Cytotoxicity of ionic liquids and precursor compounds towards human cell line HeLa
|
|
- Ελλεν Κούνδουρος
- 6 χρόνια πριν
- Προβολές:
Transcript
1 Cytotoxcty of oc lqud ad precuror compoud toward huma cell le HeLa Xuefeg Wag, a,b C. Adré Ohl, a Qghua Lu,* a Zhaofu Fe, c Ju Hu, b ad Paul J. Dyo c a School of Chemtry ad Chemcal Techology, Shagha Jao Tog Uverty, Shagha , P.R. Cha Fax: ; Tel: ; E-mal: qhlu@jtu.edu.c b School of Lfe Scece ad Botechology, Shagha Jao Tog Uverty, Shagha , P.R. Cha. Tel: ; E-mal: xuefegwag@jtu.edu.c c Laboratory of Orgaometallc ad Medccal Chemtry, Ittut de Scece et Igéere Chmque, Sw Federal Ittute of Techology, 05-Lauae, Swtzerlad. Tel.: 4- ( ; E-mal: zhaofu.fe@epfl.ch. Idex a. Toxcty of ome commo olvet ad alt toward HeLa cell. b. Detaled parameter for alt ued cocetrato addto expermet. 2. Reult from cocetrato addto expermet. 3. K-value calculato for lthum bromde ad chole bromde. 4. Flow cytometrc meauremet of mtochodral membrae potetal ad reactve oxyge pece HeLa cell expoed to [C 2 mm][bf 4 ]. 5. Dervato of equato 3a ad 3b the ma text.
2 a. Toxcty of ome commo olvet ad alt toward HeLa cell. Table. Toxcty of ome commo olvet ad alt toward HeLa cell, determed after 48 hour the preece of FBS. Compoud f(x0-4 b EC 50 ± SE a (mm R 2 Acetoe - b ± Acetotrle - - > Ethaol ± N,N-Dmethylformamde ± Dmethylulfoxde ± Sodum dodecylbezeeulfoate ± Sodum chlorde ± Sodum bromde ± Lthum chlorde ± Lthum bromde ± a Stadard error. b f wa fxed a zero. b. Detaled parameter for alt ued cocetrato addto expermet. Table 2. Detaled parameter for alt ued cocetrato addto expermet. Toxcte determed the abece of FBS after 24 hour. Cato -R Ao f ± SE f (x0-4 b ± SE b EC 50 ± SE EC50 (mm a R 2 -C 2 H 5 Br ± ± C 4 H 9 Br ± ± C 8 H 7 Br ± ± CH 2 C 6 H 5 Br ± ± C 2 H 5 Br ± ± C 4 H 9 Br ± ± C 8 H 7 Br ± ± CH 2 C 6 H 5 Br ± ± CH 3 Br ± ± ± C 2 H 5 Br ± ± ± C 4 H 9 Br ± ± ± C 8 H 7 Br ± ± CH 2 C 6 H 5 Br ± ± L - Br ± ± ± a Sample ze. See ecto 5. 2
3 2. Reult from cocetrato addto expermet Table 3. Cocetrato addto data for mxture of alt ad cell cultured the abece of FBS for 24 hour. Etry Mxture C a b /EC 50, [C 2 Chol]Br ( ad [C 4 Chol]Br (2 2 [C 2 Chol]Br ( ad [C 8 Chol]Br (2 3 [C 2 Chol]Br ( ad [C 6 H 5 CH 2 Chol]Br (2 4 [C 4 Chol]Br ( ad[ C 8 Chol]Br (2 5 [C 4 Chol]Br ( ad [C 6 H 5 CH 2 Chol]Br (2 C 2 /EC 50,2 P c ± SE P -,d P,e ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
4 Etry Mxture C a b /EC 50, C 2 /EC 50,2 P c ± SE P -,d P,e ± ± ± ± ± ± ± ± [C 8 Chol]Br ( ad ± [C 6 H 5 CH 2 Chol]Br ( ± ± ± ± ± ± ± ± ± ± [C 2 Py]Br ( ad ± [C 4 Py]Br ( ± ± ± ± ± ± ± ± ± [C 2 Py]Br ( ad [C 8 Py]Br (2 9 [C 2 Py]Br ( ad [C 6 H 5 CH 2 Py]Br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± [C 4 Py]Br ( ad ±
5 Etry Mxture C /EC 50, C 2 /EC 50,2 P ± SE P -,d P,e [C 8 Py]Br ( ± ± ± ± ± ± ± ± ± ± [C 4 Py]Br ( ad ± [C 6 H 5 CH 2 Py]Br ( ± ± ± ± ± ± ± ± ± [C 8 Py]Br ( ad [C 6 H 5 CH 2 Py]Br (2 3 [C 2 mm]br ( ad [C 4 mmbr] (2 4 [C 2 mm]br ( ad [C 8 mm]br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
6 Etry Mxture C /EC 50, C 2 /EC 50,2 P ± SE P -,d P,e 5 [C 2 mm]br ( ad [C 6 H 5 CH 2 mm]br (2 6 [C 4 mm]br ( ad [C 8 mm]br (2 7 [C 4 mm]br ( ad [C 6 H 5 CH 2 mm]br (2 8 [C 8 mm]br ( ad [C 6 H 5 CH 2 mm]br (2 9 [C 2 Chol]Br ( ad [C 2 Py]Br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
7 Etry Mxture C /EC 50, C 2 /EC 50,2 P ± SE P -,d P,e 20 [C 2 Chol]Br ( ad [C 2 mm]br (2 2 [C 2 Py]Br ( ad [C 2 mm]br (2 22 [C 4 Chol]Br ( ad [C 4 Py]Br (2 23 [C 4 Chol]Br ( ad [C 4 mm]br (2 24 [C 4 Py]Br ( ad [C 4 mm]br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
8 Etry Mxture C /EC 50, C 2 /EC 50,2 P ± SE P -,d P,e 25 [C 8 Chol]Br ( ad [C 8 Py]Br (2 26 [C 8 Chol]Br ( ad [C 8 mm]br (2 27 [C 8 Py]Br ( ad [C 8 mm]br (2 28 [C 6 H 5 CH 2 Chol]Br ( ad [C 6 H 5 CH 2 Py]Br (2 29 [C 6 H 5 CH 2 Chol]Br ( ad [C 6 H 5 CH 2 mm]br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
9 Etry Mxture C /EC 50, C 2 /EC 50,2 P ± SE P -,d P,e 30 [C 6 H 5 CH 2 Py]Br ( ad [C 6 H 5 CH 2 mm]br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± a Cocetrato of compoud the mxture. b EC 50 of compoud. c Oberved mxture vablty. d See equato 3a the ma text. e See equato 3b the ma text. Table 4. Cocetrato addto volvg [C 4 Chol]Br (, [C 4 Py]Br (2 ad [C 4 mm]br (3. Cell cultured for 24 hour the abece of FBS. C /EC 50, C 2 /EC 50,2 C 3 /EC 50,3 P ± SE P - P ± ± ± ± ± ± ± ± ±
