INTEGRATION OF THE NORMAL DISTRIBUTION CURVE
|
|
- Έρις Ελευθεριάδης
- 8 χρόνια πριν
- Προβολές:
Transcript
1 INTEGRATION OF THE NORMAL DISTRIBUTION CURVE By Tom Irvie March 3, 999 Itroductio May processes have a ormal probability distributio. Broadbad radom vibratio is a example. The purpose of this report is to derive a formula for itegratig the ormal distributio curve. This effort is eeded due to the limitatios of statistical tables published i textbooks. Derivatio From Referece, the probability desity fuctio ( x;µ,σ) give by of a ormal distributio is x µ σ ( x; µ, σ), < x < σ π () here x is a cotiuous radom variable, µ is the mea, σ is the stadard deviatio. The ormal distributio curve has the shape sho i Figure. For this distributio, the probability P that the radom variable X has a value betee x x ad x x is obtaied by itegratig the area uder the probability desity curve. x < σ () σ π x ( x X < x ) ( x; µ, )dx P x x µ < x (3) σ π σ ( x X < x ) dx P No trasform the data via a radom variable Z.
2 µ Z X σ (4) dz dx σ (5) By substitutio, σ + µ σ σ + µ (6a) π (( + µ ) < ( σ Z + µ ) < ( σ + µ ) d P No assume a ero mea ad a uity stadard deviatio. < (6b) π ( Z < ) d P Note that the ormal distributio is symmetric about the mea. No cosider the case here > >. Further reuire that each limit be euidistat from the ero mea. Thus, -. Euatio (6c) ca be restated as (7) π ( < Z < ) d P Let (8) d d (9) () π ( < Z < ) { }d P here There are a umber of euivalet methods for evaluatig the itegral i euatio (). Oe method is by use of the error fuctio. The method used here is based o the icomplete gamma fuctio P(a,), as give i Referece.
3 P ( a, ) ( a, ) ( a) ( a) γ [ ( )] ( a t t ) [ ] dt, a > () Note that the gamma fuctio itself is a stadard mathematical fuctio defied as ( ) x x [ t ] ( t) dt, x > () a γ ( a,) [ t ] ( t) dt (3) No let u t (4) udu dt (5) By substitutio, (a ) (, ) [ u] [ ( u )][ u ] γ a du (6) (a ) (, ) [ ( u )][ u ] γ a du (7) No let a/. γ, ( ) u du (8) From Referece, the γ ( a,) fuctio ca be represeted i series form as a [ ][ ] ( a) (,) ( ) γ a ( ) (9) a + + γ, [ ( ) ][ ] 3 + () 3
4 4 Euatig the respective right-had-sides of euatio (8) ad (). ( ) ( ) [ ][ ] + 3 du u () Divide each side by. π ( ) ( ) [ ][ ] + π π 3 du u () No let y (3) ( ) ( ) [ ][ ] + π π y y 3 y y du u (4) Recall euatio () restated here as euatio (5). ( ) { }d Z P π < < (5) The right side of euatio (5) matches the left side of euatio (4) for u ad y. ( ) ( ) [ ][ ], 3 Z P + π < < (6) Thus, the probability of the radom variable Z ca be calculated via (6).
