difficulty. The New Zealad Curriculum achievemet objectives (Miistry of Educatio, 07) give little idicatio of this difficulty. At level, the relevat objective is Form ad solve simple liear equatios, ad at level 5, it is Form ad solve simple liear ad quadratic equatios. The level 3 objective of Record ad iterpret additive ad simple multiplicative strategies, usig words, symbols, ad diagrams, with a uderstadig of equality is useful i focusig o equivalece, but it does ot spell out that studets eed to fid ukow values i ay positio i a statemet of equivalece. Educators eed to appreciate how huge the rage of difficulty is ad ot trivialise the solvig of equatios dow to a few lessos o specific procedures. Although equatios i cotext were geerally foud to be slightly easier tha symbolic equatios, the geeral picture for item difficulty was very similar whe the two sets of parallel questios were compared. This demostrates that it is primarily the structure of problems that makes them difficult, 0
13 Studets Kowledge ad Strategies for Solvig Equatios ot the algebraic symbolism. This fidig is backed up by the lack of a strog relatioship betwee studets uderstadig of algebraic otatio ad their most sophisticated algebraic strategy. Teachig of algebra should therefore be focusig o the structure of problems. The additioal difficulties that studets experieced with equatios ivolvig divisio highlight the eed for greater emphasis to be placed o a variety of operators withi both oe-step ad two-step equatios. Isights ito why studets foud some equatios so difficult to solve were obtaied by examiig the strategies they employed to solve them. It was clear that studets were usig a wide variety of strategies to solve all the equatios. For oe-step equatios, may studets were gettig correct solutios but ever used a iverse operatio. To attempt to move these studets o to two-step equatios would be courtig disaster. Iverse operatios are ivolved i all the successful strategies for two-step equatios other tha guess-ad-check. Studets are therefore likely to be reduced to usig guess-ad-check or learig a specific procedure that applies oly to specific structures. Similarly, may studets were obtaiig correct solutios to some two-step equatios but were oly partially usig workig backwards or were eve usig guess-ad-check. This poit, that the strategy of workig backwards is less homogeeous tha previously reported, is importat. May studets are oly just graspig the strategy ad ca use it oly whe the first step reveals a kow basic fact to them for the ext step. These studets use the strategy of workig backwards, the kow facts. Other studets are preveted from fully usig workig backwards because of lack of kowledge of multiplicatio ad divisio facts. These studets use the strategy of workig backwards, the guessad-check. To attempt to move these studets o to usig trasformatios would almost certaily be premature. Whe teachers suggest to studets that a equatio is like a balace pivoted about the equals sig, it is hard to imagie why it would be difficult to do the same thig to both sides of the equatio ad keep it balaced. However, this study has cofirmed just how difficult the strategy of usig trasformatios is for studets. Usig trasformatios requires seeig a equatio as a object to be acted o (Sfard, 1991), but it is clear that most studets see equatios as processes. I order to ivestigate the relative sophisticatio of strategies, it was assumed that the more sophisticated strategies would be chose by the more able studets. The fidigs usig this approach were cosistet with the fact that there was oly oe studet who was able to perform trasformatios but could ot also work backwards (this low-ability studet appeared to be followig a procedure of doig the same thig to both sides for simple equatios) ad that all studets who could work backwards could also use iverse operatios. This study has show that the strategy of solvig oestep equatios by iverse operatios is used by the more able studets rather tha by those who use either kow basic facts or coutig strategies. These strategies i tur were used by the more able studets rather tha by those who solved oe-step equatios usig guess-ad-check. Similarly, the strategies of solvig two-step equatios by partially workig backwards were used by less able studets rather tha by those fully workig backwards. O ay particular equatio, studets chose a strategy that was sufficiet to solve the equatio rather tha usig their most sophisticated strategy. However, it is suggested that the differet strategies are ot merely a matter of choice but that the most sophisticated strategy that a studet ever uses is idicative of coceptual developmet. The impact of cotext o studets ability to solve equivalet problems was very iterestig. I geeral, cotext problems were foud to be easier tha symbolic problems util the difficulty level of ukows o both sides was reached. However, most school programmes focus o teachig skills for solvig symbolic equatios. Solvig word problems is usually regarded as harder ad itroduced later as a applicatio of these skills. A alterative perspective o cotexts is to view them as models of the mathematics. Models are a importat feature of Realistic Mathematics Educatio (RME) (Gravemeijer, 1997). Traditioally, models are derived from formal mathematics, whereas i RME, models are derived from real situatios that studets have experieced ad are chose to reflect 1