10 3. K-value calculato for lthum bromde ad chole bromde Table 5. Cocetrato addto of LBr ad chole bromde to [C 2 mm]br ad [C 8 mm]br ad cell cultured for 24 hour the abece of FBS. Etry Mxture C /EC 50, C 2 /EC 50,2 P ± SE P - P LBr ( ad [C 2 mm]br (2 2 LBr ( ad [C 8 mm]br (2 3 [C Chol]Br ( ad [C 2 mm]br (2 4 [C Chol]Br ( ad [C 8 mm]br ( ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
11 Fgure. K-value plot for LBr ad chole bromde ([C Chol]Br whe hypotoxc quatte are added to [C 2 mm]br (A ad [C 8 mm]br (B A B A B K-Value K-Value LBr (mm [C Chol]Br (mm
12 4. Chage of mtochodral membrae potetal ad reactve oxyge pece HeLa cell cultured wth [C 2 mm][bf 4 ]. Fgure 2. Chage of mtochodral membrae potetal of HeLa cell cultured wth or wthout [C 2 mm][bf 4 ] for 48 hour detected by Rhodame 23. A: egatve cotrol, utaed cell; B: potve cotrol, taed ormal cell; C: treatmet, taed cell cultured wth [C 2 mm][bf 4 ] (6.3 mm; D: combato of B ad C. 2
13 Fgure 3. Reactve oxyge pece (ROS producto of HeLa cell cultured wth or wthout [C 2 mm][bf 4 ] for 48 hour A: egatve cotrol, utaed cell; B: potve cotrol, taed ormal cell; C: treatmet, taed cell cultured wth [C 2 mm][bf 4 ] (6.3 mm; D: combato of B ad C. 3
14 5. Dervato of equato 3a ad 3b the ma text. Equato 3a ad 3b were derved from equato 2 referece 33 the ma paper. The relatohp betwee P ad R ca be decrbed through equato S. P = R S. A ρ ad b deote the ame term, ad ρ beg the mple average of the ρ for each chemcal ( ρ the mxture, equato 2 from Rder ad LeBlac ca be wrtte a ρ ' = = P = R = ( = C EC 50, ρ ' = ( C EC = 50, ρ = = ( C EC = 50, b = S.2 If the cofdece terval of EC 50 ad b (at 95% cofdece level are take to accout, we get P = ( = EC 50, C.96SE ± EC 50, =.96SE b ± where SE deote tadard error ad the ample ze for compoud. Sce the cocetrato were choe o that C =, S.4 = EC50, the followg relatohp are oberved for SE EC50, >0 ad SE b, >0 C ( < S.5 =.96SEEC 50, EC50, ad ( C.96SE = EC50, EC50, o that >.96SEb,.96SEb, b b = = C C ( < ( SE S.7 =.96 EC = SE 50,.96 EC50, EC50, EC50, ad b, S.3 S.6 4
15 .96SE b,.96seb, b b = = C C ( > ( SE S.8 =.96 EC = SE 50.96, EC 50, EC50, EC50, The the upper ad lower lmt of the cofdece terval of P (P deotg the upper lmt, ad P - deotg the lower lmt wll be P = S.9.96SEb, b = C ( =.96SEEC50, EC50, = C.96SE ad P = S.0 ( EC 50, EC50,.96SEb, b = Equato S.9 ad S.0 are detcal to equato 3a ad 3b the ma text. 5
Estimators when the Correlation Coefficient. is Negative
It J Cotemp Math Sceces, Vol 5, 00, o 3, 45-50 Estmators whe the Correlato Coeffcet s Negatve Sad Al Al-Hadhram College of Appled Sceces, Nzwa, Oma abur97@ahoocouk Abstract Rato estmators for the mea of
Διαβάστε περισσότεραDESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.
DESIGN OF MACHINERY SOLUTION MANUAL -7-1! PROBLEM -7 Statement: Design a double-dwell cam to move a follower from to 25 6, dwell for 12, fall 25 and dwell for the remader The total cycle must take 4 sec
Διαβάστε περισσότεραCS 1675 Introduction to Machine Learning Lecture 7. Density estimation. Milos Hauskrecht 5329 Sennott Square
CS 675 Itroducto to Mache Learg Lecture 7 esty estmato Mlos Hausrecht mlos@cs.tt.edu 539 Seott Square ata: esty estmato {.. } a vector of attrbute values Objectve: estmate the model of the uderlyg robablty
Διαβάστε περισσότεραt-distribution t a (ν) s N μ = where X s s x = ν 2 FD ν 1 FD a/2 a/2 t-distribution normal distribution for ν>120
t-ditribution t X x μ = where x = ν FD ν FD t a (ν) 0 t-ditribution normal ditribution for ν>0 a/ a/ -ta ta ΒΑΘΜΟΙ ΕΛΕΥΘΕΡΙΑΣ (freedom degree) Βαθμοί ελευθερίας (ν): ο αριθμός των ανεξάρτητων μετρήσεων
Διαβάστε περισσότερα1. For each of the following power series, find the interval of convergence and the radius of convergence:
Math 6 Practice Problems Solutios Power Series ad Taylor Series 1. For each of the followig power series, fid the iterval of covergece ad the radius of covergece: (a ( 1 x Notice that = ( 1 +1 ( x +1.
