A REA AND INTEGRALS. 1 Sigma Notation 2. 2 Area 7. 3 The Definite Integral 16

Size: px
Start display at page:

Download "A REA AND INTEGRALS. 1 Sigma Notation 2. 2 Area 7. 3 The Definite Integral 16"

Transcription

1 ALTERNATIVE TREATMENT: A REA AND INTEGRALS Sigm Nottio Are 7 The Defiite Itegrl Reprited with permissio from Clculus: Erl Trscedetls, Third Editio Jmes Stewrt 995 Brooks/Cole Pulishig Comp, A divisio of Itertiol Thomso Pulishig Co.

2 SECTION SIGMA NOTATION SECTION Sigm Nottio I fidig res d evlutig itegrls we ofte ecouter sums with m terms. A coveiet w of writig such sums uses the Greek letter (cpitl sigm, correspodig to our letter S) d is clled sigm ottio. This tells us to ed with i=. This tells us to dd. This tells us to strt with i=m. µ i im Defiitio If m, m,..., re rel umers d m d re itegers such tht m, the i m m m im With fuctio ottio, Defiitio c e writte s f i f m f m f m f f im im Thus, the smol idictes summtio i which the letter i (clled the ide of summtio) tkes o the vlues m, m,...,. Other letters c lso e used s the ide of summtio. EXAMPLE () () (c) (d) (e) (f) 4 i 4 i 4 5 i 5 j 4 5 j k k i i EXAMPLE Write the sum i sigm ottio. SOLUTION There is o uique w of writig sum i sigm ottio. We could write i i or or j j k k The followig theorem gives three simple rules for workig with sigm ottio.

3 SECTION SIGMA NOTATION () (c) Theorem c i c i im im If c is costt (tht is, it does ot deped o i), the i i i i im im im () i i i i im im im Proof To see wh these rules re true, ll we hve to do is write oth sides i epded form. Rule () is just the distriutive propert of rel umers: c m c m c c m m Rule () follows from the ssocitive d commuttive properties: m m m m m m m m Rule (c) is proved similrl. EXAMPLE Fid SOLUTION. terms PRINCIPLE OF MATHEMATICAL INDUCTION Let S e sttemet ivolvig the positive iteger. Suppose tht. S is true.. If S k is true, the S k is true. The S is true for ll positive itegers. EXAMPLE 4 Prove the formul for the sum of the first positive itegers: i SOLUTION This formul c e proved mthemticl iductio (see pge 59) or the followig method used the Germ mthemtici Krl Friedrich Guss ( ) whe he ws te ers old. Write the sum S twice, oce i the usul order d oce i reverse order: S S Addig ll colums verticll, we get S O the right side there re terms, ech of which is, so S or S EXAMPLE 5 Prove the formul for the sum of the squres of the first positive itegers: i

4 4 SECTION SIGMA NOTATION SOLUTION Let S e the desired sum. We strt with the telescopig sum (or collpsig sum): Most terms ccel i pirs. i i 4 O the other hd, usig Theorem d Emples d 4, we hve i i i i i i S S 5 Thus we hve S 5 Solvig this equtio for S, we oti S or S See pges 59 d for more thorough discussio of mthemticl iductio. SOLUTION Let e the give formul. S S. is true ecuse S k. Assume tht is true; tht is, The k kk k k k k So S k is true. k k k 7k B the Priciple of Mthemticl Iductio, is true for ll. kk k k k k k k k S k kk k We list the results of Emples, 4, d 5 together with similr result for cues d fourth powers (see Eercises 7 4) s Theorem. These formuls re eeded for fidig res i the et sectio.

5 SECTION SIGMA NOTATION 5 () Theorem Let c e costt d positive iteger. The () c c (c) (e) i i (d) (f) i i 4 The tpe of clcultio i Emple 7 rises i the et sectio whe we compute res. EXAMPLE Evlute i4i. SOLUTION Usig Theorems d, we hve EXAMPLE 7 Fid lim. SOLUTION i4i 4i i 4 i i l i lim i l l 4 l l l l i i 4

6 SECTION SIGMA NOTATION Eercises Write the sum i epded form.. si k. k j. Write the sum i sigm ottio.. 4. s s4 s5 s s i i4 k i j Fid the vlue of the sum. 8 i4. i. j j i 7. i i i.. i i 4.. i i i i. 7. Prove formul () of Theorem. i i4 8 k k5 j j 4 i f i i ii i 8 cos k k 4 i i 5i i ii i k k k 8. Prove formul (e) of Theorem usig mthemticl iductio. 9. Prove formul (e) of Theorem usig method similr to tht of Emple 5, Solutio [strt with i 4 i Prove formul (e) of Theorem usig the followig method pulished Au Bekr Mohmmed i Alhusi Alkrchi i out A.D.. The figure shows squre ABCD i which sides AB d AD hve ee divided ito segmets of legths,,,...,. Thus the side of the squre hs legth so the re is. But the re is lso the sum of the res of the gomos G, G,..., G show i the figure. Show tht the re of G is i i d coclude tht formul (e) is true. 4. Evlute ech telescopig sum. () (c) () (d) 4. Prove the geerlized trigle iequlit 4 4 Fid ech limit i 4 i 4 i 99 i i lim l lim l D 5 4 i i lim i l lim l i. G G A G B i 5 i G i i 5 i 5 i 47. Prove the formul for the sum of fiite geometric series with first term d commo rtio r : r r r r r r... G C

7 SECTION AREA Evlute. 49. Evlute i i. 5. Evlute m j i j 5. Fid the umer such tht i () Use the product formul for si cos (see 8 i Appedi D) to show tht si cos i si(i ) si(i ) () Use the idetit i prt () d telescopig sums to prove the formul cos i si( ) si si where is ot iteger multiple of cos i si cos si. Deduce tht 5. Use the method of Eercise 5 to prove the formul si i si si si where is ot iteger multiple of. SECTION Are We egi ttemptig to solve the re prolem: Fid the re of the regio S tht lies uder the curve f from to. This mes tht S, illustrted i Figure, is ouded the grph of cotiuous fuctio f [where f ], the verticl lies d, d the -is. =ƒ FIGURE S=s(, ), ƒd = S = I trig to solve the re prolem we hve to sk ourselves: Wht is the meig of the word re? This questio is es to swer for regios with stright sides. For rectgle, the re is defied s the product of the legth d the width. The re of trigle is hlf the se times the height. The re of polgo is foud dividig it ito trigles (s i Figure ) d ddig the res of the trigles. A A w h A A l FIGURE A=lw A= h A=A +A +A +A However, it is t so es to fid the re of regio with curved sides. We ll hve ituitive ide of wht the re of regio is. But prt of the re prolem is to mke this ituitive ide precise givig ect defiitio of re. Recll tht i defiig tget we first pproimted the slope of the tget lie slopes of sect lies d the we took the limit of these pproimtios. We pursue sim-