14 Fidigs from the Secodary Numeracy Project 08 the iformal strategies of studets. Iitially, a model of a situatio that is familiar to the studets is used. Next, through geeralisig ad formalisig, the model becomes a etity i its ow right. Fially, it becomes possible to use the model for mathematical reasoig. Gravemeijer describes this as a trasitio from model-of to model-for. The ature of a model therefore evolves from beig highly cotext-specific to derivig its meaig from a mathematical framework. I cotrast, whe pre-existig models are give to studets to help them solve problems, the studets are expected to use them i prescribed ways that may ot be clear to them. The results from this study are cosistet with Gravemeijer s perspective ad suggest that algebra would be better itroduced i cotext rather tha just as symbols. The impact of cotext o the strategies that studets used may help to explai why studets foud these problems easier. For oe-step equatios, there was much higher use of iverse operatios tha of less sophisticated strategies. It appears likely that cotexts allow studets to perceive the structure of a problem i more tha oe way. For example, the problem Whe I shared a packet of lollies roud my class of studets, they got each. How may lollies were i the packet? has the structure =, but may be viewed as The umber of lollies is for each of the studets, with a structure of = x. The cotext is therefore aturally leadig the studet ito a iverse operatio. If this is the case, the the role of the teacher should be to scaffold the writig of symbolic equatios to describe cotexts ad the to explore ad symbolise the solutio strategies of the studets. There was a high correspodece betwee umeracy strategy stage ad the most sophisticated strategy a studet was able to use to solve equatios. Oly for studets who were at the advaced multiplicative or advaced proportioal thikig stages did the majority solve equatios by usig workig backwards or trasformatios. Studets at lower stages of umeracy were largely restricted to less sophisticated strategies. The fidigs from this study strogly suggest that prerequisite umeracy should be cosidered whe desigig teachig programmes for algebra. However, there were studets who did ot score highly o GloSS but were able to use sophisticated strategies for solvig equatios. These studets were ivariably efficiet at usig algorithms for computatios ad ofte came from primary schools that did ot promote NDP umeracy. The algebra diagostic tool may be more useful tha GloSS for revealig the thikig of studets at the upper ed of the Number Framework. This is because GloSS focuses o metal strategies (ad does ot value the use of algorithms), whereas the algebra tool has a focus o studets uderstadig of mathematical structure. There was a very strog relatioship betwee studets kowledge of basic facts ad their highest algebraic strategy. Ay studet who was at stage 6 or below o the Number Framework for basic facts was ulikely to be able to solve equatios by workig backwards or by trasformatios. This fidig emphasises the critical importace of istat recall of all basic facts, icludig multiplicatio ad divisio. There were also strog associatios betwee studets highest algebraic strategies ad their uderstadig of arithmetical structure, iverse operatios, lack of closure, ad equivalece. There was ot such a strog associatio betwee studets highest algebraic strategies ad their kowledge of algebraic covetios ad otatio. The relatioship betwee studets highest algebraic strategy ad their uderstadig of equivalece was particularly iterestig. Uderstadig of equivalece ad, to a lesser extet, acceptace of lack of closure had much higher impacts o whether a studet could use trasformatios compared with usig the strategy of workig backwards tha did the other areas of algebraic kowledge. Give the reasoably large umber of studets who could work backwards ad the very small umber who could use trasformatios, these fidigs may have sigificat implicatios for teachig. 2
