RECHERCHES sur une question relative au calcul des probabilités

Size: px
Start display at page:

Download "RECHERCHES sur une question relative au calcul des probabilités"

Transcription

1 RECHERCHES sur ue questio relative au calcul des probabilités M. JEAN TREMBLEY Mémoires de l Académie royale des scieces et belles-lettres, Berli 1794/5 ages Oe fids at the ed of the secod volume of the aalytic Works of Mr. Euler, prited i etersburg i 1795, a Memoir etitled: Solutio quarudam quaestioum difficiorum i calculo probabilitatum. 1 These questios revolve o the lottery of Geoa, which has bee sice imitated at Maheim, at aris, at Berli & i other cities of Europe, i which out of 90 tickets marked with umbers 1,, 3,... 90, oe draws 5 of them at some fied periods. Mr. Euler supposig ay umber tickets, of which oe draws at each time a umber p, & which oe puts back agai ito the ur which cotaied them, seeks the probability that i a give umber of coups oe will have brought forth all umbers, the probability that oe will have brought forth 1 umbers at least, the probability that oe will have brought forth umbers at least &c. Has igitur quaestioes, says Mr. Euler, utpote difficillimas hic e pricipiis calculi probabilitatum iam pridem usus receptis resolvere costitui. Qui i huiusmodi ivestigatioibus elaborarut, facile perspiciet resolutioem harum quaestioum calculos maime itricatos postulare, quos autem mihi beeficio certorum caracterum superare licuit. 3 The aalysis of which Mr. Euler makes use i this Memoir is very igeious & worthy of this great geometer, but as it is a little idirect & as it would ot be easy to apply it to the geeral problem of which this oe is oly a particular case, I have udertake to treat the thig directly accordig to the theory of combiatios, & to give to the questio all the etet of which it is susceptible. 1. Let a regular prism of which the umber of faces are, amog which there Traslated by Richard J. ulskamp, Departmet of Mathematics & Computer Sciece, Xavier Uiversity, Ciciati, OH. December 1, 009 Read to the Academy 18 Jue Opuscula Aalytica Vol. II, 1785, p Traslator s ote: The word used is uméro. This sigifies a umber used i the sese of a label. 3 Traslator s ote: We have here i the first setece a etract from the first paragraph of Euler s paper E600. Therefore here I have decided to resolve these questios, iasmuch as they are the most difficult oes, from the priciples of the calculus of probability, which have log sice bee accepted by practice. It is followed by most, but ot all of the first setece of the secod paragraph. Everyoe who has carefully labored i ivestigatios of this sort, easily will observe the solutio of these questios to require the most itricate calculatios, but which by beefit of certai characters, it is permitted by me to have the upper had. 1

2 are a marked 1, a marked, a marked 3,... a marked, oe demads the probability that at the ed of a umber coups oe will have brought forth all the kids of faces. The probability that 1 will ot come at all is =, therefore the probability that 1 will come with or without is 1. The probability that, will ot come at all is = the probability that either 1 or will come is =. The first of these probabilities gives the umber of combiatios by a where all the umbers are foud ecept, the secod gives the umber of combiatios where either 1 or is foud. If oe subtracts this umber of combiatios from the precedig, oe will have the umber of combiatios where 1 is foud without ; thus a epresses the probability that 1 will come without. If oe subtracts this probability from that which 1 will come with or without, there will remai for the probability that oe will brig forth 1 &, a a a a 1. This formula epresses thus the probability that 1 & will come with or without 3, ow epresses the probability that 3 will ot come at all, that is to say it gives the combiatios where all the umbers will come ecept 3; a epresses the probability that either 1 or 3 will come, that is to say it gives the combiatios where all the umbers will come ecept 1 & 3; subtractig this umber from the precedig oe has the combiatios where 1 is foud & ot 3, therefore a epresses the probability that 1 will come without 3, et a epresses the probability that either or 3 will come, that is to say it gives the combiatios where either or 3 is foud; a a epresses the probability that either 1, or, or 3 will come, that is to say it gives the combiatios where either 1 or or 3 is foud. Subtractig this umber from the precedig oe has the combiatios where 1 is foud without or 3, therefore a epresses the probability that 1 will come without or 3; ow a a subtractig from the umber of combiatios where 1 is foud & ot 3, the oe where 1 is foud without or 3, there will remai the umber of combiatios where 1 & is foud without 3, therefore a a a a a a a a epresses the probability that 1 & will come without 3; if oe subtracts this probability from the oe that 1 & will come with or without 3, there will remai the

3 probability that 1 will come with & 3 = a a a a a 1 a a a a a a a. This formula epresses the probability that 1, & 3 will come with or without 4; ow iv epresses the probability that 4 will ot come at all, that is to say it gives the combiatios where all the umbers ca be, ecept 4; a iv epresses the probability that either 1 or 4 will come, that is to say it gives the combiatios where all the letters ca be, ecept 1 & 4; subtractig this umber from the precedig, oe has the combiatios where 1 will be foud, but ot 4, therefore iv a iv epresses the probability that 1 will come without 4, et a iv epresses the probability that either or 4 will come, that is to say it gives the combiatios where it will be watig & 4; a a iv epresses the probability that either 1 or or 4 will come, that is to say it gives the combiatios where 1, & 4 will be watig. Subtractig this umber from the precedig, oe will have the combiatios where 1 will be foud without or 4, therefore epresses the a iv a a iv probability that 1 will come without or 4; subtractig these combiatios from those where is foud 1 without 4 with or without, oe will have those where 1 is foud with without 4, therefore a iv a a iv a a iv a a a iv epresses the probability that 1 will come with without 4; moreover a iv epresses the probability that either 3 or 4 will come, that is to say it gives the combiatios where 3 & 4 will be watig; a a iv epresses the probability that either 1 or 3 or 4 will come; subtractig this umber from the precedig, oe has the combiatios where 1 will be foud without 3 or 4, therefore a iv a a iv epresses the probability that 1 will come without 3 or 4; fially a a iv epresses the probability that either or 3 or 4 will come, that is to say it gives the combiatios where, 3 & 4 will be watig; a a a iv epresses the probability that either 1 or or 3 or 4 will come. Subtractig this umber from the precedig, oe will have the combiatios where 1 comes without, 3 or 4; therefore epresses the probability a a iv a a a iv that 1 will come without, 3 or 4. Subtractig this probability from that which 1 will come without 3 or 4, oe will have the probability that 1 will come with without 3 or 3

4 4 = a a iv a a a iv. a a a iv a a a a iv Subtractig this probability from that which 1 will come with without 4, oe will have the probability that 1 will come with & 3 without 4 = a iv a a iv a a iv a a iv a a a iv a a a iv a a a iv a a a a iv Subtractig this probability from that which 1 will come with & 3 with or without 4, oe will have the probability that 1,, 3 & 4 will come together = a a a a a a iv a a a a iv 1 a a a a a a iv a a a iv a a a iv a iv a a a a a iv a a iv a a iv Mr. de Moivre is arrived to the same results i his Doctrie of chaces. The aalogy is ow evidet, & oe sees that if oe calls A the sum of the terms which oe obtais by subtractig from the combiatios of a, a, &c. a oe by oe, A the sum of the terms which oe obtais by subtractig from the sum of the combiatios of the same quatities take two by two, A the sum of the terms which oe obtais by subtractig from the sum of the combiatios of the same quatities take three by three, & i geeral A the sum of the combiatios of the 4

5 same quatities take by, oe will have for the probability that 1,, 3,... will have eited at the ed of coups 1 A A A A iv &c. ± A.. If oe makes ow a = a = a = a = 1, the precedig formulas will give us the solutio of the problem that Mr. Euler treats i first place & that Mr. de la lace has treated i T. 6. of the Mémoires des Savas étrages preseted to the Academy of Scieces of aris. 4 Oe has i this case here, by virtue of the first priciples of the doctrie of combiatios, the probability that all the umbers of the lottery will have eited at the ed of coups = &c.± It is ecessary ow to substitute ito this formula for 1, &c. their values. Now 1 epresses the probability that i coups a umber for eample o will ot eit; as oe draws p tickets at each coup, the umber of all possible cases results from the combiatio of thigs take p by p, of which the result must be raised to. 1 p p This umber is therefore by the doctrie of combiatios = & the umber of cases where 1 is ot foud, results from the combiatio of 1 thigs take p by p. This umber will be by the same rule = 1 p p Therefore by the geeral rule of probabilities, the probability that i coups the umber 1 will ot eit will be = 1 p 1 p1 = p. Likewise epresses the probability that i coups, two umbers, for eample 1 &, will ot eit; ow the umber of possible cases beig always the same, the umber of cases where 1 & will ot be foud, results from the combiatio of thigs take p by p, this umber is therefore = 3 p1, p therefore the sought probability will be = 3 p 1 p p 1 =. 1 p 1 1 Net 3 epresses the probability that the three umbers 1,, 3 will ot eit; ow the umber of cases where 1,, & 3 are ot foud, results from the combiatio, of 3 thigs take p by p amely therefore the sought probability will be = 3 4 p = 1 p 1 34 p p Oe will fid likewise p 3 = = 1 p 1 p p 1 p. 1 p p Mémoire sur les suites récurro-récurretes et sur leurs usages das la théorie des hasards, Mém. Acad. R. Sci. aris Savats étragers 6, 1774, pages