8 8 SECTION AREA ilr ide for res. We first pproimte the regio S polgos d the we tke the limit of the res of these polgos. The followig emple illustrtes the procedure. EXAMPLE Let s tr to fid the re uder the prol regio S illustrted i Figure ). from to (the prolic (, ) = FIGURE Oe method of pproimtig the desired re is to divide the itervl, ito suitervls of equl legth d cosider the rectgles whose ses re these suitervls d whose heights re the vlues of the fuctio t the right-hd edpoits of these suitervls. Figure 4 shows the pproimtio of the prolic regio four, eight, d rectgles (, ) (, ) (, ) FIGURE 4 4 () 4 8 () (c) Let S e the sum of the res of the rectgles i Figure 4(c). Ech rectgle hs width d the heights re the vlues of the fuctio f t the poits,,,..., ; tht is, the heights re,,,...,. Thus S i Usig the formul for the sum of the squres of the first itegers [Formul.(d)], we c write S For istce, the sum of the res of the four shded rectgles i Figure 4() is S

9 SECTION AREA 9 S d the sum of the res of the eight rectgles i FIgure 4() is The results of similr clcultios re show i the tle i the mrgi. It looks s if is ecomig closer to s icreses. I fct S S lim S l l l l From Figure 4 it ppers tht, s icreses, S ecomes etter d etter pproimtio to the re of the prolic segmet. Therefore we defie the re A to e the limit of the sums of the res of the pproimtig rectgles, tht is, A l S I pplig the ide of Emple to the more geerl regio S of Figure, we hve o eed to use rectgles of equl width. We strt sudividig the itervl, ito smller suitervls choosig prtitio poits,,,..., so tht The the suitervls re,,,,,,...,, This sudivisio is clled the prtitio of, d we deote it P. We use the ottio i for the legth of the ith suitervl, i. Thus i i This legth of the logest suitervl is deoted P d is clled the orm of P. Thus P m,,..., Figure 5 illustrtes oe possile prtitio of,. Î Î Î Î i Î FIGURE 5 =... i- i... - = B drwig the lies,,,...,, we use the prtitio P to divide the regio S ito strips S, S,..., S s i Figure. Net we pproimte these strips S i rectgles R i. To do this we choose umer * i i ech suitervl, i d costruct rectgle R i with se i d height f* i s i Figure 7.

10 SECTION AREA =ƒ Î i f( i *) S S S S i S R R R R i R... i- i... - i- i - FIGURE FIGURE 7 * * * i * * Ech poit * i c e where i its suitervl t the right edpoit (s i Emple ) or t the left edpoit or somewhere etwee the edpoits. The re of the ith rectgle R i is A i f * i i The rectgles R,..., R form polgol pproimtio to the regio S. Wht we thik of ituitivel s the re of S is pproimted the sum of the res of these rectgles, which is A i f * i i f * f * Figure 8 shows this pproimtio for prtitios with, 4, 8, d. * * () = () =4 (c) =8 (d) = FIGURE 8 Notice tht this pproimtio ppers to ecome etter d etter s the strips ecome thier d thier, tht is, s P l. Therefore we defie the re A of the regio S s the limitig vlue (if it eists) of the res of the pproimtig polgos, tht is, the limit of the sum () of the res of the pproimtig rectgles. I smols: A Pl f * i i The precedig discussio d the digrms i Figures 7 d 8 show tht the defiitio of re i () correspods to our ituitive feelig of wht re ought to e. The limit i () m or m ot eist. It c e show tht if f is cotiuous, the this limit does eist; tht is, the regio hs re. [The precise meig of the limit i Defiitio is tht for ever there is correspodig umer such tht A f * i i wheever P I other words, the re c e pproimted sum of res of rectgles to withi ritrr degree of ccurc ( ) tkig the orm of the prtitio sufficietl smll.

11 SECTION AREA EXAMPLE () If the itervl, is divided ito suitervls the prtitio P d the set of prtitio poits is,.,.,.,.5,, fid P. () If f 4 5 d * i is chose to e the left edpoit of the ith suitervl, fid the sum of the res of the pproimtig rectgles. (c) Sketch the pproimtig rectgles. SOLUTION () We re give tht,,.,., 4, 5.5, d, so FIGURE (See Figure 9.) Therefore P m.,.,.4,.4,.5,.5 () Sice * i, the sum of the res of the pproimtig rectgles is, (), = -4+5 f * i i f i f f. f. f. 4 f 5 FIGURE f.5 (c) The grph of f d the pproimtig rectgles re sketched i Figure. EXAMPLE Fid the re uder the prol from to. SOLUTION Sice f is cotiuous, the limit () tht defies the re must eist for ll possile prtitios P of the itervl, s log s P l. To simplif thigs let us tke the prtitio P tht divides, ito suitervls of equl legth. (This is clled regulr prtitio.) The the prtitio poits re,, 4,..., i i,..., d i so the orm of P is P m i The poit * i c e chose to e where i the ith suitervl. For the ske of defiiteess, let us choose it to e the right-hd edpoit: i * i i

12 SECTION AREA Sice P, the coditio P l is equivlet to l. So the defiitio of re () ecomes A P l f* i i i l i l l i l 8 l 8 i l f i 8i 4 ( Theorem.) ( Theorem.) 4 4 The sum i this clcultio is represeted the res of the shded rectgles i Figure. Notice tht i this cse, with our choice of * i s the right-hd edpoit d = R =5.8 = R Å4.85 =5 R =4.747 FIGURE Right sums = L =4.8 = L Å4.548 =5 L =4.587 FIGURE Left sums

13 SECTION AREA sice f is icresig, f * i is the mimum vlue of f o, i, so the sum R of the res of the pproimtig rectgles is lws greter th the ect re A 4. We could just s well hve chose * i to e the left-hd edpoit, tht is, * i i. The f * i is the miimum vlue of f o, i, so the sum L of the res of the pproimtig rectgles i Figure is lws less th A. The clcultio with this choice is s follows: A P l f* i i i l l l 8 l 8 l 4 f i 8 i i l i i i Notice tht we hve otied the sme swer with the differet choice of * i. I fct, we would oti the sme swer if * i ws chose to e the midpoit of, i (see Eercise ) or ideed other poit of this itervl. EXAMPLE 4 Fid the re uder the cosie curve from to, where. SOLUTION As i the first prt of Emple, we choose regulr prtitio P so tht P d we choose * i to e the right-hd edpoit of the ith suitervl: * i i i Sice P l s l, the re uder the cosie curve from to is A P l f* i i i l cosi i l cosi To evlute this limit we use the formul of Eercise 5 i Sectio : cos i si cos si