Διαβάστε περισσότεραCalculating the propagation delay of coaxial cable
Your source for quality GNSS Networking Solutions and Design Services! Page 1 of 5 Calculating the propagation delay of coaxial cable The delay of a cable or velocity factor is determined by the dielectric
Διαβάστε περισσότεραp n r.01.05.10.15.20.25.30.35.40.45.50.55.60.65.70.75.80.85.90.95
r r Table 4 Biomial Probability Distributio C, r p q This table shows the probability of r successes i idepedet trials, each with probability of success p. p r.01.05.10.15.0.5.30.35.40.45.50.55.60.65.70.75.80.85.90.95
Διαβάστε περισσότεραΠανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών. ΗΥ-570: Στατιστική Επεξεργασία Σήµατος. ιδάσκων : Α. Μουχτάρης. εύτερη Σειρά Ασκήσεων.
Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 2015 ιδάσκων : Α. Μουχτάρης εύτερη Σειρά Ασκήσεων Λύσεις Ασκηση 1. 1. Consder the gven expresson for R 1/2 : R 1/2
Διαβάστε περισσότεραExercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.
Exercises 0 More exercises are available in Elementary Differential Equations. If you have a problem to solve any of them, feel free to come to office hour. Problem Find a fundamental matrix of the given
Διαβάστε περισσότεραHomework for 1/27 Due 2/5
Name: ID: Homework for /7 Due /5. [ 8-3] I Example D of Sectio 8.4, the pdf of the populatio distributio is + αx x f(x α) =, α, otherwise ad the method of momets estimate was foud to be ˆα = 3X (where
Διαβάστε περισσότεραLatent variable models Variational approximations.
CS 3750 Mache Learg Lectre 9 Latet varable moel Varatoal appromato. Mlo arecht mlo@c.ptt.e 539 Seott Sqare CS 750 Mache Learg Cooperatve vector qatzer Latet varable : meoalty bary var Oberve varable :
Διαβάστε περισσότεραMulti-dimensional Central Limit Theorem
Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t tme
Διαβάστε περισσότεραDiscrete Fourier Transform { } ( ) sin( ) Discrete Sine Transformation. n, n= 0,1,2,, when the function is odd, f (x) = f ( x) L L L N N.
Dscrete Fourer Trasform Refereces:. umercal Aalyss of Spectral Methods: Theory ad Applcatos, Davd Gottleb ad S.A. Orszag, Soc. for Idust. App. Math. 977.. umercal smulato of compressble flows wth smple
Διαβάστε περισσότεραEE101: Resonance in RLC circuits
EE11: Resonance in RLC circuits M. B. Patil mbatil@ee.iitb.ac.in www.ee.iitb.ac.in/~sequel Deartment of Electrical Engineering Indian Institute of Technology Bombay I V R V L V C I = I m = R + jωl + 1/jωC
Διαβάστε περισσότεραSupplementary Appendix
Supplementary Appendix Measuring crisis risk using conditional copulas: An empirical analysis of the 2008 shipping crisis Sebastian Opitz, Henry Seidel and Alexander Szimayer Model specification Table
Διαβάστε περισσότεραAquinas College. Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET
Aquinas College Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET Pearson Edexcel Level 3 Advanced Subsidiary and Advanced GCE in Mathematics and Further Mathematics Mathematical
Διαβάστε περισσότεραLatent variable models Variational approximations.
CS 3750 Mache Learg Lectre 9 Latet varable moel Varatoal appromato. Mlo arecht mlo@c.ptt.e 539 Seott Sqare CS 750 Mache Learg Cooperatve vector qatzer Latet varable : meoalty bary var Oberve varable :
Διαβάστε περισσότεραα β
6. Eerg, Mometum coefficiets for differet velocit distributios Rehbock obtaied ) For Liear Velocit Distributio α + ε Vmax { } Vmax ε β +, i which ε v V o Give: α + ε > ε ( α ) Liear velocit distributio
Διαβάστε περισσότερα2. THEORY OF EQUATIONS. PREVIOUS EAMCET Bits.
EAMCET-. THEORY OF EQUATIONS PREVIOUS EAMCET Bits. Each of the roots of the equation x 6x + 6x 5= are increased by k so that the new transformed equation does not contain term. Then k =... - 4. - Sol.
Διαβάστε περισσότεραFREE VIBRATION OF A SINGLE-DEGREE-OF-FREEDOM SYSTEM Revision B
FREE VIBRATION OF A SINGLE-DEGREE-OF-FREEDOM SYSTEM Revisio B By Tom Irvie Email: tomirvie@aol.com February, 005 Derivatio of the Equatio of Motio Cosier a sigle-egree-of-freeom system. m x k c where m
Διαβάστε περισσότεραMatrices and Determinants
Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z
Διαβάστε περισσότεραConductivity Logging for Thermal Spring Well
/.,**. 25 +,1- **-- 0/2,,,1- **-- 0/2, +,, +/., +0 /,* Conductivity Logging for Thermal Spring Well Koji SATO +, Tadashi TAKAYA,, Tadashi CHIBA, + Nihon Chika Kenkyuusho Co. Ltd., 0/2,, Hongo, Funabashi,
Διαβάστε περισσότεραLast Lecture. Biostatistics Statistical Inference Lecture 19 Likelihood Ratio Test. Example of Hypothesis Testing.