6 The law is ow rather clear. Substitutig therefore these values, our formula will become 1 p 1 3 p p 1 1 p p &c..3 1 p 1 This is the formula that Mr. de la lace fids. Accordig to that which we just saw, oe ca set it uder the followig form which is much simpler. p 1 p p p p 1 p p p 1 p p 3 &c For that which regards the arithmetic calculatio of these formulas, oe will cosider that A p 1 =, A 1 p 1 A =, 1 A p A =, 3 A iv 3 p 3 = A 4 3 & i geeral Therefore A λ λ = A λ1 λ 1 p λ. λ l A = l l p, l A = l A l 1 l p1 1, l A = l A l 3 l p &c. l A λ = l A λ1 l l λ λ1 pλ λ Let as i the lottery of Berli = 90, p = 5, & make = 100, we will have A = , A = , A = , A iv = , therefore 1 A A A A iv &c. = Make = 00, we will have A = , 1 A = There are therefore early odds of three agaist oe that all the umbers will have eited at the ed of

7 drawigs, & early odds of oe thousad agaist oe that all the umbers will have eited at the ed of 00 drawigs, as Mr. Euler fids it. If oe would wish to kow what is the umber of coups where oe ca wager eve that all the umbers will have eited, oe would fid this umber betwee 85 ad 86, so that there is advatage to wager that all the umbers will have eited at the ed of 86 drawigs, & disadvatage to wager that all the umbers will have eited at the ed of 85 drawigs. The eact umber is earer 85 tha Supposig the same thigs as i 1. oe demads the probability that at the ed of coups oe will have brought forth at least 1 kids of faces. Reasoig always i the same maer, I say: a is the probability that i drawigs either 1 or will come, therefore 1 a epresses the probability that of the two umbers there will eit at least oe, a a a epresses the probability that will come without 1 or 3, a a a epresses the probability that 1 will come without or 3. Subtractig these two probabilities from the first, oe will see that 1 a a a a a a a a a epresses the probability that of the three umbers there will eit at least two of them, sice 1 & must ecessarily eit together or separately, & sice 1 must come with & 3 together or separately, & with 1 & 3 together or separately. Oe fids likewise that a iv a a iv epresses the probability that 3 will come without or 4; that a iv a a iv epresses the probability that will come without 1 or 4; that a iv a a iv epresses the probability that 1 will come without 3 or 4. Oe fids agai that a a iv a a a iv epresses the probability that 3 will come without 1 or or 4; that a a iv a a a iv epresses the probability that will come without 1, 3 or 4; that a a iv a a a iv epresses the probability that 1 will come without, 3 or 4. Therefore by subtractig these probabilities two by two, oe will have the followig epressios: a a iv a a a iv a a a iv a a a a iv = 7

8 the probability that will come with 3 without 1 or 4; a a iv a a a iv a a a iv a a a a iv = the probability that 3 will come with 1 without or 4; a a iv a a a iv a a a iv a a a a iv = the probability that 1 will come with without 3 or 4. Ideed, if the probability that will come without 1 or 4 with or without 3, oe takes off the probability that 3 will come without 1, or 4, there remais the probability that will come with 3 without 1 or 4, & it is the first of our three ew formulas. The two others are obtaied precisely i the same maer. If oe subtracts ow these three formulas from the first which epresses the probability that at least two of the three umbers 1,, 3 will eit, it is easy to see that which remais. These three umbers furish three combiatios two by two 1, ; 1, 3;, 3. Now 1, ca ot come without 3 or 4, by virtue of subtractig it from the third formula; 1, 3 ca ot come without or 4, by subtractig it from the secod;, 3 ca ot come without 1 or 4, by subtractig it from the first. Therefore the formula a a a a a a a a a iv 1 3 a a a a a iv a a iv a a a iv a a a a a iv a a iv a a iv epresses the probability, that of the umbers 1,, 3, 4 there will eit at least three of them. These four umbers take three by three form the followig four combiatios, 1,, 3; 1,, 4;, 3, 4. It is ecessary to seek the probability that each of these combiatios will come without the two other umbers, for eample that 1,, 3 will come without 4 & 5, & subtractig these four probabilities from the probability that we just 8

9 foud, oe will have the probability that of the umbers 1,, 3, 4, 5 there will eit at least four of them, sice there must eit at least three of the first four, & sice ay of the combiatios three by three of these first four ca ot come without brigig forth at least oe of the two other umbers. Now, i order to fid the probability that 1,, 3 will come without 4 & 5, it is ecessary to seek the probability that 1, will come without 4 or 5 with or without 3, & by subtractig the probability that 1, will come without 3, 4 or 5. Now the probability that 1, will come without 4 & 5 is by that which precedes, a iv a v a a iv a v a a iv a v a a a iv a v. I order to have the probability that 1, will come without 3, 4 or 5, it is ecessary to seek the probability that 1 will come without 3, 4 or 5 with or without, & by subtractig the probability that 1 will come without, 3, 4 or 5. Now the probability that 1 will come without 3, 4 or 5 is by that which precedes a iv a v, & the probability that 1 will come without, 3, 4 or 5 is 5 is a a iv a v a a a iv a v. Therefore the probability that 1, will come without 3, 4 or a a iv a v a a a iv a v a a a iv a v a a a a iv a v & the probability that 1,, 3 will come without 4 or 5, is = a a iv a v a iv a v a a iv a v a a a iv a v a a a a iv a v a a iv a v a a a iv a v a a iv a v a a a iv a v Oe will have likewise the probability that 1,, 4 will come without 3 or 5 = a a v a a a v a a a a v a a a a iv a v a a a v a a a iv a v a a iv a v a a a iv a v 9

10 Oe will have likewise the probability that 1, 3, 4 will come without or 5 = a a v a a a v a a a a v a a a a iv a v a a a v a a a iv a v a a iv a v a a a iv a v Oe will have likewise the probability that, 3, 4 will come without 1 or 5 = a a v a a a v a a a a v a a a a iv a v a a a v a a a iv a v a a iv a v a a a iv a v The sum of these four probabilities will be therefore a a v a a a 4 a a a a v a a a a iv a v 3 4 a a v a a a v a a a iv a v 3 a a v a a iv a v a a a iv a v 3 3 a iv a v a a iv a v a a a iv a v 3 a a iv a v 10

11 & by subtractig it from the precedig formula, oe will have the formula, 1 a a a 3 a a a iv 4 a a a iv a v a a a iv 3 a a a v a iv a a v 3 a a iv a v a v a a iv 3 a a iv a v a a a v a iv a iv a v a v a a iv a iv a a v a v a iv a v iv a v a iv a v which epresses the probability that of the umbers 1,, 3, 4, 5 there will eit at least four of them. The aalogy is ow evidet, & oe sees that by coservig the deomiatios of 1 oe will have for the probability that i coups oe will have brought forth at least 1 kids of faces = 1 A A 3A iv 4A v 5A vi 6A vii &c. 4. If a = b = c = d =&c.= 1 oe will have by the theory of combiatios, 5 the probability that out of umbers oe will have brought forth at least 1 of them i coups= p &c , & by settig for 3, 4 p &c. the values foud. oe will have this probability = 1 p p p p 1 p p p &c. 5 Traslator s ote: a = a, b = a, c = a, d = a iv,... Trembley repeatedly uses this alterate otatio. 11

12 This is that which Mr. Euler fids. 5. Supposig always the same thigs as i 1. oe demads the probability that at the ed of coups oe has brought forth at least faces. I reaso always i the same maer, & I say: a a is the probability that there will come either 1 or or 3 i drawigs, therefore 1 a a epresses the probability that of the umbers 1,, 3 there will eit at least oe of them. I order to have the probability that of the umbers 1,, 3, 4 there will eit at least two of them, it is ecessary to subtract from the precedig probability the probability that oe of the umbers 1,, 3 comes without oe of the three others. Now the probability that 1 will come without, 3 or 4 is by that which precedes a a iv 1, 3 or 4 is without 1,, or 4 is a a iv a a a v a a iv ; the probability that will come without a a a iv ; the probability that 3 will come a a a iv. Therefore a a a a a a a iv 1 3 a a a iv a a a iv a a a iv epresses the probability that of the umbers 1,, 3, 4 there will eit at least of them. I order to have the probability that of the umbers 1,, 3, 4, 5 there will eit at least three of them, it is ecessary to subtract from the precedig probability the probability that each of the si combiatios two by two of the umbers 1,, 3, 4 will come without the three other umbers. Now by that which precedes, the probability that 1, will come without 3, 4 or 5 is a a iv a v a a a iv a v a a a iv a v a a a a iv a v. The probability that 1, 3 will come without, 4 or 5 will be a a iv a v a a a iv a v a a a iv a v a a a a iv a v. 1