5 Note that π (7) Furthermore, the gamma fuctio follos a recursive relatioship, as give i Referece. ( + ) ( ) (8) Euatios (7) ad (8) allo for a simple computer program implemetatio of euatio (6). Tables of probability values based o this euatio are give i Appedix A. Examples. A certai maufacturig process yields a reliability of 6σ ith a ero mea. Ho may defects are ected per oe millio parts? The Table i Appedix A shos that the probability of a part fallig outside of the absolute value of 6σ is e-9. Thus, the ected umber of part failures is., hich is essetially ero.. A.5σ shift i the mea occurs i the previous maufacturig process. Ho may defects are ected per oe millio parts cosiderig this shift? The limits are thus -7.5σ to +4.5σ. Note that the values could be iterchaged due to symmetry. For practical purposes, there is ero probability of a occurrece less tha -7.5σ. The Table i Appedix A shos that the probability of a part fallig outside of the absolute value of 4.5σ is E-6. The probability from +4.5σ to ifiity is oe-half this amout, or E-6. The umber of ected defects i a lot of oe millio is thus 3.4, rouded to to sigificat digits. Refereces. R. Walpole ad R. Myers, Probability ad Statistics for Egieers ad Scietists, d editio, Macmilla, Ne York, William Press, et al, Numerical Recipes The Art of Scietific Computig, Cambridge Uiversity Press, Cambridge, UK,
6 Normal Distributio Curve Area uder the curve (x; µ, σ) -σ µ σ Figure. x 6
7 E E E E E E E E E E E E E E E E E E E E E E E E E E-.4.34E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E- λ P[-λ < Z < λ] P[ Z > λ] E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E- 4.67E E E E E E E E E E E E E E E E E E E E E E E- 7
8 E E E E E E E E E E E E E E E E E E E- 3.36E E E E E E E E E E-.848E E E E-.733E E E E E E E E E E E E E E-.4969E E-.385E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E- λ P[-λ < Z < λ] P[ Z > λ] E E E-.5779E E E E E E E E E E E E E E E E E E E E-.6679E E E E-.456E E E E-.645E E E E E E E E E E-.5377E E-.3497E E-.567E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E- 8
9 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-.7563E E E E E E-.5999E E E E-.3858E E E E E E-.366E E-.448E E E E E E-.9865E E E E E E E E E- λ P[-λ < Z < λ] P[ Z > λ] E E E E E E E E E-.5557E E E E E E E E E E-.3535E E E E E E E E-.736E E E E-.4657E E E E-.7799E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-3 9
10 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-.7595E E E E E E E E-.8854E E E E E E E E E E E E E E E E E E E E E E-.3798E E-.9597E E-.5458E E-.44E E E E E E E E E E E E E E E-4 λ P[-λ < Z < λ] P[ Z > λ] E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E- 4.73E E E E E E E E E E E E E E E E E E-.834E E E E-.6439E E-.5548E E E E E E-.4545E E E E E E E E E E-.8455E E E E E E E E E E E E E E E-4
11 E E E E E-.3343E E-.8785E E E E E E E E-.44E E E E- 9.96E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-5 λ P[-λ < Z < λ] P[ Z > λ] E E E E E-.569E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-.6649E E E E E E E E-.3789E E E E E E E-6
12 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-.8859E E-.948E E E E E E E E E E E E-.599E-7 λ P[-λ < Z < λ] P[ Z > λ] E E E E E E E-.3636E E-.5868E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-.7696E E E E-.3668E E E E-.8963E E-.756E E E E E E E E E E E E E E E E E E E-8
13 E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E-.8595E E E E E E E E E E E E E-9 3
DERIVATION OF MILES EQUATION Revision D
By Tom Irvie Email: tomirvie@aol.com July, DERIVATION OF MILES EQUATION Revisio D Itroductio The obective is to derive Miles equatio. This equatio gives the overall respose of a sigle-degree-of-freedom
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 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 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 περισσότεραMath 6 SL Probability Distributions Practice Test Mark Scheme
Math 6 SL Probability Distributions Practice Test Mark Scheme. (a) Note: Award A for vertical line to right of mean, A for shading to right of their vertical line. AA N (b) evidence of recognizing symmetry
Διαβάστε περισσότεραOn Generating Relations of Some Triple. Hypergeometric Functions
It. Joural of Math. Aalysis, Vol. 5,, o., 5 - O Geeratig Relatios of Some Triple Hypergeometric Fuctios Fadhle B. F. Mohse ad Gamal A. Qashash Departmet of Mathematics, Faculty of Educatio Zigibar Ade
Διαβάστε περισσότεραAreas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
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 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 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 περισσότεραAreas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
Διαβάστε περισσότεραThe Heisenberg Uncertainty Principle
Chemistry 460 Sprig 015 Dr. Jea M. Stadard March, 015 The Heiseberg Ucertaity Priciple A policema pulls Werer Heiseberg over o the Autobah for speedig. Policema: Sir, do you kow how fast you were goig?
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 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 περισσότεραCHAPTER 103 EVEN AND ODD FUNCTIONS AND HALF-RANGE FOURIER SERIES
CHAPTER 3 EVEN AND ODD FUNCTIONS AND HALF-RANGE FOURIER SERIES EXERCISE 364 Page 76. Determie the Fourier series for the fuctio defied by: f(x), x, x, x which is periodic outside of this rage of period.