Last Lecture Biostatistics 602 - Statistical Iferece Lecture 19 Likelihood Ratio Test Hyu Mi Kag March 26th, 2013 Describe the followig cocepts i your ow words Hypothesis Null Hypothesis Alterative Hypothesis
Διαβάστε περισσότερα4.6 Autoregressive Moving Average Model ARMA(1,1)
84 CHAPTER 4. STATIONARY TS MODELS 4.6 Autoregressive Moving Average Model ARMA(,) This section is an introduction to a wide class of models ARMA(p,q) which we will consider in more detail later in this
Διαβάστε περισσότεραC.S. 430 Assignment 6, Sample Solutions
C.S. 430 Assignment 6, Sample Solutions Paul Liu November 15, 2007 Note that these are sample solutions only; in many cases there were many acceptable answers. 1 Reynolds Problem 10.1 1.1 Normal-order
Διαβάστε περισσότεραEd Stanek. c08ed01v6.doc A version of the grant proposal to be submitted for review in 2008.
Relatnhp between tatn ued b ew Grant Applcatn, and Regren Predctr Develpment f Gnzala wth Suggeted Change t Cmmn tatn Baed n Gnzala and Stanek ntrductn Ed Stanek We lt ntatn ued n tw prncpal dcument, wth
Διαβάστε περισσότεραMulti-dimensional Central Limit Theorem
Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t ();
Διαβάστε περισσότεραΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ
ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΕΛΕΝΑ ΦΛΟΚΑ Επίκουρος Καθηγήτρια Τµήµα Φυσικής, Τοµέας Φυσικής Περιβάλλοντος- Μετεωρολογίας ΓΕΝΙΚΟΙ ΟΡΙΣΜΟΙ Πληθυσµός Σύνολο ατόµων ή αντικειµένων στα οποία αναφέρονται
Διαβάστε περισσότεραSCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions
SCHOOL OF MATHEMATICAL SCIENCES GLMA Linear Mathematics 00- Examination Solutions. (a) i. ( + 5i)( i) = (6 + 5) + (5 )i = + i. Real part is, imaginary part is. (b) ii. + 5i i ( + 5i)( + i) = ( i)( + i)
Διαβάστε περισσότεραNa/K (mole) A/CNK
Li, W.-C., Chen, R.-X., Zheng, Y.-F., Tang, H., and Hu, Z., 206, Two episodes of partial melting in ultrahigh-pressure migmatites from deeply subducted continental crust in the Sulu orogen, China: GSA
Διαβάστε περισσότεραOn Hypersurface of Special Finsler Spaces. Admitting Metric Like Tensor Field
It J otem Mat Sceces Vo 7 0 o 9 99-98 O Hyersurface of Seca Fser Saces Admttg Metrc Lke Tesor Fed H Wosoug Deartmet of Matematcs Isamc Azad Uversty Babo Brac Ira md_vosog@yaoocom Abstract I te reset work
Διαβάστε περισσότεραHomework 4.1 Solutions Math 5110/6830
Homework 4. Solutios Math 5/683. a) For p + = αp γ α)p γ α)p + γ b) Let Equilibria poits satisfy: p = p = OR = γ α)p ) γ α)p + γ = α γ α)p ) γ α)p + γ α = p ) p + = p ) = The, we have equilibria poits
Διαβάστε περισσότερα8.1 The Nature of Heteroskedasticity 8.2 Using the Least Squares Estimator 8.3 The Generalized Least Squares Estimator 8.
8.1 The Nature of Heteroskedastcty 8. Usng the Least Squares Estmator 8.3 The Generalzed Least Squares Estmator 8.4 Detectng Heteroskedastcty E( y) = β+β 1 x e = y E( y ) = y β β x 1 y = β+β x + e 1 Fgure
Διαβάστε περισσότεραdepartment listing department name αχχουντσ ϕανε βαλικτ δδσϕηασδδη σδηφγ ασκϕηλκ τεχηνιχαλ αλαν ϕουν διξ τεχηνιχαλ ϕοην µαριανι
She selects the option. Jenny starts with the al listing. This has employees listed within She drills down through the employee. The inferred ER sttricture relates this to the redcords in the databasee
Διαβάστε περισσότεραΠανεπιστήμιο Κρήτης, Τμήμα Επιστήμης Υπολογιστών Άνοιξη 2009. HΥ463 - Συστήματα Ανάκτησης Πληροφοριών Information Retrieval (IR) Systems
Πανεπιστήμιο Κρήτης, Τμήμα Επιστήμης Υπολογιστών Άνοιξη 2009 HΥ463 - Συστήματα Ανάκτησης Πληροφοριών Information Retrieval (IR) Systems Στατιστικά Κειμένου Text Statistics Γιάννης Τζίτζικας άλ ιάλεξη :
Διαβάστε περισσότεραSolution Series 9. i=1 x i and i=1 x i.
Lecturer: Prof. Dr. Mete SONER Coordinator: Yilin WANG Solution Series 9 Q1. Let α, β >, the p.d.f. of a beta distribution with parameters α and β is { Γ(α+β) Γ(α)Γ(β) f(x α, β) xα 1 (1 x) β 1 for < x
Διαβάστε περισσότεραDurbin-Levinson recursive method
Durbin-Levinson recursive method A recursive method for computing ϕ n is useful because it avoids inverting large matrices; when new data are acquired, one can update predictions, instead of starting again
Διαβάστε περισσότεραHOMEWORK#1. t E(x) = 1 λ = (b) Find the median lifetime of a randomly selected light bulb. Answer:
HOMEWORK# 52258 李亞晟 Eercise 2. The lifetime of light bulbs follows an eponential distribution with a hazard rate of. failures per hour of use (a) Find the mean lifetime of a randomly selected light bulb.