13 The probability that 1, 4 will come without, 3 or 5 will be a a a v a a a a v a a a iv a v a a a a iv a v. The probability that, 3 will come without 1, 4 or 5 will be a a iv a v a a a iv a v a a a iv a v a a a a iv a v. The probability that, 4 will come without 1, 3 or 5 will be a a a v a a a a iv a a a iv a v a a a a iv a v. The probability that 3, 4 will come without 1, or 5 will be a a a v a a a a v a a a iv a v a a a a iv a v. Oe will have therefore by subtractig these si probabilities from the precedig, 6 1 a a 3 a a a iv a a a iv a v 3 a a iv a a v a a iv a a v a iv a v a a iv 3 3 a a v a iv a v a iv a v a a a v a a iv a v a a iv a v 13

14 this is the probability that out of the umbers 1,, 3, 4, 5 there will eit at least three of them. I order to have the probability that of the umbers 1,, 3, 4, 5, 6 there will eit at least four of them, it is ecessary to subtract from the precedig probability the probability that each of the te combiatios three-by-three of the umbers of the first five umbers will come without the three other umbers. Now these probabilities result easily from the precedig calculatios; here is a eample of it for the probability that 1,, 3 will come without 4, 5, 6. The probability that 1, will come without 4, 5, 6 is foud by that which precedes = a iv a v a vi a a iv a v a vi a a iv a v a vi a a a iv a v a vi. The probability that 1, will come without 3, 4, 5, 6 is = a a iv a v a vi a a a iv a v a vi a a a iv a v a vi a a a a iv a v a vi. Therefore subtractig the secod formula from the first, the probability that 1,, 3 will come without 4, 5, 6 is = a iv a v a vi a a iv a v a vi I. a a a iv a v a vi a a a a iv a v a vi a a iv a v a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi Oe will have likewise the probability that 1,, 4 will come without 3, 5 & 6 by echagig i the precedig c ito d & d ito c, a a v a vi a a a v a vi II. a a a a v a vi a a a a iv a v a vi a a a v a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi 14

15 Oe will have the probability that 1,, 5 will come without 3, 4, & 6 by echagig i the precedig d ito e & e ito d, III. a a iv a vi a a a iv a vi a a a a iv a vi a a a a iv a v a vi a a a iv a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi Oe will have the probability that 1, 3, 4 will come without, 5, 6 by echagig i the secod b ito c & c ito b, IV. a a v a vi a a a v a vi a a a a v a vi a a a a iv a v a vi a a a v a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi Oe will have the probability that 1, 3, 5 will come without, 4, 6 by echagig i the precedig d ito e & e ito d, V. a a iv a vi a a a iv a vi a a a a iv a vi a a a a iv a v a vi a a a iv a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi Oe will have the probability that 1, 4, 5 will come without, 3, 6 by echagig 15

16 i the precedig c ito d & d ito c, VI. a a a vi a a a a vi a a a a iv a vi a a a a iv a v a vi a a a iv a vi a a a a v a vi a a a v a vi a a a iv a v a vi Oe will have the probability that, 3, 4 will come without 1, 5, 6 by echagig i formula II a ito c & c ito a, VII. a a v a vi a a a v a vi a a a a v a vi a a a a iv a v a vi a a a v a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi Oe will have the probability that, 3, 5 will come without 1, 4, 6 by echagig i the precedig formula d ito e & e ito d, VIII. a a iv a vi a a a iv a vi a a a a iv a vi a a a a iv a v a vi a a a iv a vi a a a iv a v a vi a a iv a v a vi a a a iv a v a vi Oe will have the probability that, 4, 5 will come without 1, 3, 6 by echagig 16

17 i the precedig formula c ito d & d ito c, IX. a a a vi a a a a vi a a a a iv a vi a a a a iv a v a vi a a a iv a vi a a a a v a vi a a a v a vi a a a iv a v a vi Oe will have the probability that 3, 4, 5 will come without 1,, 6 by echagig i the precedig formula b ito c & c ito b, X. a a a vi a a a a vi a a a a iv a vi a a a a iv a v a vi a a a iv a vi a a a a v a vi a a a v a vi a a a iv a v a vi Subtractig these te formulas from the precedig, oe will have the probability that out of the umbers 1,, 3, 4, 5, 6 there will eit at least four of them, = 17

18 1 3 a a a a a iv a a iv a v a vi 6 a a a iv a v 10 a a iv 3 a a a v 6 a a a iv a vi a a v 3 a a a vi 6 a a a v a vi a a vi 3 a a iv a v 6 a a iv a v a vi a a iv 3 a a iv a vi 6 a a iv a v a vi a a v 3 a a v a vi 6 a a iv a v a vi a a vi 3 a a iv a v a iv a v 3 a a iv a vi a iv a vi 3 a a v a vi a v a vi 3 a iv a v a vi a a iv 3 a a iv a v a a v 3 a a iv a vi a a vi 3 a a v a vi a a vi 3 a a v a vi a iv a v 3 a iv a v a vi a iv a vi 3 a iv a v a vi a v a vi a iv a v a iv a vi a v a vi iv a v a vi. The aalogy is ow evidet, & oe sees that by coservig the same deomiatios as above, oe will have for the probability that out of faces oe will brig forth at least 3 of them, 1 A 3A iv 6A v 10 vi &c. 6. If a = a = a = a iv &c. = a = 1, oe will have by the theory of combiatios, &c

19 for the probability sought, & by puttig for 3 foud above, oe will have this probability, = 1 p p p p 4 &c This is the result that Mr. Euler fids., 4, 5 &c. the values p p Supposig always the same thigs, we demad the probability that at the ed of coups oe will have brought forth at least 3 faces. I cotiue to reaso likewise, & I say: a a a iv is the probability that there will come either 1 or or 3 or 4 i coups, therefore 1 a a a iv epresses the probability that of the umbers, 1,, 3, 4 there will eit at least oe of them. I order to have the probability that of the umbers 1,, 3, 4, 5 there will eit at least two of them, it is ecessary to subtract from the precedig probability the probability that oe of the umbers 1,, 3, 4 will come without the four others. Now a a a iv a v a a a a iv a v = the probability that 1 will come without, 3, 4, 5. a a a iv a v a a a a iv a v = the probability that will come without 1, 3, 4, 5. a a a iv a v a a a a iv a v = the probability that 3 will come without 1,, 4, 5. a a a a v a a a a iv a v = the probability that 4 will come without 1,, 3, 5. Therefore 1 a a a iv 4 a a a v a a iv a v a a iv a v a a iv a v = a a a iv a v 19

20 the probability that of the umbers 1,, 3, 4, 5 there will eit at least two of them. Oe will fid by cotiuig the operatio, & coservig always the same deomiatios, that 1 A iv 4A v 10A vi 0A vii 35A viii &c. epresses the probability that out of umbers there will eit at least 3 of them. 8. The aalogy is ow evidet, the umeric coefficiets beig the figurate umbers, & oe will have the followig formula, which is geeral: 1A λ λ 1A λ1 λ 1λ A λ 1. λ 1λ λ 3 A λ3 λ 1 λ 4 A λ λ 1 λ 5 A λ5 &c. = the probability that of umbers there will eit at least λ of them. 9. If ow we make a = a = a = a iv &c. = 1, we will have A = 1, 1 A 1 =, 1. A 1 3 =, 1..3 A iv 3 4 = A λ λ 1 λ = λ Oe will have therefore by substitutig these values, λ 1 λ λ λ 1 1 λ λ λ 1 λ 1λ λ 1 λ λ λ 1 λ 3 λ λ λ 3 λ 1 λ 4 λ 3 λ 4 &c. = λ 4 0

21 λ λ λ 1 λ λ 1 λ 1λ 1. λ 1λ λ λ 1 λ p p λ 1... λ 1 p p λ... λ λ 1 p p λ λ... λ 1 λ p p λ 1... λ 3... λ λ 3 p p λ 3 &c λ 4... λ 3 Mr. Euler fids a aalogous formula. Oe sees that the direct use of the doctrie of combiatios has led us quite simply to the solutio of the geeral problem of which the oe of Mr. Euler is oly a particular case, sice a, a, a... a which i the problem of Mr. Euler are = 1 ca be aythig i ours. The geeral problem would have place i a lottery where there would be a tickets marked 1, b marked, c marked 3 &c. & where oe would demad the probability that there would have eited a certai umber of kids of them. Oe will fid always the value of the epressios, a &c. by way of the followig formula which epresses the probability that by takig t thigs out of, of which u are of a certai kid, there will be foud m of this kid of them. This formula is, as oe kows, t t 1 t u m 1tt 1 t m 1 uu 1 u m 1 1 u m 10. It is evidet by the same ature of thigs, that i problem 1, if the umber of drawigs is smaller tha p, it will be impossible that all the umbers have eited at the ed of a umber of drawigs; thus i all the cases where < p, the foud probability must be = 0, & the miimum of where the probability is ot ull, has place whe = p or = p. Mr. Euler remarks that i this case the sum of the series which gives the probability, ca be epressed by some products. This ca be demostrated by the itegral calculus, by the followig method which is quite simple. 11. The series that the questio is to sum is i this case here p p pp 1 p pp p 1 1p p 1. pp 1 pp 1p p p p p 1..3 p... p p p 3 p p p p 3 &c p... p 3 I see first that if = 1, all the series = 1, because all the terms vaish with the eceptio of the first. 1

22 If =, oe has the series p pp 1 pp 1 1p p 1. pp 1 pp 1p pp 1p 1..3 pp 1p pp 1p p = 1 p p 1 1. pp 1p p 3 pp 1p p 3 p p 1 pp 1 1 p p 1 p 1..3 pp 1p 1 p p 1 p p pp 1p p 3 &c. &c. I order to fid the sum of this series, I form the summatory sequece of that there, & I have by makig successively p = 1,, 3, 4 &c. the sequece &c. The geeral term of this sequece, that is to say the sum of the sought series whe p =, is therefore p1p p. If = 3, oe has the series, 1 p3 3p 1 1. p 3 p 1 3 3p 3p 1 1 p 3 p 1 3 p p 3p 1 3p 1 p 3 p 1 3 p 3 p p 3p 1 3p 3p 3 &c. Make successively p = 1,, 3, 4 & we will have the summatory series, of which the geeral term is evidetly If = 4, oe has the series, 1 3p4 4p &c p p1p 3p. 3p 4 3p 1 4 4p 3 4p p 4 3p 1 4 3p p 3 4p 1 3 4p 3 1 3p 4 3p 1 4 3p 4 3p p 3 4p 1 3 4p 3 4p 3 3 &c. Make successively p = 1,, 3, 4 & we will have the summatory sequece, &c.