15 Studets Kowledge ad Strategies for Solvig Equatios Coclusios Cosistet with the perspective of Filloy ad Sutherlad (1996), it is suggested that the strategies described i this study are ot simply alterative approaches to solvig equatios but represet differet stages of coceptual developmet. Istead of lookig at how hard equatios are to solve ad whether studets get them right, it appears to be more useful to look at the strategies that studets use. The approach used i this study is very similar to that used i the NDP, with strategy beig separated out from the kowledge required for strategy use. This approach allows the classificatio of the studets accordig to their most sophisticated strategy rather tha by the most difficult equatio they are able to solve. Withi umeracy teachig, studets are grouped for istructio accordig to their most sophisticated strategy. It is suggested that a similar approach to groupig studets is likely to be beeficial for teachig studets to solve equatios. Also cosistet with the NDP, the teachig of prerequisite kowledge eeds to be addressed. To solve oe-step equatios, studets eed to uderstad iverse operatios ad to kow their basic facts. To solve two-step equatios by workig backwards, studets also eed to uderstad arithmetical structure. To solve equatios by usig trasformatios, studets eed to uderstad equivalece ad also accept lack of closure. The third area of fidigs cosistet with the NDP cocers the role of cotext. Questios that were i cotext were easier tha equivalet symbolic questios. This suggests that a versio of the umeracy teachig model should be employed for teachig algebra. We should start with cotexts that are meaigful to studets, preferably ivolvig cocrete materials. Teachers should scaffold studets so that they ca symbolise the structure of the problems ad their solutio strategies before expectig them to visualise a cocrete represetatio ad fially to operate o abstract symbolic structures. Refereces Filloy, E., & Sutherlad, R. (1996). Desigig curricula for teachig ad learig algebra. I A. Bishop, K. Clemets, C. Keitel, J. Kilpatrick, & C. Laborde (Eds), Iteratioal hadbook of mathematics educatio (Vol. 1, pp ). Dordrecht: Kluwer. Gravemeijer, K. (1997). Istructioal desig for reform i mathematics educatio. I M. Beishuize, K. Gravemeijer, & E. Va Lieshout (Eds), The role of cotexts ad models i the developmet of mathematical strategies ad procedures (pp. 13 3). Utrecht: Freudethal Istitute. Herscovics, N., & Lichevski, L. (199). A cogitive gap betwee arithmetic ad algebra. Educatioal Studies i Mathematics, 27(1), Kiera, C. (1992). The learig ad teachig of school algebra. I D. A. Grouws (Ed.), Hadbook of research o mathematics teachig ad learig (pp ). New York: Macmilla. Lisell, C. (08). Solvig equatios: Studets algebraic thikig. I Fidigs from the New Zealad Secodary Numeracy Project 07 (pp. 39 ). Welligto: Learig Media. Lisell, C., McAuslad, E., Bell, M., Savell, J., & Johsto, N. (06). Usig actio research to lear about learig algebra. Paper preseted at the New Zealad Associatio for Research i Educatio, December, 06. Miistry of Educatio (03). The Number Framework. Welligto: Miistry of Educatio. Miistry of Educatio (07). The New Zealad Curriculum. Welligto: Miistry of Educatio. Sfard, A. (1991). O the dual ature of mathematical coceptios: Reflectios o processes ad objects as two sides of the same coi. Educatioal Studies i Mathematics, 22, Thomas, G., & Tagg, A. (07). Do they cotiue to improve? Trackig the progress of a cohort of logitudial studets. I Fidigs from the New Zealad Numeracy Developmet Projects 06 (pp. 8 15). Welligto: Learig Media. Wright, B. D., & Masters, G. N. (1982). Ratig scale aalysis: Rasch measuremet. Chicago: MESA. Youg-Loveridge, J. (07). Patters of performace ad progress o the Numeracy Developmet Projects: Fidigs from 06 for years 5 9 studets. I Fidigs from the New Zealad Numeracy Developmet Projects 06 (pp ). Welligto: Learig Media. 3
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 informationMathematical 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 informationExample 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 informationTHE 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 informationIn 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 informationDetermining 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 information1 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 informationLesson 15 ANOVA (analysis of variance)
Outlie Variability -betwee group variability -withi group variability -total variability -F-ratio Computatio -sums of squares (betwee/withi/total -degrees of freedom (betwee/withi/total -mea square (betwee/withi
More informationHere 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 informationCHAPTER 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 informationG 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 informationLesson 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 informationChapter 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 informationI. 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 informationPSYCHOLOGICAL STATISTICS
UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION B Sc. Cousellig Psychology (0 Adm.) IV SEMESTER COMPLEMENTARY COURSE PSYCHOLOGICAL STATISTICS QUESTION BANK. Iferetial statistics is the brach of statistics
More information7.1 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 informationMultiple 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 informationHypothesis testing. Null and alternative hypotheses
Hypothesis testig Aother importat use of samplig distributios is to test hypotheses about populatio parameters, e.g. mea, proportio, regressio coefficiets, etc. For example, it is possible to stipulate
