Teaching and Learning Guide 10: Matrices

Size: px
Start display at page:

Download "Teaching and Learning Guide 10: Matrices"

Transcription

1 Teching nd Lerning Guide : Mtrices

2 Teching nd Lerning Guide : Mtrices Tle of Contents Section : Introduction to the guide. Section : Definitions nd Opertions.. The concept of definitions nd opertions. Presenting the concept of definitions nd opertions.5. Delivering the concept of definitions nd mtri opertions nd to smll or lrger groups..6. Discussion Questions.. 5. ctivities. 6. Top Tips. 7. Conclusion Section : Trnsposing nd Inverting Mtri nd Mtri Determinnts. The concept of trnsposition, inversion nd mtri determinnts.. Presenting the concept of trnsposition, inversion nd mtri determinnts6. Delivering the concept of trnsposition, inversion nd mtri determinnts to smll or lrger groups.8. Discussion Questions ctivities.9 6. Top Tips.9 7. Conclusion Section : Crmer s Rule... The concept of Crmer s rule... Presenting the concept of Crmer s rule. Delivering the concept of Crmer s rule to smll or lrger groups.. Discussion Questions ctivities.5 6. Top Tips.8 7. Conclusion 8 Section 5: Input-Output nlysis. 8. The concept of input-output nlysis8. Presenting the concept of input-output nlysis.9. Delivering the concept of input-output nlysis to smll or lrger groups.. Discussion Questions.. 5. ctivities. 6. Top Tips.5 7. Conclusion 5 Pge of 5

3 Teching nd Lerning Guide : Mtrices Section : Introduction to the guide This guide is designed to set out some of the sic mthemticl concepts needed to tech economics nd finncil economics t undergrdute level. The concepts covered y this guide re (i) the dimensions of mtri nd surrounding voculry; (ii) ddition, sutrction, multipliction nd division of mtrices; (iii) mtri trnsposition; (iv) mtri inversion; (v) finding the determinnt of mtri; (vi) Crmer's rule; (vii) Input-Output nlysis. It is very useful to use Ecel to ssist teching the topic of mtrices. Ecel hs lrge numer of in uilt functions to help find the trnspose nd inverse of mtrices. It lso hs n inuilt function to multiply mtrices. One key issue in mtri multipliction is conformility. Ecel focuses on conformility directly s efore you undertke ny mtri opertions in Ecel you need to determine the dimension of the resultnt mtri nd highlight selection of cells mtching this dimension. If you highlight n incorrect dimension Ecel is unle to undertke the clcultion. The use of Ecel is n essentil tool for nyone working in finnce. Throughout this guide Ecel screenshots nd links to files re provided. It would e useful therefore if the session utilising this mteril were presented in clssroom where students cn gin hnds on eperience. Mtrices re commonly used in finnce. s consequence numer of the emples hve finnce is. These include (i) using mtrices to clculte covrince mtri; (ii) using mtrices to clculte the risk of shre portfolio. n emple of how mtrices re used in journl rticle is included s teching nd lerning ctivity. This is n ecellent wy of demonstrting to students tht lerning mthemticl techniques is not simply cse of lerning for the ske of lerning. It is not lwys possile to find pproprite emples in journl rticles ut the one included in this guide is set t suitle level. The lecturer is lso directed to n lterntive rticle for n eercise tht could e used s tutoril or emintion question. With the use of Ecel for mtri multipliction nd inversion it is less pprent on the reltive dvntge of using Crmmers rule over stndrd techniques to find solutions to prolems. n lgeric sed emple is included to show tht Crmmers rule is still useful. This topic is Pge of 5

4 Teching nd Lerning Guide : Mtrices most definitely doing topic. Consequently lrge numer of emples re included to help the lecturer. Section : Definitions nd Opertions. The concept of definitions nd opertions Mtrices re difficult topic for mny students nd set of cler definitions re very importnt. These will need to e revisited to ensure students hve secure understnding of the key terms. Some definitions tht might e useful include: ) Defining mtri mtri is rectngulr rry of numers, prmeters or vriles rrnged in some meningful order. The elements (or prmeters or vriles) re referred to s the elements of mtri. The elements in horizontl line constitute row of the mtri nd it follows tht the elements in verticl line constitute column of the mtri. The entries in mtri re usully enclosed in two curved lines or squre rckets. Thus the generl mtri with m rows nd n columns cn therefore e written s: m m. n n mn The element in the i th row nd the j th column is ij. If we cll the mtri ove,, we cn sometimes void writing the mtri out in full, nd insted write, very succinctly,. ) Defining the dimensions mtri, like the one ove, with m rows nd n columns is clled n m y n or n m n mtri. This determines the dimensions of the mtri. Lecturers could remind students tht in our emple tht m is the numer of rows nd n is the numer of columns nd lso to e cler tht the row numer lwys precedes the column numer. Pge of 5

5 Teching nd Lerning Guide : Mtrices. Presenting the concept of definitions nd opertions It is esy to present mtrices s purely strct nd theoreticl concept. The dnger of such n pproch is tht the mthemtics cn e perceived y students to ecome nd end in itself; tht the point of lerning out mtrices is simply to prctise methodology nd pss n em. The most effective presenttions of mtrices will continully contetulise mtrices nd give rel world emples to support the conceptul frmework. In some wys, with hrd topic like mtrices the lecturer might even find tht there is rel impertive to put mtrices into n pplied setting lmost s wy to convince students tht it is vlid, tht mtrices re legitimte tool which cn inform economic prolems. For emple, the following emple is intended to show tht mtrices re compct wy of rticulting mthemticl prolems. Consider the risk (mesured y vrince) of two sset stock portfolio cn e written s: σ where : σ σ p σ σ is the proportion of welth invested in sset, is the proportion of welth invested in sset, is the vrince of sset, σ is the vrince of sset, σ is the covrince etween ssets nd. This formul cn e etended to, or n ssets. However s we etend the numer of ssets the numer of terms gets lrger. In prticulr if we hve n ssets there n(n-)/ covrince terms to write down, i.e. n there re 99/ 95 covrince terms. Therefore epressing this eqution in its liner form cn ecome prolemtic s the numer of ssets gets lrge. Pge 5 of 5

6 Teching nd Lerning Guide : Mtrices However this eqution cn e generlised to m ssets nd written more compctly using σ p ' where : mtrices. is vector of portfolio weights (welth invested), is mtri of covrinces etween ssets Hopefully, students will gree tht the second representtion is esier to rememer!. Delivering the concept of definitions nd mtri opertions nd to smll or lrger groups In terms of delivering the nuts nd olts of sic mtri opertion, there is little sustitute for ctully going through the methods with students either in lecture or tutoril setting. Students will need to see cler emples of ddition, sutrction, etc., nd rief overview is provided elow to help collegues deliver this introductory mteril. This is not intended to replce good tetook pproch ut could inform set of PowerPoint slides or lecture hndout. Mtri opertions ddition: Remind students tht with regulr lger we could write c, wheres with mtri lger we would write C B. They will need to know tht in order to do this, mtrices nd B must e of the sme dimension. If this is the cse then ech element of one mtri is dded to the corresponding element of the other mtri. Thus if nd B re oth mtrices element will e dded to, dded to, dded to nd dded to. ddition: Worked Emple 7 9, B B Pge 6 of 5

7 Teching nd Lerning Guide : Mtrices Sutrction: gin, students could look t regulr lger where we could write c -, wheres with mtri lger we would write C - B. However in order to do this, mtrices nd B must e of the sme dimension. If this is the cse then ech element of one mtri is sutrcted from the corresponding element of the other mtri. Thus if nd B re oth mtrices element will e sutrcted from to, sutrcted from, sutrcted from nd sutrcted from. Sutrction: Worked Emple 7 9, B B Sclr Multipliction Students will need to e cler tht in liner lger rel numer such s 9, - or.6 is clled sclr. Moreover, they will need to see tht the multipliction of mtri y sclr involves multipliction of ech element of the mtri y the sclr nd tht this type of multipliction is esy to rememer s it scles the mtri up or down ccording to the vlue of the mtri. Sclr Multipliction: Worked Emple 7, k k 6 The Ecel file contining the solutions to these three prolems cn e found online t Pge 7 of 5