23 p of which the geeral term is evidetly 3p13p 4p. The aalogy is ow evidet, & oe sees that the proposed series will be 3 = by makig p = p 1p 1 1p p 1 = p 1 p 1 1 = p 1 p 1 = p Oe ca demostrate also that the sum of our series is = 0 i the case where > p. Let = p 1, the series will become p p 1 1p 1 pp 1 1p 1 p p 1p 1 1p 1p 1..3 If = 1, this series becomes 1 p pp 1 1. If =, this series becomes p p 1p 1p pp 1p 1..3 &c. &c. = 1 1 p = 0. 1 p 3p 1 p p 1 1 p p 1 p 1. 3p3p p3p 13p 1 p p 1 p p 3 &c p3p 13p 3p 3 = 1 p p pp 1 p p 1 1 3p 1. 3p 3p 1 pp 1p 1..3 p p 1 3p 3p 1 p 3p &c. If oe forms the summatory sequece of this series by makig p = 1,, 3, 4, &c. oe will have each term = 0, the geeral term of the series is therefore = 0, & the sum sought = 0. If = 3, this series becomes 1 3p 1 3p 3p3p 1 4p 1. 3p3p 13p p 4p 3p 3p 1 4p 4p 1 3 3p 1 4p 1 3p 4p &c..

24 which oe will fid i the same maer = 0. If = 4, this series becomes 1 4p 3 4p 4p4p 1 1 5p 1. 4p4p 14p p 5p 4p 4p 1 5p 5p 1 3 4p 1 5p 1 4p 5p which oe will fid likewise = 0. Therefore the series itself which oe ca put uder this form 1 p 1 p pp 1 p 1 1p 1. 1p pp 1p p p p 1p 1 3 &c.. p 1 1p 1 p 1p is = 0. Let ow = p, & oe will prove likewise that the series p 1 1p p p p 1 1. = 1 1p 1p p 1 1p 1p 1 1. p 1 p 1p p 1p 1p 1 p 1..3 p 1 1 &c. p p 1 1 p 1 1 &c. p p 1 1p 1p 1 p p 1 1 &c.. 1p &c.. p = 0. Therefore fially if = p m, m beig ay whole umber, oe will fid i the same maer that the series m 1p 1 1 m 1p mp 1 m 1p m 1p 1 1. m 1p mp m 1p m 1p 1 m 1p 1..3 m 1p m 1p mp m 1p 1 mp 1 mp 1 m 1p 1 &c. mp 1 &c. = If & are very great umbers, & p a small umber, the calculatio would become impractical by its legth, but the aalysis furishes i this case the way to 4

25 abbreviatio. Oe will have uder this assumptio, p = 1 p p = 1 p p &c. = e & likewise p 1 = e p 1 1 p λ λ = e p λ. We will have therefore for the probability that all the umbers have eited, 1 p 1 1 e e p 1 p 1. 1 e p p 1 p e p 3 p p 1 p = 1e p = e e p p e = e q.3 e &c., 3p 4 4p e &c. by makig for brevity q = e p. If oe wishes to push the approimatio further, oe will have 1 p p = 1 p 3.3 p p4 4 &c. p p 1 p 3.3 p3 3 &c. = e p Oe will have likewise 1 p 1 1 p 1 p λ = e p 1 1 = e p 1 1 = e p λ 1 p 1 p 1 p λ 1 p,,.. 5

26 We will have therefore for the probability that all the umbers have eited, 1e p 1 p 1 1 p 1. p 1 1 e p p 1 e p e p e p 1 e p p 1 = 1e p = 1e p p 1 1 e p e p 1 e p e p 3 p 1 1 p 1 e 3p p e 3 3p 1..3 e p e =by makig e p = q 1 p 1 p p e 1 p p e 4p p e 1 e p e q 1 p q 1 p e q e p q q 1 p e q e p q q 1 p p p 1 e p 3 1 p 1 p 4p 1 p 4 &c. 1 p 1 p 3 p.3 e 1 p p 3 &c. 4 &c. 3 &c. e q 1 p = e q e p q = e q e p q. 6

27 Now e p q = 1 p q &c. Therefore the sought probability will be e q 1 p q q e q = e q 1 p q q If oe cosiders this process with attetio, oe will see that oe ca put 1 1 i place of 1, &c. without committig a error greater tha that of the terms where q 3 eters. It is ecessary to ecept the terms e p 1, e p &c. Oe has 1 1 = 1 1 1, = 1 1,... λ = 1 λ. We will have therefore e p 1 = e p e p, e p = e p e p, e p 3 = e p e 3p,... e p λ = e p e λp. Therefore takig the precedig formulas, & applyig these correctios to the first part of the formula aloe, it will become Now 1e p 3.3 e e 1 p 3p 3p 1 p e 3 4p 6p 1 p e p e 3p e 6p =1 p, =1 3p, p p 1 p 4 &c. =1 6p &c. whece it follows that it is ecessary to add to the foud formula, p p e p p e p q e q. 3 3p 3p.3 e 4 1 e p e 4p.3.4 e 6p &c. = p 3 3p.3 e &c. = Thus the probability sought will be e q 1 p q p q. 7

28 If oe makes p = 1, oe will have e q 1 q q. It is that which Mr. de la lace fids i the Mémoires de l Académie des Scieces de aris for by a very profoud aalysis, draw from the itegral calculus i fiite differeces. It is remarkable that oe ca arrive to the same coclusios without itegral calculus & by some quite simple cosideratios. 15. Let for eample, as Mr. de la lace supposes it = 10000, p = 1, & let oe demad the umber of coups at the ed of which oe ca wager eve that all the umbers will have eited. We will have i this case to resolve the equatio e q 1 q q = 1. Now 7 q = e, therefore = l q, = l q. For first approimatio I make e q = 1 l, therefore q = l, q = = = , l q = , l q = Multiplyig this quatity by.30585, oe will have l q = Therefore = l q = first value. I substitute ow these values of & q ito the formula 1 q q & I have l q = l q = l = l = l q = l q = l = q = l q = q = q = q q = Therefore 1 q q = Therefore e q 1 = , q = l = , l q = Multiplyig this quatity by , oe will have l q = Therefore = l q = The sought umber is therefore a little earer to tha to Mr. de la lace arrives to the same coclusio at the ed of his Memoir. Oe sees et that i this case 6 Suite du mémoire sur les approimatios des Formules qui sot foctios de très-grads ombres, Mém. Acad. R. Sci. aris , p Traslator s ote: Where Trembley writes log. hyp., I have writte l. 8

29 the first operatio sufficed, so that the correctio was superfluous, this which cofirms the goodess of the method. 16. Oe ca fid likewise a approimatio for the secod of the formulas foud above, whe & are very great umbers. The probability that at the ed of drawigs there will have eited at least 1 umbers is p p p p p 1 1 p 1 1 p p p 3 3 by beig cotet with a first approimatio & makig q = e p 1 q q q4 &c. by makig q = e p. Let q = oe will have the sought probability Therefore S = &c. &c. = ds d = &c. = &c. = e. Therefore ds = d e, S =e e C. Whe = 0, oe has S = 1, therefore C = 0. Therefore S = e 1 = e q 1 q. Thus istead as i the precedig case it was ecessary for first approimatio to resolve the equatio e q = 1, it will be ecessary to resolve the equatio eq 1 q = 1. I order to come to ed, I suppose first e q = 1, whece I draw as above q = Therefore l q = l = l q = q = q =

30 Oe has ow e q = , q = l = l = l = l q = l = = l q = q = , q = , 1 q = , e q = , q = l l = l = l q = = q = Therefore q = , 1 q =.49054, e q = , q = l l = l = l q = = q = Therefore q = , 1 q =.60565, e q = , q = l l = l = l q = = q = Therefore q = , 1 q = , e q = , q = l l = l = l q = q = =

31 Therefore q = , 1 q = , e q = , q = l l = l = l q = = q = Therefore q = 1.67, 1 q =.67, e q = 1.67, q = l5.344 l = l = l q = = q = Therefore q = 1.676, 1 q =.676, e q = 1.676, q = l5.35 l = l = l q = = q = Therefore q = , 1 q =.67747, e q = , q = l l = l = l q = = q = , l q = l = l = l q = = l q =