14 4 SECTION AREA with. The Equtio ecomes si cos 4 A l si Now cos cos l cos s l sice cosie is cotiuous. Lettig t d usig Theorem.5., we hve lim l si t l t si t lim t l t si t Puttig these limits i Equtio 4, we oti A si cos si I prticulr, tkig, we hve proved tht the re uder the cosie curve from to is si (see Figure ). =cos re= FIGURE π NOTE The re clcultios i Emple d 4 re ot es. We will see i Sectio 5., however, tht the Fudmetl Theorem of Clculus gives much esier method for computig these res. Eercises 8 You re give fuctio f, itervl, prtitio poits, d descriptio of * i withi the ith suitervl. () Fid P. () Fid the sum of the res of the pproimtig rectgles, s give i (). (c) Sketch the grph of f d the pproimtig rectgles.. f,, 4,,,,, 4, * i left edpoit. f,, 4,,,,, 4, * i right edpoit. f,, 4,,,,, 4, * i midpoit 4. f,, 4,,.5,,, 4, * i left edpoit 5. f,,,,.5,,.5,.,.5,, * i right edpoit. f,,,,.5,.,.5,, *.5, *, *.5, * 4 7. f si,,,, 4,, 4,, *, *, *, * f 4 cos,,,,, 4,,, * i left edpoit

15 SECTION AREA 5 9. () Sketch grph of the regio tht lies uder the prol from to d use it to mke rough visul estimte of the re of the regio. () Fid epressio for R, the sum of the res of the pproimtig rectgles, tkig * i i () to e the right edpoit d usig suitervls of equl legth. (c) Fid the umericl vlues of the pproimtig res R for,, d 4. (d) Fid the ect re of the regio. ;. () Use grphig device to sketch grph of the regio tht lies uder the curve 4 from to d use it to mke rough visul estimte of the re of the regio. () Fid epressio for R, the sum of the res of the pproimtig rectgles, tkig * i i () to e the right edpoit d usig suitervls of equl legth. (c) Fid the umericl vlues of the pproimtig res R for,, d. (d) Fid the ect re of the regio.. Fid the re from Emple tkig * i to e the midpoit of, i. Illustrte the pproimtig rectgles with sketch.. Fid the re uder the curve from to usig suitervls of equl legth d tkig * i i () to e the () left edpoit, () right edpoit, d (c) midpoit of the ith suitervl. I ech cse, sketch the pproimtig rectgles. 8 Use () to fid the re uder the give curve from to. Use equl suitervls d tke * i to e the right edpoit of the ith suitervl. Sketch the regio..,, 5 4.,, ,,.,, 7.,, 8. 4,, CAS CAS 9 If ou hve progrmmle clcultor (or computer), it is possile to evlute the epressio () for the sum of res of pproimtig rectgles, eve for lrge vlues of, usig loopig. (O TI use the Is commd, o Csio use Isz, o HP or i BASIC use FOR-NEXT loop.) Compute the sum of the res of pproimtig rectgles usig equl suitervls d right edpoits for,, d 5. The guess the vlue of the ect re. 9. The regio uder si from to. The regio uder from to. Some computer lger sstems hve commds tht will drw pproimtig rectgles d evlute the sums of their res, t lest if * i is left or right edpoit. (For istce, i Mple use lefto, righto, leftsum, d rightsum.) () If f s, 4, fid the left d right sums for,, d 5. () Illustrte grphig the rectgles i prt (). (c) Show tht the ect re uder f lies etwee 4. d () If f sisi,, use the commds discussed i Eercise to fid the left d right sums for,, d 5. () Illustrte grphig the rectgles i prt (). (c) Show tht the ect re uder f lies etwee.87 d.9. 4 Determie regio whose re is equl to the give limit. Do ot evlute the limit. i. lim 4. l t 4 4 lim l i 5. Fid the re uder the curve si from to. [Hit: Use equl suitervls d right edpoits, d use Eercise 5 i Sectio.]. () Let A e the re of polgo with equl sides iscried i circle with rdius r. B dividig the polgo ito cogruet trigles with cetrl gle, show tht A r si. () Show tht lim l A r. [Hit: Use Equtio.5..]

16 SECTION THE DEFINITE INTEGRAL SECTION The Defiite Itegrl We sw i the preceedig sectio tht limit of the form A P l f* i i i rises whe we compute re. It turs out tht this sme tpe of limit occurs i wide vriet of situtios eve whe f is ot ecessril positive fuctio. I Chpters 5 d 8 we will see tht limits of the form () lso rise i fidig legths of curves, volumes of solids, res of surfces, ceters of mss, fluid pressure, d work, s well s other qutities. We therefore give this tpe of limit specil me d ottio. Defiitio of Defiite Itegrl If f is fuctio defied o closed itervl,, let P e prtitio of, with prtitio poits,,...,, where Choose poits * i i, i d let i i d P m i. The the defiite itegrl of f from to is f d P l f* i i i if this limit eists. If the limit does eist, the itervl,. f is clled itegrle o the NOTE The smol ws itroduced Leiiz d is clled itegrl sig. It is elogted S d ws chose ecuse itegrl is limit of sums. I the ottio f d, f is clled the itegrd d d re clled the limits of itegrtio; is the lower limit d is the upper limit. The smol d hs o meig itself; f d is ll oe smol. The procedure of clcultig itegrl is clled itegrtio. NOTE The defiite itegrl f d is umer; it does ot deped o. I fct, we could use letter i plce of without chgig the vlue of the itegrl: f d f t dt f r dr NOTE The sum f * i i FIGURE tht occurs i Defiitio is clled Riem sum fter the Germ mthemtici Berhrd Riem (8 8). The defiite itegrl is sometimes clled the Riem itegrl. If f hppes to e positive, the the Riem sum c e iterpreted s sum of res of pproimtig rectgles [Compre () with (.).] If f tkes o oth positive d egtive vlues, s i Figure, the the Riem sum is the sum of the res of the rectgles tht lie ove the -is d the egtives of the res of the rectgles tht lie elow the -is (the res of the gold rectgles mius the res of the lue rectgles). EXAMPLE Let f 5 d cosider the prtitio P of the itervl, mes of the set of prtitio poits,.5,,.,.,. I this emple

17 SECTION THE DEFINITE INTEGRAL 7,, 5, d,.5,,., 4., d 5. the legths of the suitervls re Thus the orm of the prtitio P is Suppose we choose *.8, *., *., * 4, d * 5.7. The the correspodig Riem sum is 5 f * i i f.8 f. f. f 4 f P m.5,.5,.7,.5,.8.8 FIGURE Notice tht, i this emple, f is ot positive fuctio d so the Riem sum does ot represet sum of res of rectgles. But it does represet the sum of the res of the gold rectgles (ove the -is) mius the sum of the res of the lue rectgles (elow the is) i Figure. NOTE 4 A itegrl eed ot represet re. But for positive fuctios, itegrl c e iterpreted s re. I fct, comprig Defiitio with the defiitio of re (.), we see the followig: For the specil cse where f, f d the re uder the grph of f from to I geerl, defiite itegrl c e iterpreted s differece of res: f d A A + _ + where A is the re of the regio ove the -is d elow the grph of f d A is the re of the regio elow the -is d ove the grph of f. (This seems resole from compriso of Figures d.) FIGURE NOTE 5 The follows: precise meig of the limit tht defies the itegrl i Defiitio is s f d I mes tht for ever there is correspodig umer such tht I f * i i for ll prtitios P of, with P d for ll possile choices of * i i, i.