8 Teching nd Lerning Guide : Mtrices Lecturers might wnt to flg up to students tht in order to undertke mtri ddition, sutrction nd sclr multipliction in Ecel you must first of ll define the nme of the mtri or vector. For emple, in this spredsheet we must first of ll highlight cells B:C then select Insert, Nme, Define nd cll this rnge of cells. Repet for B. Then when it comes to dding to B, the result of which will lso e mtri, you must first of ll highlight lock of cells nd then type B. But rther thn pressing Enter you must press CTRLSHIFTENTER together to otin the nswer. Multipliction It is often useful strting point to stte tht it is often esiest with mtri or vector multipliction to sk yourself wht the nswer will e first of ll. Students will need to know tht mtri multipliction in Ecel requires this s you hve first of ll highlight the cells where the nswer will e displyed. Students could e referred ck to the originl emple where the dimensions of mtri were stted s m n where m is the numer of rows nd n is the numer of columns. The net Pge 8 of 5

9 Teching nd Lerning Guide : Mtrices step could e to eplin tht to multiply (m n) mtri y nother (n m) then the resultnt mtri would e m m nd the multipliction opertion hs only een possile since the numer of columns in the first mtri (the led mtri) is equl to the numer of columns in the second mtri (the lg mtri). Hint: suggestion s wy to rememer this mde y Dowling (99) is to plce the two sets of dimensions in the order in which they re to e multiplied. Then circle (mentlly or physiclly) the lst numer of the led mtri dimensions nd the first numer of the lg mtri dimensions. If the two numers re equl then they re conformle (i.e. mtri multipliction is possile in the given order). Furthermore, the outer numers will provide the dimensions of the product mtri. Multipliction: Worked emple Below we consider the multipliction of mtri y mtri B, i.e. B. Dimensions of mtri Dimensions of mtri B Is B possile? ( ) ( ) Yes, numer of columns in () equls the numer of rows in B () ( ) ( ) Yes, numer of columns in () equls the numer of rows in B () ( ) ( ) Yes, numer of columns in () equls the numer of rows in B () (5 ) ( 5) Yes, numer of columns in () equls the numer of rows in B () ( ) ( ) Yes, numer of columns in () equls the numer of rows in B () No, numer of columns in () is ( ) ( ) not equl to the numer of rows in B () Dimensions of resultnt mtri ( ) - rows nd columns ( ) - rows nd columns ( ) - sclr ( 5 5) - 5 rows nd 5 columns ( ) - rows nd column N/ Pge 9 of 5

10 Teching nd Lerning Guide : Mtrices ( ) ( ) (5 ) (5 ) No, numer of columns in () is not equl to the numer of rows in B () No, numer of columns in () is not equl to the numer of rows in B (5) N/ N/ Links with the online question nk Generl questions on mtrices cn e found t: nd questions focused specificlly on multipliction re lso locted t: Discussion Questions Students could e sked to reserch some usiness or economics dt which they present s simple mtri e.g. shre dt, GDP figures over time etc 5. ctivities CTIVITY ONE Lerning Ojectives LO: Students lern how to complete mtri multipliction LO: Students lern how to use Ecel to complete mtri multipliction LO: Students lern how to use the mtri opertors Tsk One If: 6 nd B Clculte () B nd () B. Pge of 5

11 Teching nd Lerning Guide : Mtrices Tsk Two n ecellent wy of reinforcing students understnding of mtri multipliction is to use Ecel. The pproprite function is MMULT. There re two key differences when using this function compred to the mjority of Ecel functions: Rther thn pressing Enter or clicking OK if using the function wizrd you must press CTRL Shift Enter together to tell Ecel to undertke the clcultions. Since the outcome of this function is usully going to e something other thn sclr you must inform Ecel where to disply the output. Thus if the outcome is ( ) mtri you must first of ll highlight rows nd column efore strting to use the function. Students might wish to see video showing these opertions eing undertken using Ecel Tsk Three If: nd B Clculte B. NSWERS CTIVITY ONE Tsk One Rememering wht we hve lerned previously nd following the helpful hint: ( ) ( ) ( ) Therefore whichever wy we perform the multipliction the result will e mtri. Pge of 5

12 Teching nd Lerning Guide : Mtrices Pge of B B Tsk Two - Tsk Three B 6. Top Tips Tip : Specil cses Lecturers will wnt to ensure tht the specil cses re fully understood. Tht is: squre mtri in squre mtri the numer of rows equls the numer of columns. squre mtri differs from other mtrices in tht it hs digonls. The digonl leding from top left to ottom right is clled the min digonl. squre mtri which hs ll its elements zero ecept for those long its min digonl, nd these re ll ones, is clled unit mtri or identity mtri. mtri composed of severl rows nd single column hs dimensions m nd is referred to s column vector. mtri composed of single row nd severl columns hs dimensions n nd is referred to s row vector. This could e presented in simple templte or perhps s spider digrm. Tip : Multipliction When pproching this topic is fr esier to let students ecome cquinted with multiplying vectors efore they move onto multiplying mtrices. Before ttempting mtri multipliction students should consider will the dimensions of the resultnt mtri e?

13 Teching nd Lerning Guide : Mtrices 7. Conclusion This preprtory work will e crucil to the susequent success students chieve with higher level nd more comple mtri work. ny scheme of work should ensure tht plenty of time is given for students to prctise these sic opertions nd for one-to-one support to e given to remedy ny initil prolems. Section : Trnsposing nd Inverting Mtri nd Mtri Determinnts. The concept of trnsposition, inversion nd mtri determinnts s noted erlier, this is topic which students will perceive s difficult. This is compounded y the rther opque terminology used nd one key responsiility incument upon lecturers is to help students mke sense of these lels nd concepts. ) Trnsposition For emple to show tht the term trnsposition is ctully something quite simple s: If the rows nd columns of mtri re interchnged the new mtri is known s the trnspose of the originl mtri. E.g. If then the trnspose, ' This could even e introduced using imges rther thn numers such s: If Z Pge of 5

14 Teching nd Lerning Guide : Mtrices Then Z nd then more formlly tht If then ' ) Determinnts Similrly, lecturers could use simple ut forml overview y stting tht the determinnt is squre group of numers set out in mtri formt ut enclosed y stright rther thn curved Pge of 5

15 Teching nd Lerning Guide : Mtrices lines. It is importnt tht students hve mstered find the determinnt of mtri efore progressing to nd ove. The determinnts of orders nd re defined s: For emple, finding the vlue of the following determinnts of order : 5 5 ( ) ( )( ) c) Inversion Similrly, suppose we hve mtri : c d Then the inverse of is: d c Hence to otin the inverse of squre mtri of order we: Step : interchnge the elements on the min digonl, Step : chnge the sign of the other two elements, Pge 5 of 5

16 Teching nd Lerning Guide : Mtrices Step : divide y the determinnt corresponding to the originl mtri. This is simple teching sequence of core concept ut one through which students will need to e guided crefully.. Presenting the concept of trnsposition, inversion nd mtri determinnts Trnspositions re firly strightforwrd to tech nd lecturers might wnt to focus on inversions nd mtri determinnts. n outline of mteril tht could e presented is set out elow Inversions Inversions re something which students need to prctise. Students cn e reminded tht in trditionl rithmetic division is the reciprocl or inversion of multipliction. If we consider sy divided y, to tke simple emple, we sy tht ¼ nd ¼. In mtri lger we define inversion using the sme pproch. We sy tht the inverse of squre mtri is nother squre mtri B where: B I nd B I where I is the identity mtri of the sme order. Such mtri B, if it eists, is unique nd is clled the inverse of (written s - ). Consequently we hve: - I nd - I Students could consider these two squre mtrices: 7 nd 7 - Pge 6 of 5

17 Teching nd Lerning Guide : Mtrices Pge 7 of 5 Multiplying these two together we get: 7 ) ( ) ( 7 7 ) ( ) ( Or, 7 ) ( ) ( 7 ) ( 7 ) ( Clerly these two mtrices re inverses of one nother nd students need to understnd this technique Determinnts Students will need to e wre of the process for clculting determinnts including the notion of co-fctors. gin, some useful mteril is provided elow which cn e incorported into notes or slides. discussion of the determinnts of mtri will need to first introduce the concept of cofctors. Students could e shown tht Corresponding to ech element ij, of mtri,, there is cofctor, ij. nd tht it follows tht mtri hs nine elements, so there re nine cofctors, to e computed. The cofctor, ij, is defined to e the determinnt of the mtri otined y deleting row i nd column j of, prefied y either sign or s - sign. The prefies re ssigned ccording to the following pttern:

18 Teching nd Lerning Guide : Mtrices For emple, suppose we wish to clculte, which is the cofctor ssocited with in the mtri: The element lies in the third row nd second column. Consequently we delete the third row nd the second column to produce the mtri: The cofctor, is the determinnt of this mtri prefied y - sign due to the ssigning pttern ove, i.e. ( ) Now we hve introduced the cofctor concept we cn move onto showing the determinnt of mtri. The determinnt of the generl mtri is s follows: Students should note tht every one of these si products of elements contins ectly one element from ech row nd ectly one element from ech column.. Delivering the concept of trnsposition, inversion nd mtri determinnts to smll or lrger groups Lecturers could deliver this mteril through series of forml lectures ut supplement with student-led tutorils. For emple, students could e invited to sign-up to deliver mini-lectures Pge 8 of 5

19 Teching nd Lerning Guide : Mtrices covering one or more these topics nd other students re required to sign-up to ttend t lest two s udience memers. This cn e simple ut effective technique to help students grsp the essentils of mtri lger; if student cn deliver concise nd cogent overview then they re very likely to hve understood the mteril. This teching strtegy could e differentited y piring higher ility with lower ility students to led ech workshop. Links with the online question nk Questions on determinnts cn e found on the METL wesite t: whilst tsks centred on mtri inversion re ville from: Discussion Questions Students could e encourged to ring ny prolem sets they hve een working on into tutoril nd to discuss ny prolems they hve encountered. This could identify to the lecturer or tutor ny common misunderstndings or res of difficulty nd inform the tutor s tutoril scheme of work. This co-construction of future teching nd lerning ojectives is n importnt prt of successful ssessment for Lerning strtegy. 5. ctivities CTIVITY ONE Lerning Ojectives LO: Students hve opportunity to refresh clcultion of verges LO: Students to lern how to clculte verges using mtrices LO: Students lern how mtrices cn e used in pplied economics Consider the dt elow which re the weekly stock price returns of three UK gmling stocks: SPORTINGBET 888 HOLDINGS PRTYGMING 7/7/ /7/ /7/ Pge 9 of 5

20 Teching nd Lerning Guide : Mtrices 7/8/ /8/ /8/ /8/ /9/ /9/ /9/ /9/ // The verge weekly return is: Sporting Bet -8.7% 888 Holdings -.8% Prtygming -.8% Tsk One Using mtrices how would I find the verge return of Sporting Bet? Tsk Two Confirm tht the verge of oth 888 Holdings nd Prtygming is -.8% CTIVITY TWO Lerning Ojectives LO: Students lern the mening nd significnce of covrince LO: Students lern how to clculte vrince using mtri lger LO: Students lern how to pply mtri lger to solve n pplied economics prolem LO: Students lern how to mke n economic inference using covrince informtion Bckground informtion The vrince of portfolio cn e clculted s: Pge of 5

21 Teching nd Lerning Guide : Mtrices σ p ' where : is vector of portfolio weights (welth invested), is mtri of covrinces etween ssets For four sset cse this would look like the following when epnded out: σ p where : i ( ) is the weight invested in sset i, σ is the covrince etween sset i nd j, ij σ σ σ σ σ σ σ σ σ σ σ σ σ σ σ σ Note here we first of ll multiply () row vector y () mtri to otin () row vector which is multiplied y () column vector to give () nswer. Tsk One Let us ssume the following covrinces etween four UK stocks: Covrince MMO nd Mrks Spencer Brclys Scottish Power MMO Mrks nd Spencer Brclys Scottish Power Clculte the vrince of n eqully weighted ( i.5) portfolio using mtri lger Tsk Two Wht cn you infer out risk? Pge of 5

22 Teching nd Lerning Guide : Mtrices CTIVITY THREE Lerning Ojectives LO: Students lern how to find the inverse of mtri LO: Students lern how to clculte the determinnt Tsk One Find the inverse of the following mtri 5 Tsk Two Find the determinnt of the following mtri: 5 9 Tsk Three Find the inverse of the following mtri: CTIVITY FOUR Lerning Ojectives LO: Students lern how to independently clculte determinnts LO: Students lern how to mke inferences out whether mtri is singulr or not LO: Tsk One Find the determinnt of the following mtri: Pge of 5

23 Teching nd Lerning Guide : Mtrices Tsk Two Find the determinnt of the following mtri: 9 NSWERS CTIVITY ONE Tsk One n verge is found y dding up series of numers nd dividing y the numer tht they re. So for the series ove there re twelve numers so we dd them together nd divide y. To replicte the figure of -8.7% ove using mtrices we would multiply:.8 ( ) Tsk Two Students should confirm through mtri lger tht the ssertion is indeed correct. Pge of 5

24 Teching nd Lerning Guide : Mtrices CTIVITY TWO Tsk One σ p ( ) Note tht the digonl elements here re the individul vrinces of the four stocks. We cn see tht MMO is the most voltile stock. Interestingly, we lso see tht MMO nd Scottish Power hve negtive covrince. Using the MMULT commnd in Ecel we cn find the nswer very esily: ' ' ' 5.56 Pge of 5

25 Teching nd Lerning Guide : Mtrices Tsk Two Notice tht the nswer of 5.56 is less thn ny of the individul vrinces nd hence we cn reduce risk y putting 5% of our welth in ech sset rther thn putting ll our eggs in one sket. This spredsheet is ville t Note when crrying out these clcultions using Ecel it is possile to nest functions s follows: Note: Rther thn referring to n rry of cells s sy B:E (s in the screen shot ove) it is possile to nme the rnge of cells (Using Insert, Nme, Define ). You could therefore replce B:E with sigm in the emple ove. Pge 5 of 5

26 Teching nd Lerning Guide : Mtrices CTIVITY THREE Tsk One Tsk Two Epnding y the rd row (due to the presence of zero): ( 9) ( 5 ) 6 8 Tsk Three Tsk Three First of ll finding the determinnt y epnding y column : det() (6-9) ( 9) (9-) Then finding the nine cofctors: (6 9) 7 ( 9) (9 ) ( ) ( ) ( ) ( ) ( ) ( ) Putting these in-order forms the djugte mtri: Pge 6 of 5

27 Teching nd Lerning Guide : Mtrices 7 Then tking the trnspose of the djugte mtri to form the djoint mtri: 7 This ws very stright forwrd tsk due to the symmetry of the djugte mtri. The inverse is therefore: 7 7 Why hve we done ll this? Hopefully, students will e questioning why there hs een so much emphsis on finding the determinnts nd inverses of mtrices. In order to reinforce tht it is time well spent we should use numer of emples. CTIVITY FOUR Tsk One Epnding y the rd row (due to the presence of zero): ( 5 5) ( 5 5) 5 5 The vlue of the determinnt is zero. This implies tht the corresponding mtri is singulr nd hence hs no inverse. Pge 7 of 5

28 Teching nd Lerning Guide : Mtrices Pge 8 of 5 Tsk Two The first thing to sk if the pttern of s nd - s. This is just n etension of the pttern introduced erlier: The net thing to consider is wht row or column is it optiml to epnd y. If we look closely we will see tht row nd column oth hve two zero s which will reduce the numer of clcultion. Therefore we should choose either of those. Epnding y column : 9 We now hve to find the determinnts of the cofctor mtrices. Consider the term efore the minus sign nd epnding y row : ( ) ( ) { } ( ) { } ( ) Now considering the term fter the minus sign nd epnding y row : 9 9 ( ) ( ) { } 9 9

29 Teching nd Lerning Guide : Mtrices { ( 5) ( ) } { } The determinnt of this mtri is therefore Top Tips Tip : Demonstrte to students tht It is lso possile to find the inverse of mtrices using Ecel. gin you must highlight the cells where you would like the result to disply. The pproprite function is MINVERSE. Pge 9 of 5

30 Teching nd Lerning Guide : Mtrices Tip : Students might find it helpful to think of cofctors using simple shded digrm nd to then see the pttern ecomes evident. In the tle elow we strt in the top left cell (representing element ) nd then highlight cell in different row nd different column ( ). By defult the only remining cell to choose tht is from different column nd different row is the ottom right (representing element ). We then strt gin with the sme top left cell highlighted ut select different second row cell ( ) which in turn forces us to select s the third row cell. We continue this process until we hve ehusted ll the potentil comintions tht hve cell from different column nd row highlighted. The lgeric epression ove cn e fctored out to ecome: ( ) ( ) ( ) Hopefully we recognised tht the terms inside the rckets re the cofctors of the elements outside the rckets. We should lso recognise the pttern of s nd - s from the tle ove. Pge of 5