32 Oe would have bee able to fid the limit much more rapidly by supposig q a little too great, but I have preferred to give the direct approimatio without makig ay error. 17. Oe will fid likewise for the probability that at least umbers will have eited, q q q5 &c. = by makig q = Therefore &c. = S ds = d &c. = 1 = e ds = d e, S = e d e = 1 e &c. =e q 1 q 1 q = 1. Fially to shorte the gropigs, as q must be greater tha i the precedig case, I make q = 0.001, & I have q = 10, q = 50, 1 q q = 61, e q = 1 1, q = l 1 = , l = l = l q = q = I make q = & I have q = 4, q = 8, 1 q q = 13, e q = l 6, q = = l = l = l q = q =

33 I make q = & I have q =, q =, 1 q q = 5, e q = 1 l 10 10, q = = I make q = & I have q =.6, q = 3.38, 1q q = 6.98, e q = 1 l , q = = l = l = l q = q = Oe approaches thus quite ear to the value of q, but the approimatio is less eact, because it is already raised to above the value of Oe would fid likewise for the probability that there will have eited at least 3 umbers 3 S =.3 1 e by makig = q, & i geeral for the probability that there will have eited at least λ umbers λ S = 1... λ λ λ 1 1 e but ca ot be eact as log as q is of order 1. There would be may cosideratios to make o the later approimatios, but I myself could ot deliver the detail which they require without legtheig this memoir too much. 33

Analytic Theory of Probabilities

Analytic Theory of Probabilities Aalytic Theory of Probabilities PS Laplace Book II Chapter II, 4 pp 94 03 4 A lottery beig composed of umbered tickets of which r exit at each drawig, oe requires the probability that after i drawigs all

More information

MEMOIR ON THE UTILITY OF THE METHOD OF TAKING THE MEAN AMONG

MEMOIR ON THE UTILITY OF THE METHOD OF TAKING THE MEAN AMONG MEMOIR ON THE UTILITY OF THE METHOD OF TAKING THE MEAN AMONG THE RESULTS OF SEVERAL OBSERVATIONS IN WHICH ONE EXAMINES THE ADVANTAGE OF THIS METHOD BY THE CALCULUS OF PROBABILITIES AND WHERE ONE SOLVES

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

Topic 1 2: Sequences and Series. A sequence is an ordered list of numbers, e.g. 1, 2, 4, 8, 16, or

Topic 1 2: Sequences and Series. A sequence is an ordered list of numbers, e.g. 1, 2, 4, 8, 16, or Topic : Sequeces ad Series A sequece is a ordered list of umbers, e.g.,,, 8, 6, or,,,.... A series is a sum of the terms of a sequece, e.g. + + + 8 + 6 + or... Sigma Notatio b The otatio f ( k) is shorthad

More information

SEQUENCE AND SERIES NCERT

SEQUENCE AND SERIES NCERT 9. Overview By a sequece, we mea a arragemet of umbers i a defiite order accordig to some rule. We deote the terms of a sequece by a, a,..., etc., the subscript deotes the positio of the term. I view of

More information

Chapter 6 Overview: Sequences and Numerical Series. For the purposes of AP, this topic is broken into four basic subtopics:

Chapter 6 Overview: Sequences and Numerical Series. For the purposes of AP, this topic is broken into four basic subtopics: Chapter 6 Overview: Sequeces ad Numerical Series I most texts, the topic of sequeces ad series appears, at first, to be a side topic. There are almost o derivatives or itegrals (which is what most studets

More information

In algebra one spends much time finding common denominators and thus simplifying rational expressions. For example:

In algebra one spends much time finding common denominators and thus simplifying rational expressions. For example: 74 The Method of Partial Fractios I algebra oe speds much time fidig commo deomiators ad thus simplifyig ratioal epressios For eample: + + + 6 5 + = + = = + + + + + ( )( ) 5 It may the seem odd to be watig

More information

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series

Comparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series

More information

A LIMITED ARITHMETIC ON SIMPLE CONTINUED FRACTIONS - II 1. INTRODUCTION

A LIMITED ARITHMETIC ON SIMPLE CONTINUED FRACTIONS - II 1. INTRODUCTION A LIMITED ARITHMETIC ON SIMPLE CONTINUED FRACTIONS - II C. T. LONG J. H. JORDAN* Washigto State Uiversity, Pullma, Washigto 1. INTRODUCTION I the first paper [2 ] i this series, we developed certai properties

More information

Z ß cos x + si x R du We start with the substitutio u = si(x), so du = cos(x). The itegral becomes but +u we should chage the limits to go with the ew

Z ß cos x + si x R du We start with the substitutio u = si(x), so du = cos(x). The itegral becomes but +u we should chage the limits to go with the ew Problem ( poits) Evaluate the itegrals Z p x 9 x We ca draw a right triagle labeled this way x p x 9 From this we ca read off x = sec, so = sec ta, ad p x 9 = R ta. Puttig those pieces ito the itegralrwe

More information

Chapter 7: Numerical Series

Chapter 7: Numerical Series Chapter 7: Numerical Series Chapter 7 Overview: Sequeces ad Numerical Series I most texts, the topic of sequeces ad series appears, at first, to be a side topic. There are almost o derivatives or itegrals

More information

4.3 Growth Rates of Solutions to Recurrences

4.3 Growth Rates of Solutions to Recurrences 4.3. GROWTH RATES OF SOLUTIONS TO RECURRENCES 81 4.3 Growth Rates of Solutios to Recurreces 4.3.1 Divide ad Coquer Algorithms Oe of the most basic ad powerful algorithmic techiques is divide ad coquer.

More information

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT TR/46 OCTOBER 974 THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION by A. TALBOT .. Itroductio. A problem i approximatio theory o which I have recetly worked [] required for its solutio a proof that the

More information

RECHERCHES sur la mortalité de la petite vérole

RECHERCHES sur la mortalité de la petite vérole RECHERCHES sur la mortalité de la petite vérole Jea Trembley Mémoires de l Académie Royale des Scieces et Belles-Lettres... Berli 796 799) Class de math. pp. 7 38. Oe of the objects of political arithmetic

More information

PROBABILITÉ. Condorcet

PROBABILITÉ. Condorcet PROBABILITÉ Codorcet Ecyclopédie Méthodique. Mathématiques. Tome II e, Partie (1785) PROBABILITÉ. We will limit ourselves to give here the geeral priciples of the calculus of probabilities, of which oe

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information

Math 475, Problem Set #12: Answers

Math 475, Problem Set #12: Answers Math 475, Problem Set #12: Aswers A. Chapter 8, problem 12, parts (b) ad (d). (b) S # (, 2) = 2 2, sice, from amog the 2 ways of puttig elemets ito 2 distiguishable boxes, exactly 2 of them result i oe

More information

Leonhard Euler. 1 After I had exhibited 1 the sums of the series contained in this general form

Leonhard Euler. 1 After I had exhibited 1 the sums of the series contained in this general form Aother Dissertatio o the sums of the series of reciprocals arisig from the powers of the atural umbers, i which the same summatios are derived from a completely differet source * Leohard Euler 1 After

More information

~j=zhax~ 6=0, t,2... ), k=~

~j=zhax~ 6=0, t,2... ), k=~ Numerische Mathematik 6, 35 -- 39 (964) Exactess Coditios i Numerical Quadrature* By HERBERT S. WILl* The itegral b () I--f t(x)dx is usually computed umerically by meas of a formula of the type (2) I

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES 9 SEQUENCES AND SERIES INTRODUCTION Sequeces have may importat applicatios i several spheres of huma activities Whe a collectio of objects is arraged i a defiite order such that it has a idetified first

More information

Matrices and vectors

Matrices and vectors Oe Matrices ad vectors This book takes for grated that readers have some previous kowledge of the calculus of real fuctios of oe real variable It would be helpful to also have some kowledge of liear algebra

More information

Chapter 6: Numerical Series

Chapter 6: Numerical Series Chapter 6: Numerical Series 327 Chapter 6 Overview: Sequeces ad Numerical Series I most texts, the topic of sequeces ad series appears, at first, to be a side topic. There are almost o derivatives or itegrals

More information

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3 MATH 337 Sequeces Dr. Neal, WKU Let X be a metric space with distace fuctio d. We shall defie the geeral cocept of sequece ad limit i a metric space, the apply the results i particular to some special

More information

Number of fatalities X Sunday 4 Monday 6 Tuesday 2 Wednesday 0 Thursday 3 Friday 5 Saturday 8 Total 28. Day

Number of fatalities X Sunday 4 Monday 6 Tuesday 2 Wednesday 0 Thursday 3 Friday 5 Saturday 8 Total 28. Day LECTURE # 8 Mea Deviatio, Stadard Deviatio ad Variace & Coefficiet of variatio Mea Deviatio Stadard Deviatio ad Variace Coefficiet of variatio First, we will discuss it for the case of raw data, ad the