More information1 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 informationBasic 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 informationSolving 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 informationDefinition. 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 informationSolving Logarithms and Exponential Equations
Solvig Logarithms ad Epoetial Equatios Logarithmic Equatios There are two major ideas required whe solvig Logarithmic Equatios. The first is the Defiitio of a Logarithm. You may recall from a earlier topic:
More informationSoving 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 informationConfidence 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 informationThe 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 information1. C. The formula for the confidence interval for a population mean is: x t, which was
s 1. C. The formula for the cofidece iterval for a populatio mea is: x t, which was based o the sample Mea. So, x is guarateed to be i the iterval you form.. D. Use the rule : p-value
More informationTHE 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 information5: 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 informationMeasures 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 informationOverview. 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 informationINVESTMENT 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 informationSTUDENTS PARTICIPATION IN ONLINE LEARNING IN BUSINESS COURSES AT UNIVERSITAS TERBUKA, INDONESIA. Maya Maria, Universitas Terbuka, Indonesia
STUDENTS PARTICIPATION IN ONLINE LEARNING IN BUSINESS COURSES AT UNIVERSITAS TERBUKA, INDONESIA Maya Maria, Uiversitas Terbuka, Idoesia Co-author: Amiuddi Zuhairi, Uiversitas Terbuka, Idoesia Kuria Edah
More informationChapter 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.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 informationCenter, Spread, and Shape in Inference: Claims, Caveats, and Insights
Ceter, Spread, ad Shape i Iferece: Claims, Caveats, ad Isights Dr. Nacy Pfeig (Uiversity of Pittsburgh) AMATYC November 2008 Prelimiary Activities 1. I would like to produce a iterval estimate for the
More informationCS103A 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 informationModified 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 informationConfidence 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 informationHypergeometric 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 informationTrigonometric 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 informationBuilding 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 informationThe Forgotten Middle. research readiness results. Executive Summary
The Forgotte Middle Esurig that All Studets Are o Target for College ad Career Readiess before High School Executive Summary Today, college readiess also meas career readiess. While ot every high school
More informationFOUNDATIONS 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 informationBiology 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 informationwhere: T = number of years of cash flow in investment's life n = the year in which the cash flow X n i = IRR = the internal rate of return
EVALUATING ALTERNATIVE CAPITAL INVESTMENT PROGRAMS By Ke D. Duft, Extesio Ecoomist I the March 98 issue of this publicatio we reviewed the procedure by which a capital ivestmet project was assessed. The
More informationHow to read A Mutual Fund shareholder report
Ivestor BulletI How to read A Mutual Fud shareholder report The SEC s Office of Ivestor Educatio ad Advocacy is issuig this Ivestor Bulleti to educate idividual ivestors about mutual fud shareholder reports.
More informationGCSE 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 informationCase Study. Normal and t Distributions. Density Plot. Normal Distributions
Case Study Normal ad t Distributios Bret Halo ad Bret Larget Departmet of Statistics Uiversity of Wiscosi Madiso October 11 13, 2011 Case Study Body temperature varies withi idividuals over time (it ca
More informationLaws 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 informationCHAPTER 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 informationGOOD PRACTICE CHECKLIST FOR INTERPRETERS WORKING WITH DOMESTIC VIOLENCE SITUATIONS
GOOD PRACTICE CHECKLIST FOR INTERPRETERS WORKING WITH DOMESTIC VIOLENCE SITUATIONS I the sprig of 2008, Stadig Together agaist Domestic Violece carried out a piece of collaborative work o domestic violece
More informationTradigms of Astundithi and Toyota
Tradig the radomess - Desigig a optimal tradig strategy uder a drifted radom walk price model Yuao Wu Math 20 Project Paper Professor Zachary Hamaker Abstract: I this paper the author iteds to explore
More informationAP 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 informationBINOMIAL 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 information3. 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 informationProperties of MLE: consistency, asymptotic normality. Fisher information.
Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout
More informationCHAPTER 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 informationA 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 informationMath C067 Sampling Distributions
Math C067 Samplig Distributios Sample Mea ad Sample Proportio Richard Beigel Some time betwee April 16, 2007 ad April 16, 2007 Examples of Samplig A pollster may try to estimate the proportio of voters
More informationG 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 informationIncremental calculation of weighted mean and variance
Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically
More information6. p o s I T I v e r e I n f o r c e M e n T
6. p o s I T I v e r e I f o r c e M e T The way positive reiforcemet is carried out is more importat tha the amout. B.F. Skier We all eed positive reiforcemet. Whether or ot we are cosciously aware of
More informationAnalyzing 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 informationNATIONAL 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 informationUM USER SATISFACTION SURVEY 2011. Final Report. September 2, 2011. Prepared by. ers e-research & Solutions (Macau)
UM USER SATISFACTION SURVEY 2011 Fial Report September 2, 2011 Prepared by ers e-research & Solutios (Macau) 1 UM User Satisfactio Survey 2011 A Collaboratio Work by Project Cosultat Dr. Agus Cheog ers
More informationDepartment 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*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 informationSequences 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 informationElementary 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 informationProfessional 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 informationGrade 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 information5.4 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 informationSolutions to Selected Problems In: Pattern Classification by Duda, Hart, Stork
Solutios to Selected Problems I: Patter Classificatio by Duda, Hart, Stork Joh L. Weatherwax February 4, 008 Problem Solutios Chapter Bayesia Decisio Theory Problem radomized rules Part a: Let Rx be the
More informationSEQUENCES 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 informationInference on Proportion. Chapter 8 Tests of Statistical Hypotheses. Sampling Distribution of Sample Proportion. Confidence Interval
Chapter 8 Tests of Statistical Hypotheses 8. Tests about Proportios HT - Iferece o Proportio Parameter: Populatio Proportio p (or π) (Percetage of people has o health isurace) x Statistic: Sample Proportio
More informationNon-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 informationMEI Structured Mathematics. Module Summary Sheets. Statistics 2 (Version B: reference to new book)
MEI Mathematics i Educatio ad Idustry MEI Structured Mathematics Module Summary Sheets Statistics (Versio B: referece to ew book) Topic : The Poisso Distributio Topic : The Normal Distributio Topic 3:
More informationAsymptotic Growth of Functions
CMPS Itroductio to Aalysis of Algorithms Fall 3 Asymptotic Growth of Fuctios We itroduce several types of asymptotic otatio which are used to compare the performace ad efficiecy of algorithms As we ll
More information15.075 Exam 3. Instructor: Cynthia Rudin TA: Dimitrios Bisias. November 22, 2011
15.075 Exam 3 Istructor: Cythia Rudi TA: Dimitrios Bisias November 22, 2011 Gradig is based o demostratio of coceptual uderstadig, so you eed to show all of your work. Problem 1 A compay makes high-defiitio
More informationHow 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 informationSystems 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 informationPROCEEDINGS OF THE YEREVAN STATE UNIVERSITY AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM
PROCEEDINGS OF THE YEREVAN STATE UNIVERSITY Physical ad Mathematical Scieces 2015, 1, p. 15 19 M a t h e m a t i c s AN ALTERNATIVE MODEL FOR BONUS-MALUS SYSTEM A. G. GULYAN Chair of Actuarial Mathematics