31 Teching nd Lerning Guide : Mtrices Tip : With mny topics in mthemtics there eists more thn one method to find the solution to prolem. One method populr with students for finding the determinnt of mtri is s follows (using the emple ove): 5 9 shortcut involves dding copy of the first nd second rows s follows: nd then multiplying s follows: sum 7 nd: sum9 5 9 The difference etween these is then 7-9 8, which s we found erlier is the determinnt of the mtri. You could sk the students why this works. The nswer of course is tht this is simply n lterntive fctoristion of the epression given ove. Pge of 5

32 Teching nd Lerning Guide : Mtrices 7. Conclusion Crete opportunities in scheme if work for students to work through prolem sets in pirs. This cn e helpful tool to rise ny prolems or queries tht students might hve. This topic drws upon nd pulls together mny different ut complementry threds nd students re likely to enefit from this collortion. Section : Crmer s Rule. The concept of Crmer s rule simple sttement t the eginning of lecture will prove helpful. Perhps: The method offered y Crmer s rule llows us to finds the vlue of one vrile t time nd this method requires less effort if only selection of the vriles is required. Crmmers rule for solving ny n n system,, sttes tht the i th vrile, i, cn e found from: i i Where i is the n n mtri formed y replcing the i th column of y the right-hnd side vector,.. Presenting the concept of Crmer s rule Students will wnt to see simple presenttion of how Crmer s rule works in prctice. One strtegy for doing this is set out elow: Consider the simple system considered previously: 7 P Q 9 nd suppose tht we need to find the vlue of the second vrile, Q. Pge of 5

33 Teching nd Lerning Guide : Mtrices ccording to Crmmers rule: Q Where 7 nd hence nd nd hnce 79 ( ) Therefore Q -5/-6. Delivering the concept of Crmer s rule to smll or lrger groups worked emple is offered elow to help collegues delivering the concept. Smller groups will proly hve more scope to discuss ech step outlined: Worked emple of Crmer s rule Consider the following three interconnected mrkets: Mrket : Q S 6P 8 nd Q D -5P P P Mrket : Q S P nd Q D P -P P 5 Mrket : Q S P 5 nd Q D P P - P 9 These mrkets re simultneously in equilirium when quntity supplied equls quntity demnded in ll three mrkets: Mrket : 6P 8-5P P P Mrket : P P -P P 5 Mrket : P 5 P P - P 9 Rerrnging these epressions so tht they cn e written in mtri form: Pge of 5

34 Teching nd Lerning Guide : Mtrices Mrket : P - P - P Mrket : -P 6P - P 6 Mrket : - P -P 7P Hence, in mtri form: 6 P P 6 7 P Or. Using the mtri inversion pproch we would e required to invert the mtri, which involves finding its determinnt nd the nine cofctors. Using Crmmers rule we still hve to find the determinnt of mtri ut we then only hve to find the determinnt of the three i mtrices P, P 7, P Or using the inversion pproch: Pge of 5

35 Teching nd Lerning Guide : Mtrices Students should note however the reltive merits of Crmmers rule over the inversion pproch only pplies to mnul clcultions. The screen shot elow shows how quick it ws to find the solutions to these prolems simply y using the inversion pproch. The file is ville online t: Links with the online question nk See Discussion Questions Students could discuss why Crmer s rule offers n dvntge in terms of clcultion. 5. ctivities Lerning Ojectives LO: Students lern the prcticl ppliction of Crmer s rule to ntionl income determintion Pge 5 of 5

36 Teching nd Lerning Guide : Mtrices LO: Students pply their knowledge to simple prolem of evluting ntionl income Tsk One Given the following typicl Ntionl Income model found in most introductory mcroeconomics tet ooks: Y C I G C Y d T ty Where Y Income, Y d disposle income, C Consumption, TTtion, mrginl propensity to consume, t rte of ttion, I utonomous Investment nd G utonomous Government spending. Hence: Re-writing the three equtions in terms of Y, C nd T we otin: Y C I G C (Y-T) Y T nd so Y C T -ty T These three equtions cn e represented in mtri form s: Y I G C t T Using Crmmers rule we cn solve for the equilirium levels of Y nd/or C nd/or T s follows: Pge 6 of 5

37 Teching nd Lerning Guide : Mtrices Pge 7 of 5 ( ) t G I t t G I t G I Y ) ( ) ( t t G I t t t t G I t t G I C ) ( ) ( ) ( ) ( t G t I t t t G I t t t G I T ) ( ) ( ) ( ) ( We therefore hve lgeric solutions tht llow us to consider wht would hppen to the equilirium levels of Y, C nd T if, for emple, the Government chnged G or t. Tsk One () Review the ove eposition of Crmer s rule. () ssume tht I, G,.7 nd t.. Wht is the vlue of Y?

38 Teching nd Lerning Guide : Mtrices NSWER Tsk One () I G 5 5 Y 6.6 t ( I G) ( t) ( ).7 (.8) 5.56 C 66.6 t.. ( I G) t ( ). T 7.7 t.. Y C I G Top Tips sk students to use Ecel wherever they cn to rticulte nd solve mtri lger prolems. Cn they show their nswer to 5. (see ove) using Ecel? 7. Conclusion Students could e sked to crete their own plenry s prt of conclusion on Crmer s rule. For emple, how does Crmer s rule help us s economists? Wht sort of economic issues might it e prticulrly pplicle to? This evlution of Crmer s rule could e good wy to conclude this topic. Section 5: Input-Output nlysis. The concept of input-output nlysis This mteril could e prefced y eplining tht in clssicl economic nlysis it is ssumed tht country s economic ctivity cn e divided into numer of industries which produce goods nd services. In ddition, it is further ssumed tht the end product of ll these industries work is finl consumer demnd. Pge 8 of 5

39 Teching nd Lerning Guide : Mtrices This cn then e linked to input-output nlysis: it is further ssumed tht chnges in demnd for ny of the finl outputs from ny industry ffect the outputs tht it requires from other industries.. Presenting the concept of input-output nlysis ij ij j Students will need sound nd forml eplntion to which they cn relte when ttempting pplied questions on their own. For emple, students could e shown tht we cn rticulte input-output nlysis s follows: Let: j e the totl output of industry j, ij e the output of industry i to industry j nd ij is constnt. If there re n industries under considertion: i n j ij y i Where y i is the output of industry i to finl demnd. Students should note tht this eqution holds since totl output of n industry must go either s inputs to other industries or to finl demnd. Comining these two equtions students cn see tht we otin: i n j ij j y i i n j ij j y i Epnding out the summtion sign nd consider for ll vlues of i from to n: Pge 9 of 5

40 Teching nd Lerning Guide : Mtrices n.. n n n n nn n n n y y y n Clerly it is possile to group the s, s etc. together in mtri form s follows: n n n n n nn n y y y n If we crete mtri of input-output coefficients, : n n n n n nn Then the mtri on the left is: I Where I is the identity mtri of order n. Students might wnt to revisit their erlier notes nd mteril t this point. Lecturers could highlight tht we often cll the column of totl outputs X, nd the column vector of outputs to finl demnd Y, then: (I )XY Pge of 5

41 Teching nd Lerning Guide : Mtrices nd hence: X(I-) - Y (ssuming tht the inverse of (I ) eists. This is n importnt result since if we re given the required outputs to finl demnd of ech industry nd provided we know the input-output coefficients we cn otin the required totl outputs of ech industry.. Delivering the concept of input-output nlysis to smll or lrger groups Worked emple Working ntionl input-output models del with mny industries. However the sic principle cn e illustrted with the id of smll scle (n) emple: / 8 / / / / 6 / 6 / / / Y 7 55 Given nd Y we cn find the output of ech of the three industries s follows: X (I-) - Y In order to find the inverse of we must first find I-: I / 8 / / / / 6 / 6 / / / 7 / 8 / / / 5 / 6 / 6 / / / nd then find the determinnt of the resultnt mtri: Epnding y column : Pge of 5