More information

SOME TRIBONACCI IDENTITIES

SOME TRIBONACCI IDENTITIES Mathematics Today Vol.7(Dec-011) 1-9 ISSN 0976-38 Abstract: SOME TRIBONACCI IDENTITIES Shah Devbhadra V. Sir P.T.Sarvajaik College of Sciece, Athwalies, Surat 395001. e-mail : drdvshah@yahoo.com The sequece

More information

DS 100: Principles and Techniques of Data Science Date: April 13, Discussion #10

DS 100: Principles and Techniques of Data Science Date: April 13, Discussion #10 DS 00: Priciples ad Techiques of Data Sciece Date: April 3, 208 Name: Hypothesis Testig Discussio #0. Defie these terms below as they relate to hypothesis testig. a) Data Geeratio Model: Solutio: A set

More information

SNAP Centre Workshop. Basic Algebraic Manipulation

SNAP Centre Workshop. Basic Algebraic Manipulation SNAP Cetre Workshop Basic Algebraic Maipulatio 8 Simplifyig Algebraic Expressios Whe a expressio is writte i the most compact maer possible, it is cosidered to be simplified. Not Simplified: x(x + 4x)

More information

CHAPTER 10 INFINITE SEQUENCES AND SERIES

CHAPTER 10 INFINITE SEQUENCES AND SERIES CHAPTER 10 INFINITE SEQUENCES AND SERIES 10.1 Sequeces 10.2 Ifiite Series 10.3 The Itegral Tests 10.4 Compariso Tests 10.5 The Ratio ad Root Tests 10.6 Alteratig Series: Absolute ad Coditioal Covergece

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES Sequeces ad 6 Sequeces Ad SEQUENCES AND SERIES Successio of umbers of which oe umber is desigated as the first, other as the secod, aother as the third ad so o gives rise to what is called a sequece. Sequeces

More information

September 2012 C1 Note. C1 Notes (Edexcel) Copyright - For AS, A2 notes and IGCSE / GCSE worksheets 1

September 2012 C1 Note. C1 Notes (Edexcel) Copyright   - For AS, A2 notes and IGCSE / GCSE worksheets 1 September 0 s (Edecel) Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright

More information

Math 155 (Lecture 3)

Math 155 (Lecture 3) Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,

More information

MAT 271 Project: Partial Fractions for certain rational functions

MAT 271 Project: Partial Fractions for certain rational functions MAT 7 Project: Partial Fractios for certai ratioal fuctios Prerequisite kowledge: partial fractios from MAT 7, a very good commad of factorig ad complex umbers from Precalculus. To complete this project,

More information

CALCULATION OF FIBONACCI VECTORS

CALCULATION OF FIBONACCI VECTORS CALCULATION OF FIBONACCI VECTORS Stuart D. Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA email: saderso@ithaca.edu ad Dai Novak Departmet of Mathematics, Ithaca College

More information

(b) What is the probability that a particle reaches the upper boundary n before the lower boundary m?

(b) What is the probability that a particle reaches the upper boundary n before the lower boundary m? MATH 529 The Boudary Problem The drukard s walk (or boudary problem) is oe of the most famous problems i the theory of radom walks. Oe versio of the problem is described as follows: Suppose a particle

More information

PROPERTIES OF THE POSITIVE INTEGERS

PROPERTIES OF THE POSITIVE INTEGERS PROPERTIES OF THE POSITIVE ITEGERS The first itroductio to mathematics occurs at the pre-school level ad cosists of essetially coutig out the first te itegers with oe s figers. This allows the idividuals

More information

Some Basic Diophantine Equations

Some Basic Diophantine Equations Some Basic iophatie Equatios R.Maikada, epartmet of Mathematics, M.I.E.T. Egieerig College, Tiruchirappalli-7. Email: maimaths78@gmail.com bstract- - I this paper we preset a method for solvig the iophatie

More information

Mathematical Induction

Mathematical Induction Mathematical Iductio Itroductio Mathematical iductio, or just iductio, is a proof techique. Suppose that for every atural umber, P() is a statemet. We wish to show that all statemets P() are true. I a

More information

Linear Regression Demystified

Linear Regression Demystified Liear Regressio Demystified Liear regressio is a importat subject i statistics. I elemetary statistics courses, formulae related to liear regressio are ofte stated without derivatio. This ote iteds to

More information

Hoggatt and King [lo] defined a complete sequence of natural numbers

Hoggatt and King [lo] defined a complete sequence of natural numbers REPRESENTATIONS OF N AS A SUM OF DISTINCT ELEMENTS FROM SPECIAL SEQUENCES DAVID A. KLARNER, Uiversity of Alberta, Edmoto, Caada 1. INTRODUCTION Let a, I deote a sequece of atural umbers which satisfies

More information

Chapter 6 Infinite Series

Chapter 6 Infinite Series Chapter 6 Ifiite Series I the previous chapter we cosidered itegrals which were improper i the sese that the iterval of itegratio was ubouded. I this chapter we are goig to discuss a topic which is somewhat

More information

[ 11 ] z of degree 2 as both degree 2 each. The degree of a polynomial in n variables is the maximum of the degrees of its terms.

[ 11 ] z of degree 2 as both degree 2 each. The degree of a polynomial in n variables is the maximum of the degrees of its terms. [ 11 ] 1 1.1 Polyomial Fuctios 1 Algebra Ay fuctio f ( x) ax a1x... a1x a0 is a polyomial fuctio if ai ( i 0,1,,,..., ) is a costat which belogs to the set of real umbers ad the idices,, 1,...,1 are atural

More information

1 Generating functions for balls in boxes

1 Generating functions for balls in boxes Math 566 Fall 05 Some otes o geeratig fuctios Give a sequece a 0, a, a,..., a,..., a geeratig fuctio some way of represetig the sequece as a fuctio. There are may ways to do this, with the most commo ways

More information

The Random Walk For Dummies

The Random Walk For Dummies The Radom Walk For Dummies Richard A Mote Abstract We look at the priciples goverig the oe-dimesioal discrete radom walk First we review five basic cocepts of probability theory The we cosider the Beroulli

More information

N14/5/MATHL/HP1/ENG/TZ0/XX/M MARKSCHEME. November 2014 MATHEMATICS. Higher Level. Paper pages

N14/5/MATHL/HP1/ENG/TZ0/XX/M MARKSCHEME. November 2014 MATHEMATICS. Higher Level. Paper pages N4/5/MATHL/HP/ENG/TZ0/XX/M MARKSCHEME November 04 MATHEMATICS Higher Level Paper 0 pages N4/5/MATHL/HP/ENG/TZ0/XX/M This markscheme is the property of the Iteratioal Baccalaureate ad must ot be reproduced

More information

f t dt. Write the third-degree Taylor polynomial for G

f t dt. Write the third-degree Taylor polynomial for G AP Calculus BC Homework - Chapter 8B Taylor, Maclauri, ad Power Series # Taylor & Maclauri Polyomials Critical Thikig Joural: (CTJ: 5 pts.) Discuss the followig questios i a paragraph: What does it mea

More information

Data Analysis and Statistical Methods Statistics 651

Data Analysis and Statistical Methods Statistics 651 Data Aalysis ad Statistical Methods Statistics 651 http://www.stat.tamu.edu/~suhasii/teachig.html Suhasii Subba Rao Review of testig: Example The admistrator of a ursig home wats to do a time ad motio

More information

Chapter 2: Numerical Methods

Chapter 2: Numerical Methods Chapter : Numerical Methods. Some Numerical Methods for st Order ODEs I this sectio, a summar of essetial features of umerical methods related to solutios of ordiar differetial equatios is give. I geeral,

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

Calculus with Analytic Geometry 2

Calculus with Analytic Geometry 2 Calculus with Aalytic Geometry Fial Eam Study Guide ad Sample Problems Solutios The date for the fial eam is December, 7, 4-6:3p.m. BU Note. The fial eam will cosist of eercises, ad some theoretical questios,

More information

BIBECHANA A Multidisciplinary Journal of Science, Technology and Mathematics

BIBECHANA A Multidisciplinary Journal of Science, Technology and Mathematics Mohd Yusuf Yasi / BIBECHANA 8 (2012) 31-36 : BMHSS, p. 31 BIBECHANA A Multidiscipliary Joural of Sciece, Techology ad Mathematics ISSN 2091-0762 (olie) Joural homepage: http://epjol.ifo/ide.php/bibechana

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 5

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 5 CS434a/54a: Patter Recogitio Prof. Olga Veksler Lecture 5 Today Itroductio to parameter estimatio Two methods for parameter estimatio Maimum Likelihood Estimatio Bayesia Estimatio Itroducto Bayesia Decisio

More information

C. Complex Numbers. x 6x + 2 = 0. This equation was known to have three real roots, given by simple combinations of the expressions

C. Complex Numbers. x 6x + 2 = 0. This equation was known to have three real roots, given by simple combinations of the expressions C. Complex Numbers. Complex arithmetic. Most people thik that complex umbers arose from attempts to solve quadratic equatios, but actually it was i coectio with cubic equatios they first appeared. Everyoe

More information

Chapter 10: Power Series

Chapter 10: Power Series Chapter : Power Series 57 Chapter Overview: Power Series The reaso series are part of a Calculus course is that there are fuctios which caot be itegrated. All power series, though, ca be itegrated because