Διαβάστε περισσότεραExam Statistics 6 th September 2017 Solution
Exam Statstcs 6 th September 17 Soluto Maura Mezzett Exercse 1 Let (X 1,..., X be a raom sample of... raom varables. Let f θ (x be the esty fucto. Let ˆθ be the MLE of θ, θ be the true parameter, L(θ be
Διαβάστε περισσότεραSample BKC-10 Mn. Sample BKC-23 Mn. BKC-10 grt Path A Path B Path C. garnet resorption. garnet resorption. BKC-23 grt Path A Path B Path C
0.5 0.45 0.4 0.35 0.3 Sample BKC-10 Mn BKC-10 grt Path A Path B Path C 0.12 0.1 0.08 Mg 0.25 0.06 0.2 0.15 0.04 0.1 0.05 0.02 0 0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 Core Rim 0.9 0.8 Fe 0 0 0.01 0.02
Διαβάστε περισσότεραDaewoo Technopark A-403, Dodang-dong, Wonmi-gu, Bucheon-city, Gyeonggido, Korea LM-80 Test Report
LM-80 Test Report Approved Method: Measuring Lumen Maintenance of LED Light Sources Project Number: KILT1212-U00216 Date: September 17 th, 2013 Requested by: Dongbu LED Co., Ltd 90-1, Bongmyeong-Ri, Namsa-Myeon,
Διαβάστε περισσότεραΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ
ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΓΕΝΙΚΕΣ ΠΑΡΑΤΗΡΗΣΕΙΣ ΕΠΙ ΡΑΣΗ Μ.Β ΣΤΙΣ Ι ΙΟΤΗΤΕΣ ΠΟΛΥΜΕΡΩΝ ΜΑΘΗΜΑΤΙΚΗ ΠΕΡΙΓΡΑΦΗ ΤΗΣ ΚΑΤΑΝΟΜΗΣ ΜΟΡΙΑΚΟΥ ΒΑΡΟΥΣ ΣΥΝΑΡΤΗΣΗ ΠΙΘΑΝΟΤΗΤΟΣ ( ΙΑΦΟΡΙΚΗ) Probablty Densty Functon
Διαβάστε περισσότεραIIT JEE (2013) (Trigonomtery 1) Solutions
L.K. Gupta (Mathematic Classes) www.pioeermathematics.com MOBILE: 985577, 677 (+) PAPER B IIT JEE (0) (Trigoomtery ) Solutios TOWARDS IIT JEE IS NOT A JOURNEY, IT S A BATTLE, ONLY THE TOUGHEST WILL SURVIVE
Διαβάστε περισσότεραHW 3 Solutions 1. a) I use the auto.arima R function to search over models using AIC and decide on an ARMA(3,1)
HW 3 Solutions a) I use the autoarima R function to search over models using AIC and decide on an ARMA3,) b) I compare the ARMA3,) to ARMA,0) ARMA3,) does better in all three criteria c) The plot of the
Διαβάστε περισσότεραAPPENDICES APPENDIX A. STATISTICAL TABLES AND CHARTS 651 APPENDIX B. BIBLIOGRAPHY 677 APPENDIX C. ANSWERS TO SELECTED EXERCISES 679
APPENDICES APPENDIX A. STATISTICAL TABLES AND CHARTS 1 Table I Summary of Common Probability Distributions 2 Table II Cumulative Standard Normal Distribution Table III Percentage Points, 2 of the Chi-Squared
Διαβάστε περισσότεραModbus basic setup notes for IO-Link AL1xxx Master Block
n Modbus has four tables/registers where data is stored along with their associated addresses. We will be using the holding registers from address 40001 to 49999 that are R/W 16 bit/word. Two tables that
Διαβάστε περισσότεραHomework 3 Solutions
Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For
Διαβάστε περισσότεραUDZ Swirl diffuser. Product facts. Quick-selection. Swirl diffuser UDZ. Product code example:
UDZ Swirl diffuser Swirl diffuser UDZ, which is intended for installation in a ventilation duct, can be used in premises with a large volume, for example factory premises, storage areas, superstores, halls,
Διαβάστε περισσότεραα & β spatial orbitals in
The atrx Hartree-Fock equatons The most common method of solvng the Hartree-Fock equatons f the spatal btals s to expand them n terms of known functons, { χ µ } µ= consder the spn-unrestrcted case. We
Διαβάστε περισσότεραFractional Colorings and Zykov Products of graphs
Fractional Colorings and Zykov Products of graphs Who? Nichole Schimanski When? July 27, 2011 Graphs A graph, G, consists of a vertex set, V (G), and an edge set, E(G). V (G) is any finite set E(G) is
Διαβάστε περισσότεραCite as: Pol Antras, course materials for International Economics I, Spring MIT OpenCourseWare (http://ocw.mit.edu/), Massachusetts
/ / σ/σ σ/σ θ θ θ θ y 1 0.75 0.5 0.25 0 0 0.5 1 1.5 2 θ θ θ x θ θ Φ θ Φ θ Φ π θ /Φ γφ /θ σ θ π θ Φ θ θ Φ θ θ θ θ σ θ / Φ θ θ / Φ / θ / θ Normalized import share: (Xni / Xn) / (XII / XI) 1 0.1 0.01 0.001
Διαβάστε περισσότεραΥπόδειγµα Προεξόφλησης
Αρτίκης Γ. Παναγιώτης Υπόδειγµα Προεξόφλησης Μερισµάτων Γενικό Υπόδειγµα (Geeral Model) Ταµειακές ροές από αγορά µετοχών: Μερίσµατα κατά την διάρκεια κατοχής των µετοχών Μια αναµενόµενη τιµή στο τέλος
Διαβάστε περισσότεραEE512: Error Control Coding
EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3
Διαβάστε περισσότεραΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ
ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΓΕΝΙΚΕΣ ΠΑΡΑΤΗΡΗΣΕΙΣ ΕΠΙΔΡΑΣΗ Μ.Β ΣΤΙΣ ΙΔΙΟΤΗΤΕΣ ΠΟΛΥΜΕΡΩΝ ΜΑΘΗΜΑΤΙΚΗ ΠΕΡΙΓΡΑΦΗ ΤΗΣ ΚΑΤΑΝΟΜΗΣ ΜΟΡΙΑΚΟΥ ΒΑΡΟΥΣ ΣΥΝΑΡΤΗΣΗ ΠΙΘΑΝΟΤΗΤΟΣ (ΔΙΑΦΟΡΙΚΗ) Probablty Densty Functon
Διαβάστε περισσότεραOther Test Constructions: Likelihood Ratio & Bayes Tests
Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :
Διαβάστε περισσότεραSupplementary Information 1.