42 Teching nd Lerning Guide : Mtrices 7 / 8 5 / 6 / 6 / / ( / ) / / 6 / / ( / ) / 5 / 6 / / ( 5 ) ( ) ( 5 ) ( 7 ) ( 7 ) ( 7 ) 9 / 96 7 / 8 7 / 96 7 / 96 7 / The finding the nine cofctors: (5 / / ) 7 / ( / / ) (/ ( / 8 /6) 7 /6 (/ /6) ( 7 / / 8) (/ 5 / ) 5 / ) ( 7 / 8 /) (5 / 8 / 6) 7 / 7 / 9 / / 7 / / 8 7 / 8 9 /6 Putting these in-order forms the djugte mtri: Then tking the trnspose of the djugte mtri to form the djoint mtri: The inverse is therefore: Pge of 5

43 Teching nd Lerning Guide : Mtrices ( I ) / / 9 7 / 9 Multiplying this y the column vector of finl demnd we find pproimtely: 86 / 7 7 / / 59 / 9 7 / / / Which gives directly the outputs given (or required) from ech industry s eing 697, 5 nd 6577 respectively. Note tht we cn lso clculte the vector X-Y which gives directly tht output of ech industry tht goes to other industries rther thn s finl demnd. Worked emple: Etension Mteril Finlly, from the eqution: X (I-) - Y We cn find the mrginl effect of hving to produce one etr unit of finl demnd: X (I-) - Y Where X nd Y re the respective smll increses. Hence, if in the emple ove we needed to produce one etr unit for industry the Y vector would e: nd therefore: Y Pge of 5

44 Teching nd Lerning Guide : Mtrices X ( I ) Y / 59 / 9 7 / 9 86 / 7 86 / 7 7 / 7 / Links with the online question nk Questions focused on mtrices cn e found t Discussion Questions Students could e sked to find rel world economic stories from qulity news sources e.g. The Economist to show how input-output nlysis could e pplied. For emple, wht knockon might the demise of the Rover cr compny hve on other industries nd the UK economy? 5. ctivities Tsk One Lerning Ojectives LO: Students lern how to pply their knowledge of mtrices to input-output nlysis LO: Students lern how to drw inferences from nswers derived using mtri lger Tsk One sk students to review the worked emple ove (See.). Working in pirs, students should crete Powerpoint presenttion which summrises: - wht the worked emple ws trying to solve - the key steps to solving the input-output prolem; nd - ny prolems nd difficulties they encountered when working through the worked emple. Tsk Two Working in pirs. crete your own vlues of nd Y nd ssume n. Pge of 5

45 Teching nd Lerning Guide : Mtrices 6. Top Tips Students will wnt to prctise questions hving first ensured they hve mstered ech of the steps (See ove). Lecturers will proly wnt to crete opportunities for students to Ecel to pply their knowledge nd understnding. Higher ility students could e sked to develop their own prolem sets nd nswers. 7. Conclusion This is very much summtive or plenry topic. Crete chnces for students to work through prolem sets nd idelly offer one-to-one support s they design nd crete their own independent input-output prolem set (See 5. ove). uthored nd Produced y the METL Project Consortium 7 Pge 5 of 5

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered:

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered: Appendi D: Completing the Squre nd the Qudrtic Formul Fctoring qudrtic epressions such s: + 6 + 8 ws one of the topics introduced in Appendi C. Fctoring qudrtic epressions is useful skill tht cn help you

More information

P.3 Polynomials and Factoring. P.3 an 1. Polynomial STUDY TIP. Example 1 Writing Polynomials in Standard Form. What you should learn

P.3 Polynomials and Factoring. P.3 an 1. Polynomial STUDY TIP. Example 1 Writing Polynomials in Standard Form. What you should learn 33337_0P03.qp 2/27/06 24 9:3 AM Chpter P Pge 24 Prerequisites P.3 Polynomils nd Fctoring Wht you should lern Polynomils An lgeric epression is collection of vriles nd rel numers. The most common type of

More information

Operations with Polynomials

Operations with Polynomials 38 Chpter P Prerequisites P.4 Opertions with Polynomils Wht you should lern: Write polynomils in stndrd form nd identify the leding coefficients nd degrees of polynomils Add nd subtrct polynomils Multiply

More information

Reasoning to Solve Equations and Inequalities

Reasoning to Solve Equations and Inequalities Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing

More information

Section 5-4 Trigonometric Functions

Section 5-4 Trigonometric Functions 5- Trigonometric Functions Section 5- Trigonometric Functions Definition of the Trigonometric Functions Clcultor Evlution of Trigonometric Functions Definition of the Trigonometric Functions Alternte Form

More information

Multiplication and Division - Left to Right. Addition and Subtraction - Left to Right.

Multiplication and Division - Left to Right. Addition and Subtraction - Left to Right. Order of Opertions r of Opertions Alger P lese Prenthesis - Do ll grouped opertions first. E cuse Eponents - Second M D er Multipliction nd Division - Left to Right. A unt S hniqu Addition nd Sutrction

More information

Factoring Polynomials

Factoring Polynomials Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles

More information

Or more simply put, when adding or subtracting quantities, their uncertainties add.

Or more simply put, when adding or subtracting quantities, their uncertainties add. Propgtion of Uncertint through Mthemticl Opertions Since the untit of interest in n eperiment is rrel otined mesuring tht untit directl, we must understnd how error propgtes when mthemticl opertions re

More information

A.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324

A.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324 A P P E N D I X A Vectors CONTENTS A.1 Scling vector................................................ 321 A.2 Unit or Direction vectors...................................... 321 A.3 Vector ddition.................................................

More information

Algebra Review. How well do you remember your algebra?

Algebra Review. How well do you remember your algebra? Algebr Review How well do you remember your lgebr? 1 The Order of Opertions Wht do we men when we write + 4? If we multiply we get 6 nd dding 4 gives 10. But, if we dd + 4 = 7 first, then multiply by then

More information

CS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001

CS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001 CS99S Lortory 2 Preprtion Copyright W. J. Dlly 2 Octoer, 2 Ojectives:. Understnd the principle of sttic CMOS gte circuits 2. Build simple logic gtes from MOS trnsistors 3. Evlute these gtes to oserve logic

More information

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions.

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions. Lerning Objectives Loci nd Conics Lesson 3: The Ellipse Level: Preclculus Time required: 120 minutes In this lesson, students will generlize their knowledge of the circle to the ellipse. The prmetric nd

More information

2 DIODE CLIPPING and CLAMPING CIRCUITS

2 DIODE CLIPPING and CLAMPING CIRCUITS 2 DIODE CLIPPING nd CLAMPING CIRCUITS 2.1 Ojectives Understnding the operting principle of diode clipping circuit Understnding the operting principle of clmping circuit Understnding the wveform chnge of

More information

9 CONTINUOUS DISTRIBUTIONS

9 CONTINUOUS DISTRIBUTIONS 9 CONTINUOUS DISTIBUTIONS A rndom vrible whose vlue my fll nywhere in rnge of vlues is continuous rndom vrible nd will be ssocited with some continuous distribution. Continuous distributions re to discrete

More information

EQUATIONS OF LINES AND PLANES

EQUATIONS OF LINES AND PLANES EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint

More information

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( ) Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +

More information

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY MAT 0630 INTERNET RESOURCES, REVIEW OF CONCEPTS AND COMMON MISTAKES PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY Contents 1. ACT Compss Prctice Tests 1 2. Common Mistkes 2 3. Distributive

More information

Bayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom

Bayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom Byesin Updting with Continuous Priors Clss 3, 8.05, Spring 04 Jeremy Orloff nd Jonthn Bloom Lerning Gols. Understnd prmeterized fmily of distriutions s representing continuous rnge of hypotheses for the

More information

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES DAVID WEBB CONTENTS Liner trnsformtions 2 The representing mtrix of liner trnsformtion 3 3 An ppliction: reflections in the plne 6 4 The lgebr of

More information

Integration. 148 Chapter 7 Integration

Integration. 148 Chapter 7 Integration 48 Chpter 7 Integrtion 7 Integrtion t ech, by supposing tht during ech tenth of second the object is going t constnt speed Since the object initilly hs speed, we gin suppose it mintins this speed, but

More information

Experiment 6: Friction

Experiment 6: Friction Experiment 6: Friction In previous lbs we studied Newton s lws in n idel setting, tht is, one where friction nd ir resistnce were ignored. However, from our everydy experience with motion, we know tht

More information

Small Businesses Decisions to Offer Health Insurance to Employees

Small Businesses Decisions to Offer Health Insurance to Employees Smll Businesses Decisions to Offer Helth Insurnce to Employees Ctherine McLughlin nd Adm Swinurn, June 2014 Employer-sponsored helth insurnce (ESI) is the dominnt source of coverge for nonelderly dults

More information

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers.