More information

(a) (b) All real numbers. (c) All real numbers. (d) None. to show the. (a) 3. (b) [ 7, 1) (c) ( 7, 1) (d) At x = 7. (a) (b)

(a) (b) All real numbers. (c) All real numbers. (d) None. to show the. (a) 3. (b) [ 7, 1) (c) ( 7, 1) (d) At x = 7. (a) (b) Chapter 0 Review 597. E; a ( + )( + ) + + S S + S + + + + + + S lim + l. D; a diverges by the Itegral l k Test sice d lim [(l ) ], so k l ( ) does ot coverge absolutely. But it coverges by the Alteratig

More information

LESSON 2: SIMPLIFYING RADICALS

LESSON 2: SIMPLIFYING RADICALS High School: Workig with Epressios LESSON : SIMPLIFYING RADICALS N.RN.. C N.RN.. B 5 5 C t t t t t E a b a a b N.RN.. 4 6 N.RN. 4. N.RN. 5. N.RN. 6. 7 8 N.RN. 7. A 7 N.RN. 8. 6 80 448 4 5 6 48 00 6 6 6

More information

Proof of Fermat s Last Theorem by Algebra Identities and Linear Algebra

Proof of Fermat s Last Theorem by Algebra Identities and Linear Algebra Proof of Fermat s Last Theorem by Algebra Idetities ad Liear Algebra Javad Babaee Ragai Youg Researchers ad Elite Club, Qaemshahr Brach, Islamic Azad Uiversity, Qaemshahr, Ira Departmet of Civil Egieerig,

More information

MATH 324 Summer 2006 Elementary Number Theory Solutions to Assignment 2 Due: Thursday July 27, 2006

MATH 324 Summer 2006 Elementary Number Theory Solutions to Assignment 2 Due: Thursday July 27, 2006 MATH 34 Summer 006 Elemetary Number Theory Solutios to Assigmet Due: Thursday July 7, 006 Departmet of Mathematical ad Statistical Scieces Uiversity of Alberta Questio [p 74 #6] Show that o iteger of the

More information

Lecture 2: April 3, 2013

Lecture 2: April 3, 2013 TTIC/CMSC 350 Mathematical Toolkit Sprig 203 Madhur Tulsiai Lecture 2: April 3, 203 Scribe: Shubhedu Trivedi Coi tosses cotiued We retur to the coi tossig example from the last lecture agai: Example. Give,

More information

OPTIMAL ALGORITHMS -- SUPPLEMENTAL NOTES

OPTIMAL ALGORITHMS -- SUPPLEMENTAL NOTES OPTIMAL ALGORITHMS -- SUPPLEMENTAL NOTES Peter M. Maurer Why Hashig is θ(). As i biary search, hashig assumes that keys are stored i a array which is idexed by a iteger. However, hashig attempts to bypass

More information

f x x c x c x c... x c...

f x x c x c x c... x c... CALCULUS BC WORKSHEET ON POWER SERIES. Derive the Taylor series formula by fillig i the blaks below. 4 5 Let f a a c a c a c a4 c a5 c a c What happes to this series if we let = c? f c so a Now differetiate

More information

ANOTHER GENERALIZED FIBONACCI SEQUENCE 1. INTRODUCTION

ANOTHER GENERALIZED FIBONACCI SEQUENCE 1. INTRODUCTION ANOTHER GENERALIZED FIBONACCI SEQUENCE MARCELLUS E. WADDILL A N D LOUIS SACKS Wake Forest College, Wisto Salem, N. C., ad Uiversity of ittsburgh, ittsburgh, a. 1. INTRODUCTION Recet issues of umerous periodicals

More information

Properties and Tests of Zeros of Polynomial Functions

Properties and Tests of Zeros of Polynomial Functions Properties ad Tests of Zeros of Polyomial Fuctios The Remaider ad Factor Theorems: Sythetic divisio ca be used to fid the values of polyomials i a sometimes easier way tha substitutio. This is show by

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

Appendix to Quicksort Asymptotics

Appendix to Quicksort Asymptotics Appedix to Quicksort Asymptotics James Alle Fill Departmet of Mathematical Scieces The Johs Hopkis Uiversity jimfill@jhu.edu ad http://www.mts.jhu.edu/~fill/ ad Svate Jaso Departmet of Mathematics Uppsala

More information

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer.

6 Integers Modulo n. integer k can be written as k = qn + r, with q,r, 0 r b. So any integer. 6 Itegers Modulo I Example 2.3(e), we have defied the cogruece of two itegers a,b with respect to a modulus. Let us recall that a b (mod ) meas a b. We have proved that cogruece is a equivalece relatio

More information

Measures of Spread: Standard Deviation

Measures of Spread: Standard Deviation Measures of Spread: Stadard Deviatio So far i our study of umerical measures used to describe data sets, we have focused o the mea ad the media. These measures of ceter tell us the most typical value of

More information

k=1 s k (x) (3) and that the corresponding infinite series may also converge; moreover, if it converges, then it defines a function S through its sum

k=1 s k (x) (3) and that the corresponding infinite series may also converge; moreover, if it converges, then it defines a function S through its sum 0. L Hôpital s rule You alreay kow from Lecture 0 that ay sequece {s k } iuces a sequece of fiite sums {S } through S = s k, a that if s k 0 as k the {S } may coverge to the it k= S = s s s 3 s 4 = s k.

More information

DIVISIBILITY PROPERTIES OF GENERALIZED FIBONACCI POLYNOMIALS

DIVISIBILITY PROPERTIES OF GENERALIZED FIBONACCI POLYNOMIALS DIVISIBILITY PROPERTIES OF GENERALIZED FIBONACCI POLYNOMIALS VERNER E. HOGGATT, JR. Sa Jose State Uiversity, Sa Jose, Califoria 95192 ad CALVIN T. LONG Washigto State Uiversity, Pullma, Washigto 99163

More information

sin(n) + 2 cos(2n) n 3/2 3 sin(n) 2cos(2n) n 3/2 a n =

sin(n) + 2 cos(2n) n 3/2 3 sin(n) 2cos(2n) n 3/2 a n = 60. Ratio ad root tests 60.1. Absolutely coverget series. Defiitio 13. (Absolute covergece) A series a is called absolutely coverget if the series of absolute values a is coverget. The absolute covergece

More information

For use only in Badminton School November 2011 C2 Note. C2 Notes (Edexcel)

For use only in Badminton School November 2011 C2 Note. C2 Notes (Edexcel) For use oly i Badmito School November 0 C Note C Notes (Edecel) Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets For use oly i Badmito School November 0 C Note Copyright www.pgmaths.co.uk

More information

Curve Sketching Handout #5 Topic Interpretation Rational Functions

Curve Sketching Handout #5 Topic Interpretation Rational Functions Curve Sketchig Hadout #5 Topic Iterpretatio Ratioal Fuctios A ratioal fuctio is a fuctio f that is a quotiet of two polyomials. I other words, p ( ) ( ) f is a ratioal fuctio if p ( ) ad q ( ) are polyomials

More information

INTEGRATION BY PARTS (TABLE METHOD)

INTEGRATION BY PARTS (TABLE METHOD) INTEGRATION BY PARTS (TABLE METHOD) Suppose you wat to evaluate cos d usig itegratio by parts. Usig the u dv otatio, we get So, u dv d cos du d v si cos d si si d or si si d We see that it is ecessary

More information

NUMERICAL METHODS FOR SOLVING EQUATIONS

NUMERICAL METHODS FOR SOLVING EQUATIONS Mathematics Revisio Guides Numerical Methods for Solvig Equatios Page 1 of 11 M.K. HOME TUITION Mathematics Revisio Guides Level: GCSE Higher Tier NUMERICAL METHODS FOR SOLVING EQUATIONS Versio:. Date:

More information

Appendix: The Laplace Transform

Appendix: The Laplace Transform Appedix: The Laplace Trasform The Laplace trasform is a powerful method that ca be used to solve differetial equatio, ad other mathematical problems. Its stregth lies i the fact that it allows the trasformatio

More information

Product measures, Tonelli s and Fubini s theorems For use in MAT3400/4400, autumn 2014 Nadia S. Larsen. Version of 13 October 2014.

Product measures, Tonelli s and Fubini s theorems For use in MAT3400/4400, autumn 2014 Nadia S. Larsen. Version of 13 October 2014. Product measures, Toelli s ad Fubii s theorems For use i MAT3400/4400, autum 2014 Nadia S. Larse Versio of 13 October 2014. 1. Costructio of the product measure The purpose of these otes is to preset the

More information

The Riemann Zeta Function

The Riemann Zeta Function Physics 6A Witer 6 The Riema Zeta Fuctio I this ote, I will sketch some of the mai properties of the Riema zeta fuctio, ζ(x). For x >, we defie ζ(x) =, x >. () x = For x, this sum diverges. However, we

More information

If a subset E of R contains no open interval, is it of zero measure? For instance, is the set of irrationals in [0, 1] is of measure zero?