18 8 SECTION THE DEFINITE INTEGRAL Berhrd Riem received his Ph.D. uder the directio of the legedr Guss t the Uiversit of Göttige d remied there to tech. Guss, who ws ot i the hit of prisig other mthemticis, spoke of Riem s cretive, ctive, trul mthemticl mid d gloriousl fertile origilit. The defiitio () of itegrl tht we use is due to Riem. He lso mde mjor cotriutios to the theor of fuctios of comple vrile, mthemticl phsics, umer theor, d the foudtios of geometr. Riem s rod cocept of spce d geometr tured out to e the right settig, 5 ers lter, for Eistei s geerl reltivit theor. Riem s helth ws poor throughout his life, d he died of tuerculosis t the ge of 9. This mes tht defiite itegrl c e pproimted to withi desired degree of ccurc Riem sum. NOTE I Defiitio we re delig with fuctio f defied o itervl,, so we re implicitl ssumig tht. But for some purposes it is useful to eted the defiitio of to the cse where f d or s follows: EXAMPLE Epress If, the f d. f d If, the f d. lim P l * i * i si * i i i s itegrl o the itervl,. SOLUTION Comprig the give limit with the limit i Defiitio, we see tht the will e ideticl if we choose f si We re give tht d. Therefore, Defiitio, we hve lim P l i * i * i si * i i si d EXAMPLE Evlute the followig itegrls iterpretig ech i terms of res. () s d () d = œ - or + = SOLUTION () Sice f s, we c iterpret this itegrl s the re uder the curve s from to. But, sice, we get, which shows tht the grph of f is the qurter-circle with rdius i Figure 4. Therefore s d 4 4 FIGURE 4 (I Sectio 8. we will e le to prove tht the re of circle of rdius r is r evlutig the itegrl r sr d usig the techiques of Chpter 8.) () The grph of is the lie with slope show i Figure 5. We compute the itegrl s the differece of the res of the two trigles: d A A.5 (, ) =- A A FIGURE 5 _

19 SECTION THE DEFINITE INTEGRAL 9 The itegrls i Emple were simple to evlute ecuse we were le to epress them i terms of res of simple regios, ut ot ll itegrls re tht es. I fct, the itegrls of some fuctios do t eve eist. So the questio rises: Which fuctios re itegrle? A prtil swer is give the followig theorem, which is proved i courses o dvced clculus. 4 Theorem If f is either cotiuous or mootoic o,, the f is itegrle o, ; tht is, the defiite itegrl f d eists. FIGURE Discotiuous itegrle fuctio FIGURE 7 Noitegrle fuctio If f is discotiuous t some poits i,, the f d might eist or it might ot eist (see Eercises 7 d 7). If f hs ol fiite umer of discotiuities d these re ll jump discotiuities, the f is clled piecewise cotiuous d it turs out tht f is itegrle. (See Figure.) It c e show tht if f is itegrle o,, the f must e ouded fuctio o, ; tht is, there eists umer M such tht f M for ll i,. Geometricll, this mes tht the grph of f lies etwee the horizotl lies M d M. I prticulr, if f hs ifiite discotiuit t some poit i,, the f is ot ouded d is therefore ot itegrle. (See Eercise 7 d Figure 7.) If f is itegrle o,, the the Riem sums () must pproch f d s P l o mtter how the prtitios P re chose d o mtter how the poits * i re chose i, i. Therefore, if it is kow eforehd tht f is itegrle o, ( for istce, if it is kow tht f is cotiuous or mootoic), the i clcultig the vlue of itegrl we re free to choose prtitios P d poits * i i w we like s log s P l. For purposes of clcultio, it is ofte coveiet to tke P to e regulr prtitio; tht is, ll the suitervls hve the sme legth. The d,,,..., i i If we choose * i to e the right edpoit of the ith suitervl, the i * i i i Sice P, we hve P l s l, so Defiitio gives f d P l f* i i l i f i Sice does ot deped o i, Theorem. llows us to tke it i frot of the sigm sig, d we hve the followig formul for clcultig itegrls. 5 Theorem If f is itegrle o,, the f d l f i

20 SECTION THE DEFINITE INTEGRAL EXAMPLE 4 Evlute 5 d. SOLUTION Here we hve f 5,, d. Sice f is cotiuous, we kow it is itegrle d so Theorem 5 gives 5 d l l 8 l l f i lim l i i i i FIGURE 8 This itegrl cot e iterpreted s re ecuse f tkes o oth positive d egtive vlues. But it c e iterpreted s the differece of res A A, where A d re show i Figure 8. Figure 9 illustrtes the clcultio showig the positive d egtive terms i the right Riem sum R for 4. The vlues i the tle show the Riem sums pprochig the ect vlue of the itegrl,.5, s l. A R FIGURE 9 A much simpler method for evlutig the itegrl i Emple 4 will e give i Sectio 5.4 fter we hve proved the Fudmetl Theorem of Clculus. The Midpoit Rule We ofte choose the smple poit * i to e the right edpoit of the ith suitervl ecuse it is coveiet for computig the limit. But if the purpose is to fid pproimtio to itegrl, it is usull etter to choose * i to e the midpoit of the itervl, which we deote i. A Riem sum is pproimtio to itegrl, ut if we use midpoits d regulr prtitio we get the followig pproimtio: Midpoit Rule f d f i f f where d i i midpoit of, i