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers. 2 Rtionl Numbers Integers such s 5 were importnt when solving the eqution x+5 = 0. In similr wy, frctions re importnt for solving equtions like 2x = 1. Wht bout equtions like 2x + 1 = 0? Equtions of this

More information

Graphs on Logarithmic and Semilogarithmic Paper

Graphs on Logarithmic and Semilogarithmic Paper 0CH_PHClter_TMSETE_ 3//00 :3 PM Pge Grphs on Logrithmic nd Semilogrithmic Pper OBJECTIVES When ou hve completed this chpter, ou should be ble to: Mke grphs on logrithmic nd semilogrithmic pper. Grph empiricl

More information

Pentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful

Pentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful Pentominoes Bruce Bguley Cscde Mth Systems, LLC Astrct. Pentominoes nd their reltives the polyominoes, polycues, nd polyhypercues will e used to explore nd pply vrious importnt mthemticl concepts. In this

More information

9.3. The Scalar Product. Introduction. Prerequisites. Learning Outcomes

9.3. The Scalar Product. Introduction. Prerequisites. Learning Outcomes The Sclr Product 9.3 Introduction There re two kinds of multipliction involving vectors. The first is known s the sclr product or dot product. This is so-clled becuse when the sclr product of two vectors

More information

Math 135 Circles and Completing the Square Examples

Math 135 Circles and Completing the Square Examples Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for

More information

Regular Sets and Expressions

Regular Sets and Expressions Regulr Sets nd Expressions Finite utomt re importnt in science, mthemtics, nd engineering. Engineers like them ecuse they re super models for circuits (And, since the dvent of VLSI systems sometimes finite

More information

Econ 4721 Money and Banking Problem Set 2 Answer Key

Econ 4721 Money and Banking Problem Set 2 Answer Key Econ 472 Money nd Bnking Problem Set 2 Answer Key Problem (35 points) Consider n overlpping genertions model in which consumers live for two periods. The number of people born in ech genertion grows in

More information

MA 15800 Lesson 16 Notes Summer 2016 Properties of Logarithms. Remember: A logarithm is an exponent! It behaves like an exponent!

MA 15800 Lesson 16 Notes Summer 2016 Properties of Logarithms. Remember: A logarithm is an exponent! It behaves like an exponent! MA 5800 Lesson 6 otes Summer 06 Rememer: A logrithm is n eponent! It ehves like n eponent! In the lst lesson, we discussed four properties of logrithms. ) log 0 ) log ) log log 4) This lesson covers more

More information

Homework 3 Solutions

Homework 3 Solutions CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.

More information

1. Definition, Basic concepts, Types 2. Addition and Subtraction of Matrices 3. Scalar Multiplication 4. Assignment and answer key 5.

1. Definition, Basic concepts, Types 2. Addition and Subtraction of Matrices 3. Scalar Multiplication 4. Assignment and answer key 5. . Definition, Bsi onepts, Types. Addition nd Sutrtion of Mtries. Slr Multiplition. Assignment nd nswer key. Mtrix Multiplition. Assignment nd nswer key. Determinnt x x (digonl, minors, properties) summry

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

Unit 6: Exponents and Radicals

Unit 6: Exponents and Radicals Eponents nd Rdicls -: The Rel Numer Sstem Unit : Eponents nd Rdicls Pure Mth 0 Notes Nturl Numers (N): - counting numers. {,,,,, } Whole Numers (W): - counting numers with 0. {0,,,,,, } Integers (I): -

More information

Module Summary Sheets. C3, Methods for Advanced Mathematics (Version B reference to new book) Topic 2: Natural Logarithms and Exponentials

Module Summary Sheets. C3, Methods for Advanced Mathematics (Version B reference to new book) Topic 2: Natural Logarithms and Exponentials MEI Mthemtics in Ection nd Instry Topic : Proof MEI Structured Mthemtics Mole Summry Sheets C, Methods for Anced Mthemtics (Version B reference to new book) Topic : Nturl Logrithms nd Eponentils Topic

More information

The remaining two sides of the right triangle are called the legs of the right triangle.

The remaining two sides of the right triangle are called the legs of the right triangle. 10 MODULE 6. RADICAL EXPRESSIONS 6 Pythgoren Theorem The Pythgoren Theorem An ngle tht mesures 90 degrees is lled right ngle. If one of the ngles of tringle is right ngle, then the tringle is lled right

More information

6.2 Volumes of Revolution: The Disk Method

6.2 Volumes of Revolution: The Disk Method mth ppliction: volumes of revolution, prt ii Volumes of Revolution: The Disk Method One of the simplest pplictions of integrtion (Theorem ) nd the ccumultion process is to determine so-clled volumes of

More information

Rotational Equilibrium: A Question of Balance

Rotational Equilibrium: A Question of Balance Prt of the IEEE Techer In-Service Progrm - Lesson Focus Demonstrte the concept of rottionl equilirium. Lesson Synopsis The Rottionl Equilirium ctivity encourges students to explore the sic concepts of

More information

Babylonian Method of Computing the Square Root: Justifications Based on Fuzzy Techniques and on Computational Complexity

Babylonian Method of Computing the Square Root: Justifications Based on Fuzzy Techniques and on Computational Complexity Bbylonin Method of Computing the Squre Root: Justifictions Bsed on Fuzzy Techniques nd on Computtionl Complexity Olg Koshelev Deprtment of Mthemtics Eduction University of Texs t El Pso 500 W. University

More information

SPECIAL PRODUCTS AND FACTORIZATION

SPECIAL PRODUCTS AND FACTORIZATION MODULE - Specil Products nd Fctoriztion 4 SPECIAL PRODUCTS AND FACTORIZATION In n erlier lesson you hve lernt multipliction of lgebric epressions, prticulrly polynomils. In the study of lgebr, we come

More information

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100

Mathematics. Vectors. hsn.uk.net. Higher. Contents. Vectors 128 HSN23100 hsn.uk.net Higher Mthemtics UNIT 3 OUTCOME 1 Vectors Contents Vectors 18 1 Vectors nd Sclrs 18 Components 18 3 Mgnitude 130 4 Equl Vectors 131 5 Addition nd Subtrction of Vectors 13 6 Multipliction by

More information

NQF Level: 2 US No: 7480

NQF Level: 2 US No: 7480 NQF Level: 2 US No: 7480 Assessment Guide Primry Agriculture Rtionl nd irrtionl numers nd numer systems Assessor:.......................................... Workplce / Compny:.................................

More information

Vectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a.

Vectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a. Vectors mesurement which onl descries the mgnitude (i.e. size) of the oject is clled sclr quntit, e.g. Glsgow is 11 miles from irdrie. vector is quntit with mgnitude nd direction, e.g. Glsgow is 11 miles

More information

Vectors 2. 1. Recap of vectors

Vectors 2. 1. Recap of vectors Vectors 2. Recp of vectors Vectors re directed line segments - they cn be represented in component form or by direction nd mgnitude. We cn use trigonometry nd Pythgors theorem to switch between the forms

More information

Basic Analysis of Autarky and Free Trade Models

Basic Analysis of Autarky and Free Trade Models Bsic Anlysis of Autrky nd Free Trde Models AUTARKY Autrky condition in prticulr commodity mrket refers to sitution in which country does not engge in ny trde in tht commodity with other countries. Consequently

More information

1.2 The Integers and Rational Numbers

1.2 The Integers and Rational Numbers .2. THE INTEGERS AND RATIONAL NUMBERS.2 The Integers n Rtionl Numers The elements of the set of integers: consist of three types of numers: Z {..., 5, 4, 3, 2,, 0,, 2, 3, 4, 5,...} I. The (positive) nturl

More information

0.1 Basic Set Theory and Interval Notation

0.1 Basic Set Theory and Interval Notation 0.1 Bsic Set Theory nd Intervl Nottion 3 0.1 Bsic Set Theory nd Intervl Nottion 0.1.1 Some Bsic Set Theory Notions Like ll good Mth ooks, we egin with definition. Definition 0.1. A set is well-defined

More information

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1.