Supplementary Information 1. Fig. S1. Correlations between litter-derived-c and N (percent of initial input) and Al-/Fe- (hydr)oxides dissolved by ammonium oxalate (AO); a) 0 10 cm; b) 10 20 cm; c) 20
Διαβάστε περισσότεραHOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:
HOMEWORK 4 Problem a For the fast loading case, we want to derive the relationship between P zz and λ z. We know that the nominal stress is expressed as: P zz = ψ λ z where λ z = λ λ z. Therefore, applying
Διαβάστε περισσότεραCHAPTER 101 FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD
CHAPTER FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD EXERCISE 36 Page 66. Determine the Fourier series for the periodic function: f(x), when x +, when x which is periodic outside this rge of period.
Διαβάστε περισσότεραSecond Order RLC Filters
ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor
Διαβάστε περισσότεραGlobal energy use: Decoupling or convergence?
Crawford School of Public Policy Centre for Climate Economics & Policy Global energy use: Decoupling or convergence? CCEP Working Paper 1419 December 2014 Zsuzsanna Csereklyei Geschwister Scholl Institute
Διαβάστε περισσότεραΠρόβλημα 1: Αναζήτηση Ελάχιστης/Μέγιστης Τιμής
Πρόβλημα 1: Αναζήτηση Ελάχιστης/Μέγιστης Τιμής Να γραφεί πρόγραμμα το οποίο δέχεται ως είσοδο μια ακολουθία S από n (n 40) ακέραιους αριθμούς και επιστρέφει ως έξοδο δύο ακολουθίες από θετικούς ακέραιους
Διαβάστε περισσότεραStatistics & Research methods. Athanasios Papaioannou University of Thessaly Dept. of PE & Sport Science
Statistics & Research methods Athanasios Papaioannou University of Thessaly Dept. of PE & Sport Science 30 25 1,65 20 1,66 15 10 5 1,67 1,68 Κανονική 0 Height 1,69 Καμπύλη Κανονική Διακύμανση & Ζ-scores
Διαβάστε περισσότεραVidyalankar. Vidyalankar S.E. Sem. III [BIOM] Applied Mathematics - III Prelim Question Paper Solution. 1 e = 1 1. f(t) =
. (a). (b). (c) f() L L e i e Vidyalakar S.E. Sem. III [BIOM] Applied Mahemaic - III Prelim Queio Paper Soluio L el e () i ( ) H( ) u e co y + 3 3y u e co y + 6 uy e i y 6y uyy e co y 6 u + u yy e co y
Διαβάστε περισσότεραDiscontinuous Hermite Collocation and Diagonally Implicit RK3 for a Brain Tumour Invasion Model
1 Discontinuous Hermite Collocation and Diagonally Implicit RK3 for a Brain Tumour Invasion Model John E. Athanasakis Applied Mathematics & Computers Laboratory Technical University of Crete Chania 73100,
Διαβάστε περισσότεραSection 9.2 Polar Equations and Graphs
180 Section 9. Polar Equations and Graphs In this section, we will be graphing polar equations on a polar grid. In the first few examples, we will write the polar equation in rectangular form to help identify
Διαβάστε περισσότεραCHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS
CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =
Διαβάστε περισσότεραINTEGRATION OF THE NORMAL DISTRIBUTION CURVE
INTEGRATION OF THE NORMAL DISTRIBUTION CURVE By Tom Irvie Email: tomirvie@aol.com March 3, 999 Itroductio May processes have a ormal probability distributio. Broadbad radom vibratio is a example. The purpose
Διαβάστε περισσότεραECE145a / 218a Tuned Amplifier Design -basic gain relationships
ca note, M. Rodwe, copyrighted 009 ECE45a / 8a uned Ampifier Deign -aic ga reationhip -deign the (impe) uniatera imit it Mark Rodwe Univerity of Caifornia, anta Barara rodwe@ece.uc.edu 805-893-344, 805-893-36
Διαβάστε περισσότεραStatistics 104: Quantitative Methods for Economics Formula and Theorem Review
Harvard College Statistics 104: Quantitative Methods for Economics Formula and Theorem Review Tommy MacWilliam, 13 tmacwilliam@college.harvard.edu March 10, 2011 Contents 1 Introduction to Data 5 1.1 Sample
Διαβάστε περισσότεραDoes anemia contribute to end-organ dysfunction in ICU patients Statistical Analysis
Does anemia contribute to end-organ dysfunction in ICU patients Statistical Analysis Xue Han, MPH and Matt Shotwell, PhD Department of Biostatistics Vanderbilt University School of Medicine March 14, 2014