21 SECTION THE DEFINITE INTEGRAL = EXAMPLE 5 Use the Midpoit Rule with 5 to pproimte. d SOLUTION The prtitio poits re,.,.4,.,.8, d., so the midpoits of the five itervls re.,.,.5,.7, d.9. The width of the itervls is 5 5, so the Midpoit Rule gives d f. f. f.5 f.7 f FIGURE Sice f for, the itegrl represets re d the pproimtio give the Midpoit Rule is the sum of the res of the rectgles show i Figure. At the momet we do t kow how ccurte the pproimtio i Emple 5 is, ut i Sectio 8.7 we will ler method for estimtig the error ivolved i usig the Midpoit Rule. At tht time we will discuss other methods for pproimtig defiite itegrls. If we ppl the Midpoit Rule to the itegrl i Emple 4, we get the picture i Figure. The pproimtio M 4.5 is much closer to the true vlue.5 th the right edpoit pproimtio, R show i Figure 9. Properties of the Defiite Itegrl FIGURE M 4.5 We ow develop some sic properties of itegrls tht will help us to evlute itegrls i simple mer. Properties of the Itegrl Suppose tht ll of the followig itegrls eist. The. cd c, where c is costt. f t d f d t d. cf d c f d, where c is costt f t d f d t d f d f d f d The proof of Propert is requested i Eercise 5. This propert ss tht the itegrl of costt fuctio f c is the costt times the legth of the itervl. If c d, this is to e epected ecuse c is the re of the shded rectgle i Figure. c =c FIGURE j c d=c(-) re=c(-)

22 SECTION THE DEFINITE INTEGRAL Proof of Propert Sice f t d eists, we c compute it usig regulr prtitio d choosig * i to e the right edpoit of the ith suitervl, tht is, * i i. Usig the fct tht the limit of sum is the sum of the limits, we hve f t d l f i t i l f i t i l f i l t i f d t d ( Theorem.) FIGURE =ƒ c Propert ss tht the itegrl of sum is the sum of the itegrls. Propert c e proved i similr mer (see Eercise 5) d ss tht the itegrl of costt times fuctio is the costt times the itegrl of the fuctio. I other words, costt (ut ol costt) c e tke i frot of itegrl sig. Propert 4 is proved writig f t f td usig Properties d with c. Propert 5 is somewht more complicted d is proved t the ed of this sectio, ut for the cse where f d c, it c e see from the geometric iterprettio i Figure. For positive fuctios f, f d is the totl re uder f from to, which is the sum of (the re from to c ) d c f d f d (the re from c c to ). EXAMPLE Use the properties of itegrls d the results d cos d (from Eercise i this sectio d Emple 4 i Sectio ) to evlute the followig itegrls. () cos d () 5 4 d SOLUTION () Usiig Properties d of itegrls, we get () Sice cos d d if if cos d 8 we use Propert 5 to split the itegrl t : 5 d d 5 d 4 4 d 5 4 d 4 d 5 d Notice tht Properties 5 re true whether,, or. The followig properties, however, re true ol if.

23 SECTION THE DEFINITE INTEGRAL Order Properties of the Itegrl Suppose the followig itegrls eist d.. If f for, the f d. 7. If f t for, the f d t d. 8. If m f M for, the m f d M 9. f d f d M m FIGURE 4 =ƒ If f, the f d represets the re uder the grph of f, so the geometric iterprettio of Propert is simpl tht res re positive. But the propert c e proved from the defiitio of itegrl (Eercise ). Propert 7 ss tht igger fuctio hs igger itegrl. It follows from Properties d 4 ecuse f t. Propert 8 is illustrted Figure 4 for the cse where f. If f is cotiuous we could tke m d M to e the solute miimum d mimum vlues of f o the itervl,. I this cse Propert 8 ss tht the re uder the grph of f is greter th the re of the rectgle with height m d less th the re of the rectgle with height M. Proof of Propert 8 Sice m f M, Propert 7 gives md f d Md Usig Propert to evlute the itegrls o the left- d right-hd sides, we oti m f d M The proof of Propert 9 is left s Eercise 7. 4 EXAMPLE 7 Use Propert 8 to estimte the vlue of s d. =œ 4 FIGURE 5 SOLUTION Sice f s is icresig fuctio, its solute miimum o, 4 is m f d its solute mimum o, 4 is M f 4 s4. Thus Propert 8 gives or The result of Emple 7 is illustrted i Figure 5. The re uder s from to 4 is greter th the re of the lower rectgle d less th the re of the lrge rectgle. EXAMPLE 8 Show tht s d s d 4 4 s d SOLUTION The miimum vlue of f s o, 4 is m f s, sice f is icresig. Thus Propert 8 gives 4 s d s4 s 4.4

24 4 SECTION THE DEFINITE INTEGRAL This result is ot good eough, so isted we use Propert 7. Notice tht Sice for, we hve s for 4. Thus, Propert 7, 4? s s s d 4 d [Here we hve used the fct tht d from Eercise.] Proof of Propert 5 We first ssume tht c. Sice we re ssumig tht f d eists, we c compute it s limit of Riem sums usig ol prtitios P tht iclude c s oe of the prtitio poits. If P is such prtitio, let P e the correspodig prtitio of, c determied those prtitio poits of P tht lie i, c. Similrl, P will deote the correspodig prtitio of c,. Note tht P P d P P. Thus, if P l, it follows tht P d P l l. If i i is the set of prtitio poits for P d k m, where k is the umer of suitervls i, cd m is the umer of suitervls i c,, the i i k is the set of prtitio poits for P. If we write t j for the prtitio poits to the right of c kj, the t i j m is the set of prtitio poits for. Thus we hve P k k Choosig * d lettig t i i j t j t j, we compute f d s follows: f P l f i i P l k f i i P l k f i i m j P l k f i i P l m f t j t j j c f d f t dt Now suppose tht c. B wht we hve lred proved, we hve c c t t m ik f i i f t j t j f f d f d c Therefore f c f d f d c f d f d (See Note.) The proofs re similr for the remiig four orderigs of,, d c. c

25 SECTION THE DEFINITE INTEGRAL 5 Eercises You re give fuctio f, itervl, prtitio poits Riem sums for the fuctio f s o the itervl tht defie prtitio P, d poits * i i the ith suitervl., with. Epli wh these estimtes show tht () Fid P. () Fid the Riem sum ().. f 7,, 5,,.,.,., 4., 5, * i midpoit.85 s d.85. f,,,,.,.,,.8,.,, Deduce tht the pproimtio usig the Midpoit Rule with * i midpoit i Eercise is ccurte to two deciml plces.. f,,,,.4,,,.8,.4,, 5 Use Theorem 5 to evlute the itegrl. * i right edpoit 4. f,,,,.5,,.7,.4,, 5. c d. 7 d * i left edpoit 5. f,,,,.5,,.5,, *, *.4, *., * 4. f si,,,,,,,,, *.5, *.5, *.5, * 4.5, * d d. 5 d 5 4 d 7. The grph of fuctio f is give. Estimte f d usig four equl suitervls with () right edpoits, () left edpoits, d (c) midpoits. f 8. Prove tht d.. Prove tht d. 8 Evlute the itegrl iterpretig it i terms of res.. d 4. s4 d 5. ( s9 ) d. d CAS 8. The tle gives the vlues of fuctio otied from eperimet. Use them to estimte f d usig three equl suitervls with () right edpoits, () left edpoits, d (c) midpoits. If the fuctio is kow to e decresig fuctio, c ou s whether our estimtes re less th or greter th the ect vlue of the itegrl? 9 Use the Midpoit Rule with the give vlue of to pproimte the itegrl. Roud the swer to four deciml plces d, f s d,.. If ou hve CAS tht evlutes midpoit pproimtios d grphs the correspodig rectgles (use middlesum d middleo commds i Mple), check the swer to Eercise d illustrte with grph. The repet with d. 4. With progrmmle clcultor or computer (see the istructios for Eercise 9 i Sectio ), compute the left d right 4 d, 4 7 t d, Epress the limit s defiite itegrl o the give itervl. 9. lim * i 5* i i,. lim s* i i,. lim cos i i, t i. lim i, 5 Epress the limit s defiite itegrl.. lim [Hit: Cosider f 4.] ( ) d Pl Pl Pl Pl i 4 l 5 lim l i i lim l i, 4 5,, 4, 5 d