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1. Mth 4, Homework Assignment. Prove tht two nonverticl lines re perpendiculr if nd only if the product of their slopes is. Proof. Let l nd l e nonverticl lines in R of slopes m nd m, respectively. Suppose

More information

1. Find the zeros Find roots. Set function = 0, factor or use quadratic equation if quadratic, graph to find zeros on calculator

1. Find the zeros Find roots. Set function = 0, factor or use quadratic equation if quadratic, graph to find zeros on calculator AP Clculus Finl Review Sheet When you see the words. This is wht you think of doing. Find the zeros Find roots. Set function =, fctor or use qudrtic eqution if qudrtic, grph to find zeros on clcultor.

More information

Learning Outcomes. Computer Systems - Architecture Lecture 4 - Boolean Logic. What is Logic? Boolean Logic 10/28/2010

Learning Outcomes. Computer Systems - Architecture Lecture 4 - Boolean Logic. What is Logic? Boolean Logic 10/28/2010 /28/2 Lerning Outcomes At the end of this lecture you should: Computer Systems - Architecture Lecture 4 - Boolen Logic Eddie Edwrds eedwrds@doc.ic.c.uk http://www.doc.ic.c.uk/~eedwrds/compsys (Hevily sed

More information

5 a LAN 6 a gateway 7 a modem

5 a LAN 6 a gateway 7 a modem STARTER With the help of this digrm, try to descrie the function of these components of typicl network system: 1 file server 2 ridge 3 router 4 ckone 5 LAN 6 gtewy 7 modem Another Novell LAN Router Internet

More information

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3.

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3. The nlysis of vrince (ANOVA) Although the t-test is one of the most commonly used sttisticl hypothesis tests, it hs limittions. The mjor limittion is tht the t-test cn be used to compre the mens of only

More information

Binary Representation of Numbers Autar Kaw

Binary Representation of Numbers Autar Kaw Binry Representtion of Numbers Autr Kw After reding this chpter, you should be ble to: 1. convert bse- rel number to its binry representtion,. convert binry number to n equivlent bse- number. In everydy

More information

Exponential and Logarithmic Functions

Exponential and Logarithmic Functions Nme Chpter Eponentil nd Logrithmic Functions Section. Eponentil Functions nd Their Grphs Objective: In this lesson ou lerned how to recognize, evlute, nd grph eponentil functions. Importnt Vocbulr Define

More information

Section 7-4 Translation of Axes

Section 7-4 Translation of Axes 62 7 ADDITIONAL TOPICS IN ANALYTIC GEOMETRY Section 7-4 Trnsltion of Aes Trnsltion of Aes Stndrd Equtions of Trnslted Conics Grphing Equtions of the Form A 2 C 2 D E F 0 Finding Equtions of Conics In the

More information

Answer, Key Homework 10 David McIntyre 1

Answer, Key Homework 10 David McIntyre 1 Answer, Key Homework 10 Dvid McIntyre 1 This print-out should hve 22 questions, check tht it is complete. Multiple-choice questions my continue on the next column or pge: find ll choices efore mking your

More information

10.6 Applications of Quadratic Equations

10.6 Applications of Quadratic Equations 10.6 Applictions of Qudrtic Equtions In this section we wnt to look t the pplictions tht qudrtic equtions nd functions hve in the rel world. There re severl stndrd types: problems where the formul is given,

More information

5.6 POSITIVE INTEGRAL EXPONENTS

5.6 POSITIVE INTEGRAL EXPONENTS 54 (5 ) Chpter 5 Polynoils nd Eponents 5.6 POSITIVE INTEGRAL EXPONENTS In this section The product rule for positive integrl eponents ws presented in Section 5., nd the quotient rule ws presented in Section

More information

Vector differentiation. Chapters 6, 7

Vector differentiation. Chapters 6, 7 Chpter 2 Vectors Courtesy NASA/JPL-Cltech Summry (see exmples in Hw 1, 2, 3) Circ 1900 A.D., J. Willird Gis invented useful comintion of mgnitude nd direction clled vectors nd their higher-dimensionl counterprts

More information

and thus, they are similar. If k = 3 then the Jordan form of both matrices is

and thus, they are similar. If k = 3 then the Jordan form of both matrices is Homework ssignment 11 Section 7. pp. 249-25 Exercise 1. Let N 1 nd N 2 be nilpotent mtrices over the field F. Prove tht N 1 nd N 2 re similr if nd only if they hve the sme miniml polynomil. Solution: If

More information

Helicopter Theme and Variations

Helicopter Theme and Variations Helicopter Theme nd Vritions Or, Some Experimentl Designs Employing Pper Helicopters Some possible explntory vribles re: Who drops the helicopter The length of the rotor bldes The height from which the

More information

Physics 43 Homework Set 9 Chapter 40 Key

Physics 43 Homework Set 9 Chapter 40 Key Physics 43 Homework Set 9 Chpter 4 Key. The wve function for n electron tht is confined to x nm is. Find the normliztion constnt. b. Wht is the probbility of finding the electron in. nm-wide region t x

More information

Thinking out of the Box... Problem It s a richer problem than we ever imagined

Thinking out of the Box... Problem It s a richer problem than we ever imagined From the Mthemtics Techer, Vol. 95, No. 8, pges 568-574 Wlter Dodge (not pictured) nd Steve Viktor Thinking out of the Bo... Problem It s richer problem thn we ever imgined The bo problem hs been stndrd

More information

Pure C4. Revision Notes

Pure C4. Revision Notes Pure C4 Revision Notes Mrch 0 Contents Core 4 Alger Prtil frctions Coordinte Geometry 5 Prmetric equtions 5 Conversion from prmetric to Crtesin form 6 Are under curve given prmetriclly 7 Sequences nd

More information

Chapter. Contents: A Constructing decimal numbers

Chapter. Contents: A Constructing decimal numbers Chpter 9 Deimls Contents: A Construting deiml numers B Representing deiml numers C Deiml urreny D Using numer line E Ordering deimls F Rounding deiml numers G Converting deimls to frtions H Converting

More information

AntiSpyware Enterprise Module 8.5

AntiSpyware Enterprise Module 8.5 AntiSpywre Enterprise Module 8.5 Product Guide Aout the AntiSpywre Enterprise Module The McAfee AntiSpywre Enterprise Module 8.5 is n dd-on to the VirusScn Enterprise 8.5i product tht extends its ility

More information

Numeracy across the Curriculum in Key Stages 3 and 4. Helpful advice and suggested resources from the Leicestershire Secondary Mathematics Team

Numeracy across the Curriculum in Key Stages 3 and 4. Helpful advice and suggested resources from the Leicestershire Secondary Mathematics Team Numercy cross the Curriculum in Key Stges 3 nd 4 Helpful dvice nd suggested resources from the Leicestershire Secondry Mthemtics Tem 1 Contents pge The development of whole school policy 3 A definition

More information

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Friday 16 th May 2008. Time: 14:00 16:00

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Friday 16 th May 2008. Time: 14:00 16:00 COMP20212 Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE Digitl Design Techniques Dte: Fridy 16 th My 2008 Time: 14:00 16:00 Plese nswer ny THREE Questions from the FOUR questions provided

More information

Review guide for the final exam in Math 233

Review guide for the final exam in Math 233 Review guide for the finl exm in Mth 33 1 Bsic mteril. This review includes the reminder of the mteril for mth 33. The finl exm will be cumultive exm with mny of the problems coming from the mteril covered

More information

Unit 29: Inference for Two-Way Tables

Unit 29: Inference for Two-Way Tables Unit 29: Inference for Two-Wy Tbles Prerequisites Unit 13, Two-Wy Tbles is prerequisite for this unit. In ddition, students need some bckground in significnce tests, which ws introduced in Unit 25. Additionl

More information

4.11 Inner Product Spaces

4.11 Inner Product Spaces 314 CHAPTER 4 Vector Spces 9. A mtrix of the form 0 0 b c 0 d 0 0 e 0 f g 0 h 0 cnnot be invertible. 10. A mtrix of the form bc d e f ghi such tht e bd = 0 cnnot be invertible. 4.11 Inner Product Spces

More information

Firm Objectives. The Theory of the Firm II. Cost Minimization Mathematical Approach. First order conditions. Cost Minimization Graphical Approach

Firm Objectives. The Theory of the Firm II. Cost Minimization Mathematical Approach. First order conditions. Cost Minimization Graphical Approach Pro. Jy Bhttchry Spring 200 The Theory o the Firm II st lecture we covered: production unctions Tody: Cost minimiztion Firm s supply under cost minimiztion Short vs. long run cost curves Firm Ojectives

More information

FUNCTIONS AND EQUATIONS. xεs. The simplest way to represent a set is by listing its members. We use the notation

FUNCTIONS AND EQUATIONS. xεs. The simplest way to represent a set is by listing its members. We use the notation FUNCTIONS AND EQUATIONS. SETS AND SUBSETS.. Definition of set. A set is ny collection of objects which re clled its elements. If x is n element of the set S, we sy tht x belongs to S nd write If y does

More information

4.5 Signal Flow Graphs

4.5 Signal Flow Graphs 3/9/009 4_5 ignl Flow Grphs.doc / 4.5 ignl Flow Grphs Reding Assignment: pp. 89-97 Q: Using individul device scttering prmeters to nlze comple microwve network results in lot of mess mth! Isn t there n

More information

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one.