Διαβάστε περισσότεραL.K.Gupta (Mathematic Classes) www.pioeermathematics.com MOBILE: 985577, 4677 + {JEE Mai 04} Sept 0 Name: Batch (Day) Phoe No. IT IS NOT ENOUGH TO HAVE A GOOD MIND, THE MAIN THING IS TO USE IT WELL Marks:
Διαβάστε περισσότεραMATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)
1. MATH43 String Theory Solutions 4 x = 0 τ = fs). 1) = = f s) ) x = x [f s)] + f s) 3) equation of motion is x = 0 if an only if f s) = 0 i.e. fs) = As + B with A, B constants. i.e. allowe reparametrisations
Διαβάστε περισσότεραSUPERPOSITION, MEASUREMENT, NORMALIZATION, EXPECTATION VALUES. Reading: QM course packet Ch 5 up to 5.6
SUPERPOSITION, MEASUREMENT, NORMALIZATION, EXPECTATION VALUES Readig: QM course packet Ch 5 up to 5. 1 ϕ (x) = E = π m( a) =1,,3,4,5 for xa (x) = πx si L L * = πx L si L.5 ϕ' -.5 z 1 (x) = L si
Διαβάστε περισσότεραMock Exam 7. 1 Hong Kong Educational Publishing Company. Section A 1. Reference: HKDSE Math M Q2 (a) (1 + kx) n 1M + 1A = (1) =
Mock Eam 7 Mock Eam 7 Section A. Reference: HKDSE Math M 0 Q (a) ( + k) n nn ( )( k) + nk ( ) + + nn ( ) k + nk + + + A nk... () nn ( ) k... () From (), k...() n Substituting () into (), nn ( ) n 76n 76n
Διαβάστε περισσότεραΑΝΑΛΥΣΗ ΔΙΑΣΠΟΡΑΣ,
ΑΝΑΛΥΣΗ ΔΙΑΣΠΟΡΑΣ, --0 Άσκηση. Τα παρακάτω δεδομένα προέρχονται από μετρήσεις του δείκτη του σακχάρου στο αίμα 0 ποντικών που εξετάσθηκαν: ) υπό κανονικές συνθήκες, ) μετά από ένεση ptre, ) μετά από ένεση
Διαβάστε περισσότεραResurvey of Possible Seismic Fissures in the Old-Edo River in Tokyo
Bull. Earthq. Res. Inst. Univ. Tokyo Vol. 2.,**3 pp.,,3,.* * +, -. +, -. Resurvey of Possible Seismic Fissures in the Old-Edo River in Tokyo Kunihiko Shimazaki *, Tsuyoshi Haraguchi, Takeo Ishibe +, -.
Διαβάστε περισσότεραΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα,
ΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα Βασίλειος Σύρης Τμήμα Επιστήμης Υπολογιστών Πανεπιστήμιο Κρήτης Εαρινό εξάμηνο 2008 Economcs Contents The contet The basc model user utlty, rces and
Διαβάστε περισσότεραΨηφιακή Επεξεργασία Εικόνας
ΠΑΝΕΠΙΣΤΗΜΙΟ ΙΩΑΝΝΙΝΩΝ ΑΝΟΙΚΤΑ ΑΚΑΔΗΜΑΪΚΑ ΜΑΘΗΜΑΤΑ Ψηφιακή Επεξεργασία Εικόνας Φιλτράρισμα στο πεδίο των συχνοτήτων Διδάσκων : Αναπληρωτής Καθηγητής Νίκου Χριστόφορος Άδειες Χρήσης Το παρόν εκπαιδευτικό
Διαβάστε περισσότερα( )( ) ( ) ( )( ) ( )( ) β = Chapter 5 Exercise Problems EX α So 49 β 199 EX EX EX5.4 EX5.5. (a)
hapter 5 xercise Problems X5. α β α 0.980 For α 0.980, β 49 0.980 0.995 For α 0.995, β 99 0.995 So 49 β 99 X5. O 00 O or n 3 O 40.5 β 0 X5.3 6.5 μ A 00 β ( 0)( 6.5 μa) 8 ma 5 ( 8)( 4 ) or.88 P on + 0.0065
Διαβάστε περισσότεραΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Αν κάπου κάνετε κάποιες υποθέσεις να αναφερθούν στη σχετική ερώτηση. Όλα τα αρχεία που αναφέρονται στα προβλήματα βρίσκονται στον ίδιο φάκελο με το εκτελέσιμο
Διαβάστε περισσότεραΜορφοποίηση υπό όρους : Μορφή > Μορφοποίηση υπό όρους/γραμμές δεδομένων/μορφοποίηση μόο των κελιών που περιέχουν/
Μορφοποίηση υπό όρους : Μορφή > Μορφοποίηση υπό όρους/γραμμές δεδομένων/μορφοποίηση μόο των κελιών που περιέχουν/ Συνάρτηση round() Περιγραφή Η συνάρτηση ROUND στρογγυλοποιεί έναν αριθμό στον δεδομένο
Διαβάστε περισσότεραΔΙΑΣΤΑΣΕΙΣ ΕΣΩΤΕΡΙΚΗΣ ΓΩΝΙΑΣ INTERNAL CORNER SIZES
ΔΙΑΣΤΑΣΕΙΣ ΕΣΩΤΕΡΙΚΗΣ ΓΩΝΙΑΣ 90 90 INTERNAL CORNER SIZES ΟΠΤΙΚΗ PERSPECTIVE ΠΑΝΩ ΟΨΗ TOP VIEW ΔΙΑΣΤΑΣΕΙΣ ΡΑΦΙΩΝ SHELF DIMENSIONS T1 ΜΕΓΙΣΤΟ ΕΠΙΤΡΕΠΟΜΕΝΟ ΦΟΡΤΙΟ (1) MAXIMUM LOADING CAPACITIES (1) ΤΥΠΙΚΑ
Διαβάστε περισσότεραSecond Order Partial Differential Equations
Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y
Διαβάστε περισσότεραA study on generalized absolute summability factors for a triangular matrix
Proceedigs of the Estoia Acadey of Scieces, 20, 60, 2, 5 20 doi: 0.376/proc.20.2.06 Available olie at www.eap.ee/proceedigs A study o geeralized absolute suability factors for a triagular atrix Ere Savaş
Διαβάστε περισσότερα; +302 ; +313; +320,.