26 SECTION THE DEFINITE INTEGRAL. Evlute cos d. 7. Give tht s d 8, wht is st dt? () Fid pproimtio to the itegrl d usig Riem sum with right edpoits d 8. () Drw digrm like Figure to illustrte the pproimtio i prt (). (c) Evlute 4 d. (d) Iterpret the itegrl i prt (c) s differece of res d illustrte with digrm like Figure Use the properties of itegrls to evlute ech itegrl. You m ssume from Sectio tht d ou m use the results of Eercises d. 9. s d d 4. 5 cos 4 d if 4. where f f d if Write the give sum or differece s sigle itegrl i the form f d Use the properties of itegrls to verif the iequlit without evlutig the itegrls f d f d f d f d 5 f d f d 7 f d s5 d s d d 4 8 d si d 5. s d s f d f d f d f d f d f d 5 si d 4 si d 4 4 cos d si d Use Propert 8 to estimte the vlue of the itegrl d 57. d s 4 d. 4 Use properties of itegrls, together with Eercises d, to prove the iequlit Prove Propert of itegrls.. Prove Propert of itegrls. 7. Prove Propert 9 of itegrls. [Hit:.] 8. Suppose tht f is cotiuous o, d f for ll i,. Prove tht f d. [Hit: Use the Etreme Vlue Theorem d Propert 8.] 9. Which of the followig fuctios re itegrle o the itervl,? () f si () f sec if (c) f if (d) 7. Let f si d f d s 4 d 5 s d.5 si d 8 cos d f f f f if if f t if if s d 4 si d 4 () Show tht f is ot cotiuous o,. () Show tht f is uouded o,. (c) Show tht f d does ot eist, tht is, f is ot itegrle o,. [Hit: Show tht the first term i the Riem sum, f*, c e mde ritrril lrge.] 4 cos d

27 SECTION THE DEFINITE INTEGRAL A7 7. Let Show tht f is ouded ut ot itegrle o,. [Hit: Show tht, o mtter how smll P is, some Riem sums re wheres others re equl to.] 7. Evlute d usig prtitio of, poits of geometric progressio:,,,...,,..., i i. Tke * i i d use the formul i Eercise 47 i Sectio for the sum of geometric series. if is rtiol f if is irrtiol 7. Fid d. Hit: Use regulr prtitio ut choose * to i e the geometric me of d i ( * i s i ) d use the idetit mm m m ; 74. () Drw the grph of the fuctio f cos i the viewig rectgle,,. () If we defie ew fuctio t t, the cost dt t is the re uder the grph of f from to [util f ecomes egtive, t which poit t ecomes differece of res.] Use the grph of f from prt () to estimte the vlue of t whe,.,.4,.,... up to. At wht vlue of does t strt to decrese? (c) Use the iformtio from prt () to sketch rough grph of t. (d) Sketch more ccurte grph of t usig our clcultor or computer to estimte t., t.4,.... (Use the itegrtio commd, if ville, or the Midpoit Rule.) (e) Use our grph of t from prt (d) to sketch the grph of t usig the iterprettio of t s the slope of tget lie. How does the grph of t compre with the grph of f?

Application: Volume. 6.1 Overture. Cylinders

Application: Volume. 6.1 Overture. Cylinders Applictio: Volume 61 Overture I this chpter we preset other pplictio of the defiite itegrl, this time to fid volumes of certi solids As importt s this prticulr pplictio is, more importt is to recogize

More information

MATHEMATICS FOR ENGINEERING BASIC ALGEBRA

MATHEMATICS FOR ENGINEERING BASIC ALGEBRA MATHEMATICS FOR ENGINEERING BASIC ALGEBRA TUTORIAL - INDICES, LOGARITHMS AND FUNCTION This is the oe of series of bsic tutorils i mthemtics imed t begiers or yoe wtig to refresh themselves o fudmetls.

More information

Summation Notation The sum of the first n terms of a sequence is represented by the summation notation i the index of summation

Summation Notation The sum of the first n terms of a sequence is represented by the summation notation i the index of summation Lesso 0.: Sequeces d Summtio Nottio Def. of Sequece A ifiite sequece is fuctio whose domi is the set of positive rel itegers (turl umers). The fuctio vlues or terms of the sequece re represeted y, 2, 3,...,....

More information

Repeated multiplication is represented using exponential notation, for example:

Repeated multiplication is represented using exponential notation, for example: Appedix A: The Lws of Expoets Expoets re short-hd ottio used to represet my fctors multiplied together All of the rules for mipultig expoets my be deduced from the lws of multiplictio d divisio tht you

More information

Chapter 04.05 System of Equations

Chapter 04.05 System of Equations hpter 04.05 System of Equtios After redig th chpter, you should be ble to:. setup simulteous lier equtios i mtrix form d vice-vers,. uderstd the cocept of the iverse of mtrix, 3. kow the differece betwee

More information

Released Assessment Questions, 2015 QUESTIONS

Released Assessment Questions, 2015 QUESTIONS Relesed Assessmet Questios, 15 QUESTIONS Grde 9 Assessmet of Mthemtis Ademi Red the istrutios elow. Alog with this ooklet, mke sure you hve the Aswer Booklet d the Formul Sheet. You my use y spe i this

More information

MATHEMATICS SYLLABUS SECONDARY 7th YEAR

MATHEMATICS SYLLABUS SECONDARY 7th YEAR Europe Schools Office of the Secretry-Geerl Pedgogicl developmet Uit Ref.: 2011-01-D-41-e-2 Orig.: DE MATHEMATICS SYLLABUS SECONDARY 7th YEAR Stdrd level 5 period/week course Approved y the Joit Techig

More information

PROBLEMS 05 - ELLIPSE Page 1

PROBLEMS 05 - ELLIPSE Page 1 PROBLEMS 0 ELLIPSE Pge 1 ( 1 ) The edpoits A d B of AB re o the X d Yis respectivel If AB > 0 > 0 d P divides AB from A i the rtio : the show tht P lies o the ellipse 1 ( ) If the feet of the perpediculrs

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

We will begin this chapter with a quick refresher of what an exponent is.