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one. 5.2. LINE INTEGRALS 265 5.2 Line Integrls 5.2.1 Introduction Let us quickly review the kind of integrls we hve studied so fr before we introduce new one. 1. Definite integrl. Given continuous rel-vlued

More information

SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1470 - COLLEGE ALGEBRA (4 SEMESTER HOURS)

SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 1470 - COLLEGE ALGEBRA (4 SEMESTER HOURS) SINCLAIR COMMUNITY COLLEGE DAYTON, OHIO DEPARTMENT SYLLABUS FOR COURSE IN MAT 470 - COLLEGE ALGEBRA (4 SEMESTER HOURS). COURSE DESCRIPTION: Polynomil, rdicl, rtionl, exponentil, nd logrithmic functions

More information

Morgan Stanley Ad Hoc Reporting Guide

Morgan Stanley Ad Hoc Reporting Guide spphire user guide Ferury 2015 Morgn Stnley Ad Hoc Reporting Guide An Overview For Spphire Users 1 Introduction The Ad Hoc Reporting tool is ville for your reporting needs outside of the Spphire stndrd

More information

MATH 150 HOMEWORK 4 SOLUTIONS

MATH 150 HOMEWORK 4 SOLUTIONS MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive

More information

Novel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm

Novel Methods of Generating Self-Invertible Matrix for Hill Cipher Algorithm Bibhudendr chry, Girij Snkr Rth, Srt Kumr Ptr, nd Sroj Kumr Pnigrhy Novel Methods of Generting Self-Invertible Mtrix for Hill Cipher lgorithm Bibhudendr chry Deprtment of Electronics & Communiction Engineering

More information

Distributions. (corresponding to the cumulative distribution function for the discrete case).

Distributions. (corresponding to the cumulative distribution function for the discrete case). Distributions Recll tht n integrble function f : R [,] such tht R f()d = is clled probbility density function (pdf). The distribution function for the pdf is given by F() = (corresponding to the cumultive

More information

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2 7 CHAPTER THREE. Cross Product Given two vectors = (,, nd = (,, in R, the cross product of nd written! is defined to e: " = (!,!,! Note! clled cross is VECTOR (unlike which is sclr. Exmple (,, " (4,5,6

More information

** Dpt. Chemical Engineering, Kasetsart University, Bangkok 10900, Thailand

** Dpt. Chemical Engineering, Kasetsart University, Bangkok 10900, Thailand Modelling nd Simultion of hemicl Processes in Multi Pulse TP Experiment P. Phnwdee* S.O. Shekhtmn +. Jrungmnorom** J.T. Gleves ++ * Dpt. hemicl Engineering, Ksetsrt University, Bngkok 10900, Thilnd + Dpt.hemicl

More information

Simulation of operation modes of isochronous cyclotron by a new interative method

Simulation of operation modes of isochronous cyclotron by a new interative method NUKLEONIKA 27;52(1):29 34 ORIGINAL PAPER Simultion of opertion modes of isochronous cyclotron y new intertive method Ryszrd Trszkiewicz, Mrek Tlch, Jcek Sulikowski, Henryk Doruch, Tdeusz Norys, Artur Srok,

More information

FAULT TREES AND RELIABILITY BLOCK DIAGRAMS. Harry G. Kwatny. Department of Mechanical Engineering & Mechanics Drexel University

FAULT TREES AND RELIABILITY BLOCK DIAGRAMS. Harry G. Kwatny. Department of Mechanical Engineering & Mechanics Drexel University SYSTEM FAULT AND Hrry G. Kwtny Deprtment of Mechnicl Engineering & Mechnics Drexel University OUTLINE SYSTEM RBD Definition RBDs nd Fult Trees System Structure Structure Functions Pths nd Cutsets Reliility

More information

Object Semantics. 6.170 Lecture 2

Object Semantics. 6.170 Lecture 2 Object Semntics 6.170 Lecture 2 The objectives of this lecture re to: to help you become fmilir with the bsic runtime mechnism common to ll object-oriented lnguges (but with prticulr focus on Jv): vribles,

More information

Rotating DC Motors Part II

Rotating DC Motors Part II Rotting Motors rt II II.1 Motor Equivlent Circuit The next step in our consiertion of motors is to evelop n equivlent circuit which cn be use to better unerstn motor opertion. The rmtures in rel motors

More information

DlNBVRGH + Sickness Absence Monitoring Report. Executive of the Council. Purpose of report

DlNBVRGH + Sickness Absence Monitoring Report. Executive of the Council. Purpose of report DlNBVRGH + + THE CITY OF EDINBURGH COUNCIL Sickness Absence Monitoring Report Executive of the Council 8fh My 4 I.I...3 Purpose of report This report quntifies the mount of working time lost s result of

More information

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply?

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply? Assignment 3: Bohr s model nd lser fundmentls 1. In the Bohr model, compre the mgnitudes of the electron s kinetic nd potentil energies in orit. Wht does this imply? When n electron moves in n orit, the

More information

Quick Reference Guide: One-time Account Update

Quick Reference Guide: One-time Account Update Quick Reference Guide: One-time Account Updte How to complete The Quick Reference Guide shows wht existing SingPss users need to do when logging in to the enhnced SingPss service for the first time. 1)

More information

CHAPTER 11 Numerical Differentiation and Integration

CHAPTER 11 Numerical Differentiation and Integration CHAPTER 11 Numericl Differentition nd Integrtion Differentition nd integrtion re bsic mthemticl opertions with wide rnge of pplictions in mny res of science. It is therefore importnt to hve good methods

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

According to Webster s, the

According to Webster s, the dt modeling Universl Dt Models nd P tterns By Len Silversn According Webster s, term universl cn be defined s generlly pplicble s well s pplying whole. There re some very common ptterns tht cn be generlly

More information

Lectures 8 and 9 1 Rectangular waveguides

Lectures 8 and 9 1 Rectangular waveguides 1 Lectures 8 nd 9 1 Rectngulr wveguides y b x z Consider rectngulr wveguide with 0 < x b. There re two types of wves in hollow wveguide with only one conductor; Trnsverse electric wves

More information

Welch Allyn CardioPerfect Workstation Installation Guide

Welch Allyn CardioPerfect Workstation Installation Guide Welch Allyn CrdioPerfect Worksttion Instlltion Guide INSTALLING CARDIOPERFECT WORKSTATION SOFTWARE & ACCESSORIES ON A SINGLE PC For softwre version 1.6.5 or lter For network instlltion, plese refer to

More information

Solving BAMO Problems

Solving BAMO Problems Solving BAMO Problems Tom Dvis tomrdvis@erthlink.net http://www.geometer.org/mthcircles Februry 20, 2000 Abstrct Strtegies for solving problems in the BAMO contest (the By Are Mthemticl Olympid). Only

More information

One Minute To Learn Programming: Finite Automata

One Minute To Learn Programming: Finite Automata Gret Theoreticl Ides In Computer Science Steven Rudich CS 15-251 Spring 2005 Lecture 9 Fe 8 2005 Crnegie Mellon University One Minute To Lern Progrmming: Finite Automt Let me tech you progrmming lnguge

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Lecture 3 Gaussian Probability Distribution

Lecture 3 Gaussian Probability Distribution Lecture 3 Gussin Probbility Distribution Introduction l Gussin probbility distribution is perhps the most used distribution in ll of science. u lso clled bell shped curve or norml distribution l Unlike

More information

JaERM Software-as-a-Solution Package

JaERM Software-as-a-Solution Package JERM Softwre-s--Solution Pckge Enterprise Risk Mngement ( ERM ) Public listed compnies nd orgnistions providing finncil services re required by Monetry Authority of Singpore ( MAS ) nd/or Singpore Stock

More information