More informationA 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 informationVolatility of rates of return on the example of wheat futures. Sławomir Juszczyk. Rafał Balina
Overcomig the Crisis: Ecoomic ad Fiacial Developmets i Asia ad Europe Edited by Štefa Bojec, Josef C. Brada, ad Masaaki Kuboiwa http://www.hippocampus.si/isbn/978-961-6832-32-8/cotets.pdf Volatility of
More informationLECTURE 13: Cross-validation
LECTURE 3: Cross-validatio Resampli methods Cross Validatio Bootstrap Bias ad variace estimatio with the Bootstrap Three-way data partitioi Itroductio to Patter Aalysis Ricardo Gutierrez-Osua Texas A&M
More informationApplication and research of fuzzy clustering analysis algorithm under micro-lecture English teaching mode
SHS Web of Cofereces 25, shscof/20162501018 Applicatio ad research of fuzzy clusterig aalysis algorithm uder micro-lecture Eglish teachig mode Yig Shi, Wei Dog, Chuyi Lou & Ya Dig Qihuagdao Istitute of
More informationDOCUMENT RESUME. Powell, Evan R.; Dennis, Virginia Collier
DOCUMENT RESUME ED 075 970 EC 051 775 AUTHOR Powell, Eva R.; Deis, Virgiia Collier TITLE No-Verbal Commuicatio i Retarded Pupils. PUB DATE Feb 73 NOTE 9p.; A paper preseted at the America Educatioal Research
More informationA probabilistic proof of a binomial identity
A probabilistic proof of a biomial idetity Joatho Peterso Abstract We give a elemetary probabilistic proof of a biomial idetity. The proof is obtaied by computig the probability of a certai evet i two
More informationMaximum 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 informationEstimating Probability Distributions by Observing Betting Practices
5th Iteratioal Symposium o Imprecise Probability: Theories ad Applicatios, Prague, Czech Republic, 007 Estimatig Probability Distributios by Observig Bettig Practices Dr C Lych Natioal Uiversity of Irelad,
More informationODBC. Getting Started With Sage Timberline Office ODBC
ODBC Gettig Started With Sage Timberlie Office ODBC NOTICE This documet ad the Sage Timberlie Office software may be used oly i accordace with the accompayig Sage Timberlie Office Ed User Licese Agreemet.
More informationConvexity, Inequalities, and Norms
Covexity, Iequalities, ad Norms Covex Fuctios You are probably familiar with the otio of cocavity of fuctios. Give a twicedifferetiable fuctio ϕ: R R, We say that ϕ is covex (or cocave up) if ϕ (x) 0 for
More informationAPPENDIX V TWO-YEAR COLLEGE SURVEY
APPENDIX V TWO-YEAR COLLEGE SURVEY GENERAL INSTRUCTIONS Coferece Board of the Mathematical Scieces SURVEY OF PROGRAMS i MATHEMATICS AND COMPUTER SCIENCE i TWO-YEAR COLLEGES 1990 This questioaire should
More informationIMPROVING AWARENESS ABOUT THE MEANING OF THE PRINCIPLE OF MATHEMATICAL INDUCTION
IMPROVING AWARENESS ABOUT THE MEANING OF THE PRINCIPLE OF MATHEMATICAL INDUCTION Aalisa Cusi ad Nicolia A. Malara This work is based o our covictio that it is possible to miimize difficulties studets face
More informationForecasting techniques
2 Forecastig techiques this chapter covers... I this chapter we will examie some useful forecastig techiques that ca be applied whe budgetig. We start by lookig at the way that samplig ca be used to collect
More informationDAME - Microsoft Excel add-in for solving multicriteria decision problems with scenarios Radomir Perzina 1, Jaroslav Ramik 2
Itroductio DAME - Microsoft Excel add-i for solvig multicriteria decisio problems with scearios Radomir Perzia, Jaroslav Ramik 2 Abstract. The mai goal of every ecoomic aget is to make a good decisio,
More informationCURIOUS MATHEMATICS FOR FUN AND JOY
WHOPPING COOL MATH! CURIOUS MATHEMATICS FOR FUN AND JOY APRIL 1 PROMOTIONAL CORNER: Have you a evet, a workshop, a website, some materials you would like to share with the world? Let me kow! If the work
More informationhp 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