We will begin this chapter with a quick refresher of what an exponent is. .1 Exoets We will egi this chter with quick refresher of wht exoet is. Recll: So, exoet is how we rereset reeted ultilictio. We wt to tke closer look t the exoet. We will egi with wht the roerties re for

More information

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

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

More information

m n Use technology to discover the rules for forms such as a a, various integer values of m and n and a fixed integer value a.

m n Use technology to discover the rules for forms such as a a, various integer values of m and n and a fixed integer value a. TIth.co Alger Expoet Rules ID: 988 Tie required 25 iutes Activity Overview This ctivity llows studets to work idepedetly to discover rules for workig with expoets, such s Multiplictio d Divisio of Like

More information

Harold s Calculus Notes Cheat Sheet 26 April 2016

Harold s Calculus Notes Cheat Sheet 26 April 2016 Hrol s Clculus Notes Chet Sheet 26 April 206 AP Clculus Limits Defiitio of Limit Let f e fuctio efie o ope itervl cotiig c let L e rel umer. The sttemet: lim x f(x) = L mes tht for ech ε > 0 there exists

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

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

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

SOME IMPORTANT MATHEMATICAL FORMULAE

SOME IMPORTANT MATHEMATICAL FORMULAE SOME IMPORTANT MATHEMATICAL FORMULAE Circle : Are = π r ; Circuferece = π r Squre : Are = ; Perieter = 4 Rectgle: Are = y ; Perieter = (+y) Trigle : Are = (bse)(height) ; Perieter = +b+c Are of equilterl

More information

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

AREA OF A SURFACE OF REVOLUTION

AREA OF A SURFACE OF REVOLUTION AREA OF A SURFACE OF REVOLUTION h cut r πr h A surfce of revolution is formed when curve is rotted bout line. Such surfce is the lterl boundr of solid of revolution of the tpe discussed in Sections 7.

More information

MATHEMATICAL ANALYSIS

MATHEMATICAL ANALYSIS Mri Predoi Trdfir Băl MATHEMATICAL ANALYSIS VOL II INTEGRAL CALCULUS Criov, 5 CONTENTS VOL II INTEGRAL CALCULUS Chpter V EXTENING THE EFINITE INTEGRAL V efiite itegrls with prmeters Problems V 5 V Improper

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

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

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

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

More information

Section 11.3: The Integral Test

Section 11.3: The Integral Test Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult

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

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

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

More information

n Using the formula we get a confidence interval of 80±1.64

n Using the formula we get a confidence interval of 80±1.64 9.52 The professor of sttistics oticed tht the rks i his course re orlly distributed. He hs lso oticed tht his orig clss verge is 73% with stdrd devitio of 12% o their fil exs. His fteroo clsses verge

More information

Math 113 HW #11 Solutions

Math 113 HW #11 Solutions Math 3 HW # Solutios 5. 4. (a) Estimate the area uder the graph of f(x) = x from x = to x = 4 usig four approximatig rectagles ad right edpoits. Sketch the graph ad the rectagles. Is your estimate a uderestimate

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

A. Description: A simple queueing system is shown in Fig. 16-1. Customers arrive randomly at an average rate of

A. Description: A simple queueing system is shown in Fig. 16-1. Customers arrive randomly at an average rate of Queueig Theory INTRODUCTION Queueig theory dels with the study of queues (witig lies). Queues boud i rcticl situtios. The erliest use of queueig theory ws i the desig of telehoe system. Alictios of queueig

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties 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 information

Convexity, Inequalities, and Norms

Convexity, 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 information

I. Chi-squared Distributions

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

More information

Sequences and Series

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

More information

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS Lecture Notes PH 4/5 ECE 598 A. L Ros INTRODUCTION TO QUANTUM MECHANICS CHAPTER-0 WAVEFUNCTIONS, OBSERVABLES d OPERATORS 0. Represettios i the sptil d mometum spces 0..A Represettio of the wvefuctio i

More information

www.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values)

www.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values) www.mthsbo.org.uk CORE SUMMARY NOTES Functions A function is rule which genertes ectl ONE OUTPUT for EVERY INPUT. To be defined full the function hs RULE tells ou how to clculte the output from the input

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

Chapter 13 Volumetric analysis (acid base titrations)

Chapter 13 Volumetric analysis (acid base titrations) Chpter 1 Volumetric lysis (cid se titrtios) Ope the tp d ru out some of the liquid util the tp coectio is full of cid d o ir remis (ir ules would led to iccurte result s they will proly dislodge durig

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

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

MATHEMATICAL INDUCTION

MATHEMATICAL INDUCTION MATHEMATICAL INDUCTION. Itroductio Mthemtics distiguishes itself from the other scieces i tht it is built upo set of xioms d defiitios, o which ll subsequet theorems rely. All theorems c be derived, or

More information

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

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

More information

Infinite Sequences and Series

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

More information

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx SAMPLE QUESTIONS FOR FINAL EXAM REAL ANALYSIS I FALL 006 3 4 Fid the followig usig the defiitio of the Riema itegral: a 0 x + dx 3 Cosider the partitio P x 0 3, x 3 +, x 3 +,......, x 3 3 + 3 of the iterval

More information

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem Lecture 4: Cauchy sequeces, Bolzao-Weierstrass, ad the Squeeze theorem The purpose of this lecture is more modest tha the previous oes. It is to state certai coditios uder which we are guarateed that limits

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

STUDY COURSE BACHELOR OF BUSINESS ADMINISTRATION (B.A.)