1.,,*+, - +./ +/2 +, -. ; +, - +* cm : Key words: snow-water content, surface soil, snow type, water permeability, water retention +,**. +,,**/.. +30- +302 ; +302 ; +313; +320,. + *+, *2// + -.*, **. **+.,
Διαβάστε περισσότεραMean bond enthalpy Standard enthalpy of formation Bond N H N N N N H O O O
Q1. (a) Explain the meaning of the terms mean bond enthalpy and standard enthalpy of formation. Mean bond enthalpy... Standard enthalpy of formation... (5) (b) Some mean bond enthalpies are given below.
Διαβάστε περισσότεραComparison of Evapotranspiration between Indigenous Vegetation and Invading Vegetation in a Bog
J. Jpn. Soc. Soil Phys. No. +*-, p.-3.1,**0 ** * *** Comparison of Evapotranspiration between Indigenous Vegetation and Invading Vegetation in a Bog Toshiki FUJIMOTO*, Ippei IIYAMA*, Mai SAKAI*, Osamu
Διαβάστε περισσότεραderivation of the Laplacian from rectangular to spherical coordinates
derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used
Διαβάστε περισσότεραSolutions to Exercise Sheet 5
Solutions to Eercise Sheet 5 jacques@ucsd.edu. Let X and Y be random variables with joint pdf f(, y) = 3y( + y) where and y. Determine each of the following probabilities. Solutions. a. P (X ). b. P (X
Διαβάστε περισσότερα1 1 1 2 1 2 2 1 43 123 5 122 3 1 312 1 1 122 1 1 1 1 6 1 7 1 6 1 7 1 3 4 2 312 43 4 3 3 1 1 4 1 1 52 122 54 124 8 1 3 1 1 1 1 1 152 1 1 1 1 1 1 152 1 5 1 152 152 1 1 3 9 1 159 9 13 4 5 1 122 1 4 122 5
Διαβάστε περισσότεραBoundary-Fitted Coordinates!
Computatoal Flud Damcs I Computatoal Flud Damcs I http://users.wp.edu/~gretar/me.html! Computatoal Methods or Domas wth! Comple Boudares-I! Grétar Trggvaso! Sprg 00! For most egeerg problems t s ecessar
Διαβάστε περισσότεραΣΤΑΤΙΣΤΙΚΗ ΕΠΙΧΕΙΡΗΣΕΩΝ ΕΙΔΙΚΑ ΘΕΜΑΤΑ. Κεφάλαιο 13. Συμπεράσματα για τη σύγκριση δύο πληθυσμών
ΤΕΧΝΟΛΟΓΙΚΟ ΕΚΠΑΙΔΕΥΤΙΚΟ ΙΔΡΥΜΑ ΔΥΤΙΚΗΣ ΕΛΛΑΔΑΣ ΤΜΗΜΑ ΔΙΟΙΚΗΣΗΣ ΕΠΙΧΕΙΡΗΣΕΩΝ ΠΑΤΡΑΣ Εργαστήριο Λήψης Αποφάσεων & Επιχειρησιακού Προγραμματισμού Καθηγητής Ι. Μητρόπουλος ΣΤΑΤΙΣΤΙΚΗ ΕΠΙΧΕΙΡΗΣΕΩΝ ΕΙΔΙΚΑ ΘΕΜΑΤΑ
Διαβάστε περισσότεραΜενύχτα, Πιπερίγκου, Σαββάτης. ΒΙΟΣΤΑΤΙΣΤΙΚΗ Εργαστήριο 5 ο
Κατανομές Στατιστικών Συναρτήσεων Δύο ανεξάρτητα δείγματα από κανονική κατανομή Έστω Χ= ( Χ, Χ,..., Χ ) τ.δ. από Ν( µ, σ ) μεγέθους n και 1 n 1 1 Y = (Y, Y,..., Y ) τ.δ. από Ν( µ, σ ) 1 n 1 Χ Y ( µ µ )
Διαβάστε περισσότερα1 Decay Scheme. 2 Nuclear Data. 2.1 α Transitions
1 Decay Scheme Cf- disintegrates by alpha emissions mainly to the Cm-248 ground state level, and by spontaneous fission for 3,086(8) %. The average number of neutrons emitted by spontaneous fission is:
Διαβάστε περισσότεραn r f ( n-r ) () x g () r () x (1.1) = Σ g() x = Σ n f < -n+ r> g () r -n + r dx r dx n + ( -n,m) dx -n n+1 1 -n -1 + ( -n,n+1)
8 Higher Derivative of the Product of Two Fuctios 8. Leibiz Rule about the Higher Order Differetiatio Theorem 8.. (Leibiz) Whe fuctios f ad g f g are times differetiable, the followig epressio holds. r
Διαβάστε περισσότεραΓιάννης Σαριδάκης Σχολή Μ.Π.Δ., Πολυτεχνείο Κρήτης
2 η Διάλεξη Ακολουθίες 29 Νοεµβρίου 206 Γιάννης Σαριδάκης Σχολή Μ.Π.Δ., Πολυτεχνείο Κρήτης ΑΠΕΙΡΟΣΤΙΚΟΣ ΛΟΓΙΣΜΟΣ, ΤΟΜΟΣ Ι - Fiey R.L. / Weir M.D. / Giordao F.R. Πανεπιστημιακές Εκδόσεις Κρήτης 2 Όρια Ακολουθιών
Διαβάστε περισσότεραST5224: Advanced Statistical Theory II
ST5224: Advanced Statistical Theory II 2014/2015: Semester II Tutorial 7 1. Let X be a sample from a population P and consider testing hypotheses H 0 : P = P 0 versus H 1 : P = P 1, where P j is a known
Διαβάστε περισσότεραSection 8.3 Trigonometric Equations
99 Section 8. Trigonometric Equations Objective 1: Solve Equations Involving One Trigonometric Function. In this section and the next, we will exple how to solving equations involving trigonometric functions.
Διαβάστε περισσότεραInverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------
Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin
Διαβάστε περισσότεραThe Simply Typed Lambda Calculus
Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and
Διαβάστε περισσότερα