If a subset E of R contains no open interval, is it of zero measure? For instance, is the set of irrationals in [0, 1] is of measure zero? 2 Lebesgue Measure I Chapter 1 we defied the cocept of a set of measure zero, ad we have observed that every coutable set is of measure zero. Here are some atural questios: If a subset E of R cotais a

More information

The "Last Riddle" of Pierre de Fermat, II

The Last Riddle of Pierre de Fermat, II The "Last Riddle" of Pierre de Fermat, II Alexader Mitkovsky mitkovskiy@gmail.com Some time ago, I published a work etitled, "The Last Riddle" of Pierre de Fermat " i which I had writte a proof of the

More information

Proof of Goldbach s Conjecture. Reza Javaherdashti

Proof of Goldbach s Conjecture. Reza Javaherdashti Proof of Goldbach s Cojecture Reza Javaherdashti farzijavaherdashti@gmail.com Abstract After certai subsets of Natural umbers called Rage ad Row are defied, we assume (1) there is a fuctio that ca produce

More information

Find a formula for the exponential function whose graph is given , 1 2,16 1, 6

Find a formula for the exponential function whose graph is given , 1 2,16 1, 6 Math 4 Activity (Due by EOC Apr. ) Graph the followig epoetial fuctios by modifyig the graph of f. Fid the rage of each fuctio.. g. g. g 4. g. g 6. g Fid a formula for the epoetial fuctio whose graph is

More information

Quadrature of the parabola with the square pyramidal number

Quadrature of the parabola with the square pyramidal number Quadrature of the parabola with the square pyramidal umber By Luciao Acora We perform here a ew proof of the Archimedes theorem o the quadrature of the parabolic segmet, executed without the aid of itegral

More information

Notes on iteration and Newton s method. Iteration

Notes on iteration and Newton s method. Iteration Notes o iteratio ad Newto s method Iteratio Iteratio meas doig somethig over ad over. I our cotet, a iteratio is a sequece of umbers, vectors, fuctios, etc. geerated by a iteratio rule of the type 1 f

More information

Castiel, Supernatural, Season 6, Episode 18

Castiel, Supernatural, Season 6, Episode 18 13 Differetial Equatios the aswer to your questio ca best be epressed as a series of partial differetial equatios... Castiel, Superatural, Seaso 6, Episode 18 A differetial equatio is a mathematical equatio

More information

Machine Learning for Data Science (CS 4786)

Machine Learning for Data Science (CS 4786) Machie Learig for Data Sciece CS 4786) Lecture & 3: Pricipal Compoet Aalysis The text i black outlies high level ideas. The text i blue provides simple mathematical details to derive or get to the algorithm

More information

Synopsis of Euler s paper. E Memoire sur la plus grande equation des planetes. (Memoir on the Maximum value of an Equation of the Planets)

Synopsis of Euler s paper. E Memoire sur la plus grande equation des planetes. (Memoir on the Maximum value of an Equation of the Planets) 1 Syopsis of Euler s paper E105 -- Memoire sur la plus grade equatio des plaetes (Memoir o the Maximum value of a Equatio of the Plaets) Compiled by Thomas J Osler ad Jase Adrew Scaramazza Mathematics

More information

Physics 116A Solutions to Homework Set #1 Winter Boas, problem Use equation 1.8 to find a fraction describing

Physics 116A Solutions to Homework Set #1 Winter Boas, problem Use equation 1.8 to find a fraction describing Physics 6A Solutios to Homework Set # Witer 0. Boas, problem. 8 Use equatio.8 to fid a fractio describig 0.694444444... Start with the formula S = a, ad otice that we ca remove ay umber of r fiite decimals

More information

CONVERGENCE OF SERIES. 225 SOME THEOREMS ON THE CONVERGENCE OF SERIES. BY PROFESSOR R. D. CARMICHAEL.

CONVERGENCE OF SERIES. 225 SOME THEOREMS ON THE CONVERGENCE OF SERIES. BY PROFESSOR R. D. CARMICHAEL. CONVERGENCE OF SERIES. 225 SOME THEOREMS ON THE CONVERGENCE OF SERIES. BY PROFESSOR R. D. CARMICHAEL. (Read before the America Mathematical Society, September 8, 1913.) No geeral criteria are kow for the

More information

Analysis of Experimental Measurements

Analysis of Experimental Measurements Aalysis of Experimetal Measuremets Thik carefully about the process of makig a measuremet. A measuremet is a compariso betwee some ukow physical quatity ad a stadard of that physical quatity. As a example,

More information

THE ZETA FUNCTION AND THE RIEMANN HYPOTHESIS. Contents 1. History 1

THE ZETA FUNCTION AND THE RIEMANN HYPOTHESIS. Contents 1. History 1 THE ZETA FUNCTION AND THE RIEMANN HYPOTHESIS VIKTOR MOROS Abstract. The zeta fuctio has bee studied for ceturies but mathematicias are still learig about it. I this paper, I will discuss some of the zeta

More information

Math 312 Lecture Notes One Dimensional Maps

Math 312 Lecture Notes One Dimensional Maps Math 312 Lecture Notes Oe Dimesioal Maps Warre Weckesser Departmet of Mathematics Colgate Uiversity 21-23 February 25 A Example We begi with the simplest model of populatio growth. Suppose, for example,

More information

Linear Differential Equations of Higher Order Basic Theory: Initial-Value Problems d y d y dy

Linear Differential Equations of Higher Order Basic Theory: Initial-Value Problems d y d y dy Liear Differetial Equatios of Higher Order Basic Theory: Iitial-Value Problems d y d y dy Solve: a( ) + a ( )... a ( ) a0( ) y g( ) + + + = d d d ( ) Subject to: y( 0) = y0, y ( 0) = y,..., y ( 0) = y

More information

a. For each block, draw a free body diagram. Identify the source of each force in each free body diagram.

a. For each block, draw a free body diagram. Identify the source of each force in each free body diagram. Pre-Lab 4 Tesio & Newto s Third Law Refereces This lab cocers the properties of forces eerted by strigs or cables, called tesio forces, ad the use of Newto s third law to aalyze forces. Physics 2: Tipler

More information

Final Review for MATH 3510

Final Review for MATH 3510 Fial Review for MATH 50 Calculatio 5 Give a fairly simple probability mass fuctio or probability desity fuctio of a radom variable, you should be able to compute the expected value ad variace of the variable

More information

Sets. Sets. Operations on Sets Laws of Algebra of Sets Cardinal Number of a Finite and Infinite Set. Representation of Sets Power Set Venn Diagram

Sets. Sets. Operations on Sets Laws of Algebra of Sets Cardinal Number of a Finite and Infinite Set. Representation of Sets Power Set Venn Diagram Sets MILESTONE Sets Represetatio of Sets Power Set Ve Diagram Operatios o Sets Laws of lgebra of Sets ardial Number of a Fiite ad Ifiite Set I Mathematical laguage all livig ad o-livig thigs i uiverse

More information

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER / Statistics

ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER / Statistics ACCESS TO SCIENCE, ENGINEERING AND AGRICULTURE: MATHEMATICS 1 MATH00030 SEMESTER 1 018/019 DR. ANTHONY BROWN 8. Statistics 8.1. Measures of Cetre: Mea, Media ad Mode. If we have a series of umbers the

More information

11.6 Absolute Convergence and the Ratio and Root Tests

11.6 Absolute Convergence and the Ratio and Root Tests .6 Absolute Covergece ad the Ratio ad Root Tests The most commo way to test for covergece is to igore ay positive or egative sigs i a series, ad simply test the correspodig series of positive terms. Does

More information

WHAT IS THE PROBABILITY FUNCTION FOR LARGE TSUNAMI WAVES? ABSTRACT

WHAT IS THE PROBABILITY FUNCTION FOR LARGE TSUNAMI WAVES? ABSTRACT WHAT IS THE PROBABILITY FUNCTION FOR LARGE TSUNAMI WAVES? Harold G. Loomis Hoolulu, HI ABSTRACT Most coastal locatios have few if ay records of tsuami wave heights obtaied over various time periods. Still

More information

lecture 3: Interpolation Error Bounds

lecture 3: Interpolation Error Bounds 6 lecture 3: Iterpolatio Error Bouds.6 Covergece Theory for Polyomial Iterpolatio Iterpolatio ca be used to geerate low-degree polyomials that approimate a complicated fuctio over the iterval [a, b]. Oe

More information

About the use of a result of Professor Alexandru Lupaş to obtain some properties in the theory of the number e 1

About the use of a result of Professor Alexandru Lupaş to obtain some properties in the theory of the number e 1 Geeral Mathematics Vol. 5, No. 2007), 75 80 About the use of a result of Professor Alexadru Lupaş to obtai some properties i the theory of the umber e Adrei Verescu Dedicated to Professor Alexadru Lupaş

More information

The Gamma function. Marco Bonvini. October 9, dt e t t z 1. (1) Γ(z + 1) = z Γ(z) : (2) = e t t z. + z dt e t t z 1. = z Γ(z).

The Gamma function. Marco Bonvini. October 9, dt e t t z 1. (1) Γ(z + 1) = z Γ(z) : (2) = e t t z. + z dt e t t z 1. = z Γ(z). The Gamma fuctio Marco Bovii October 9, 2 Gamma fuctio The Euler Gamma fuctio is defied as Γ() It is easy to show that Γ() satisfy the recursio relatio ideed, itegratig by parts, dt e t t. () Γ( + ) Γ()

More information