STUDY COURSE BACHELOR OF BUSINESS ADMINISTRATION (B.A.) STUDY COURSE BACHELOR OF BUSINESS ADMINISTRATION (B.A. MATHEMATICS (ENGLISH & GERMAN REPETITORIUM 0/06 Prof. Dr. Philipp E. Zeh Mthemtis Prof. Dr. Philipp E. Zeh LITERATURE (GERMAN Böker, F., Formelsmmlug

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

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

More information

Soving Recurrence Relations

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

More information

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series 8 Fourier Series Our aim is to show that uder reasoable assumptios a give -periodic fuctio f ca be represeted as coverget series f(x) = a + (a cos x + b si x). (8.) By defiitio, the covergece of the series

More information

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding 1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde

More information

Measures of Spread and Boxplots Discrete Math, Section 9.4

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

More information

1. MATHEMATICAL INDUCTION

1. MATHEMATICAL INDUCTION 1. MATHEMATICAL INDUCTION EXAMPLE 1: Prove that for ay iteger 1. Proof: 1 + 2 + 3 +... + ( + 1 2 (1.1 STEP 1: For 1 (1.1 is true, sice 1 1(1 + 1. 2 STEP 2: Suppose (1.1 is true for some k 1, that is 1

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

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

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

More information

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

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

More information

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

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

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

More information

Discontinuous Simulation Techniques for Worm Drive Mechanical Systems Dynamics

Discontinuous Simulation Techniques for Worm Drive Mechanical Systems Dynamics Discotiuous Simultio Techiques for Worm Drive Mechicl Systems Dymics Rostyslv Stolyrchuk Stte Scietific d Reserch Istitute of Iformtio Ifrstructure Ntiol Acdemy of Scieces of Ukrie PO Box 5446, Lviv-3,

More information

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

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

More information

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5 Sectio 13 Kolmogorov-Smirov test. Suppose that we have a i.i.d. sample X 1,..., X with some ukow distributio P ad we would like to test the hypothesis that P is equal to a particular distributio P 0, i.e.

More information

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

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

More information

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

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

Asymptotic Growth of Functions

Asymptotic 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 information

Chapter 5: Inner Product Spaces

Chapter 5: Inner Product Spaces Chapter 5: Ier Product Spaces Chapter 5: Ier Product Spaces SECION A Itroductio to Ier Product Spaces By the ed of this sectio you will be able to uderstad what is meat by a ier product space give examples

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

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

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

More information

Introduction to Integration Part 2: The Definite Integral

Introduction to Integration Part 2: The Definite Integral Mthemtics Lerning Centre Introduction to Integrtion Prt : The Definite Integrl Mr Brnes c 999 Universit of Sdne Contents Introduction. Objectives...... Finding Ares 3 Ares Under Curves 4 3. Wht is the

More information

Theorems About Power Series

Theorems About Power Series Physics 6A Witer 20 Theorems About Power Series Cosider a power series, f(x) = a x, () where the a are real coefficiets ad x is a real variable. There exists a real o-egative umber R, called the radius

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

Gray level image enhancement using the Bernstein polynomials

Gray level image enhancement using the Bernstein polynomials Buletiul Ştiiţiic l Uiersităţii "Politehic" di Timişor Seri ELECTRONICĂ şi TELECOMUNICAŢII TRANSACTIONS o ELECTRONICS d COMMUNICATIONS Tom 47(6), Fscicol -, 00 Gry leel imge ehcemet usig the Berstei polyomils

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

Basic Elements of Arithmetic Sequences and Series

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

More information

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

Lesson 15 ANOVA (analysis of variance)

Lesson 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 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

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

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

More information

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

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

More information

INVESTIGATION OF PARAMETERS OF ACCUMULATOR TRANSMISSION OF SELF- MOVING MACHINE

INVESTIGATION OF PARAMETERS OF ACCUMULATOR TRANSMISSION OF SELF- MOVING MACHINE ENGINEEING FO UL DEVELOENT Jelgv, 28.-29.05.2009. INVESTIGTION OF ETES OF CCUULTO TNSISSION OF SELF- OVING CHINE leksdrs Kirk Lithui Uiversity of griculture, Kus leksdrs.kirk@lzuu.lt.lt bstrct. Uder the

More information

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

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

More information

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

How To Solve An Old Japanese Geometry Problem

How To Solve An Old Japanese Geometry Problem 116 Taget circles i the ratio 2 : 1 Hiroshi Okumura ad Masayuki Wataabe I this article we cosider the followig old Japaese geometry problem (see Figure 1), whose statemet i [1, p. 39] is missig the coditio

More information

Sequences and Series

Sequences and Series Secto 9. Sequeces d Seres You c thk of sequece s fucto whose dom s the set of postve tegers. f ( ), f (), f (),... f ( ),... Defto of Sequece A fte sequece s fucto whose dom s the set of postve tegers.

More information

INFINITE SERIES KEITH CONRAD

INFINITE SERIES KEITH CONRAD INFINITE SERIES KEITH CONRAD. Itroductio The two basic cocepts of calculus, differetiatio ad itegratio, are defied i terms of limits (Newto quotiets ad Riema sums). I additio to these is a third fudametal

More information

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have Comple Numbers I spite of Calvi s discomfiture, imagiar umbers (a subset of the set of comple umbers) eist ad are ivaluable i mathematics, egieerig, ad sciece. I fact, i certai fields, such as electrical

More information

Case Study. Normal and t Distributions. Density Plot. Normal Distributions

Case 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 information

SEQUENCES AND SERIES

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

More information

1 Correlation and Regression Analysis

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

More information

CS103X: Discrete Structures Homework 4 Solutions

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

More information

Building Blocks Problem Related to Harmonic Series

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

More information

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

Normal Distribution.

Normal Distribution. Normal Distributio www.icrf.l Normal distributio I probability theory, the ormal or Gaussia distributio, is a cotiuous probability distributio that is ofte used as a first approimatio to describe realvalued

More information

MATHEMATICS P1 COMMON TEST JUNE 2014 NATIONAL SENIOR CERTIFICATE GRADE 12

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

More information

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

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

More information

Lecture 3. denote the orthogonal complement of S k. Then. 1 x S k. n. 2 x T Ax = ( ) λ x. with x = 1, we have. i = λ k x 2 = λ k.

Lecture 3. denote the orthogonal complement of S k. Then. 1 x S k. n. 2 x T Ax = ( ) λ x. with x = 1, we have. i = λ k x 2 = λ k. 18.409 A Algorithmist s Toolkit September 17, 009 Lecture 3 Lecturer: Joatha Keler Scribe: Adre Wibisoo 1 Outlie Today s lecture covers three mai parts: Courat-Fischer formula ad Rayleigh quotiets The

More information

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required.

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required. S. Tay MAT 344 Sprig 999 Recurrece Relatios Tower of Haoi Let T be the miimum umber of moves required. T 0 = 0, T = 7 Iitial Coditios * T = T + $ T is a sequece (f. o itegers). Solve for T? * is a recurrece,

More information

Calculus Cheat Sheet. except we make f ( x ) arbitrarily large and. Relationship between the limit and one-sided limits

Calculus Cheat Sheet. except we make f ( x ) arbitrarily large and. Relationship between the limit and one-sided limits Clulus Chet Sheet Limits Deiitios Preise Deiitio : We sy lim L i or every ε > 0 there is δ > 0 suh tht wheever 0 δ L < ε. < < the Workig Deiitio : We sy lim L i we mke ( ) s lose to L s we wt y tkig suiietly

More information