Διαβάστε περισσότεραExample Sheet 3 Solutions
Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note
Διαβάστε περισσότερα3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β
3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle
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 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 περισσότερα9.09. # 1. Area inside the oval limaçon r = cos θ. To graph, start with θ = 0 so r = 6. Compute dr
9.9 #. Area inside the oval limaçon r = + cos. To graph, start with = so r =. Compute d = sin. Interesting points are where d vanishes, or at =,,, etc. For these values of we compute r:,,, and the values
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 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 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 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 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 περισσότερα5.4 The Poisson Distribution.
The worst thing you can do about a situation is nothing. Sr. O Shea Jackson 5.4 The Poisson Distribution. Description of the Poisson Distribution Discrete probability distribution. The random variable
Διαβάστε περισσότεραLecture 17: Minimum Variance Unbiased (MVUB) Estimators
ECE 830 Fall 2011 Statistical Sigal Processig istructor: R. Nowak, scribe: Iseok Heo Lecture 17: Miimum Variace Ubiased (MVUB Estimators Ultimately, we would like to be able to argue that a give estimator
Διαβάστε περισσότεραSolve the difference equation
Solve the differece equatio Solutio: y + 3 3y + + y 0 give tat y 0 4, y 0 ad y 8. Let Z{y()} F() Taig Z-trasform o both sides i (), we get y + 3 3y + + y 0 () Z y + 3 3y + + y Z 0 Z y + 3 3Z y + + Z y
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 περισσότεραBessel function for complex variable
Besse fuctio for compex variabe Kauhito Miuyama May 4, 7 Besse fuctio The Besse fuctio Z ν () is the fuctio wich satisfies + ) ( + ν Z ν () =. () Three kids of the soutios of this equatio are give by {
Διαβάστε περισσότερα6.3 Forecasting ARMA processes
122 CHAPTER 6. ARMA MODELS 6.3 Forecasting ARMA processes The purpose of forecasting is to predict future values of a TS based on the data collected to the present. In this section we will discuss a linear
Διαβάστε περισσότεραFinite Field Problems: Solutions
Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The
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 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 περισσότεραIntroduction of Numerical Analysis #03 TAGAMI, Daisuke (IMI, Kyushu University)
Itroductio of Numerical Aalysis #03 TAGAMI, Daisuke (IMI, Kyushu Uiversity) web page of the lecture: http://www2.imi.kyushu-u.ac.jp/~tagami/lec/ Strategy of Numerical Simulatios Pheomea Error modelize
Διαβάστε περισσότεραEcon 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1
Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test
Διαβάστε περισσότεραGeodesic Equations for the Wormhole Metric
Geodesic Equations for the Wormhole Metric Dr R Herman Physics & Physical Oceanography, UNCW February 14, 2018 The Wormhole Metric Morris and Thorne wormhole metric: [M S Morris, K S Thorne, Wormholes
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 περισσότεραReview Exercises for Chapter 7
8 Chapter 7 Integration Techniques, L Hôpital s Rule, and Improper Integrals 8. For n, I d b For n >, I n n u n, du n n d, dv (a) d b 6 b 6 (b) (c) n d 5 d b n n b n n n d, v d 6 5 5 6 d 5 5 b d 6. b 6
Διαβάστε περισσότεραLAD Estimation for Time Series Models With Finite and Infinite Variance
LAD Estimatio for Time Series Moels With Fiite a Ifiite Variace Richar A. Davis Colorao State Uiversity William Dusmuir Uiversity of New South Wales 1 LAD Estimatio for ARMA Moels fiite variace ifiite
Διαβάστε περισσότεραStatistical Inference I Locally most powerful tests
Statistical Inference I Locally most powerful tests Shirsendu Mukherjee Department of Statistics, Asutosh College, Kolkata, India. shirsendu st@yahoo.co.in So far we have treated the testing of one-sided
Διαβάστε περισσότεραHISTOGRAMS AND PERCENTILES What is the 25 th percentile of a histogram? What is the 50 th percentile for the cigarette histogram?
HISTOGRAMS AND PERCENTILES What is the 25 th percentile of a histogram? The point on the horizontal axis such that of the area under the histogram lies to the left of that point (and to the right) What
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 περισσότεραLecture 34 Bootstrap confidence intervals
Lecture 34 Bootstrap confidence intervals Confidence Intervals θ: an unknown parameter of interest We want to find limits θ and θ such that Gt = P nˆθ θ t If G 1 1 α is known, then P θ θ = P θ θ = 1 α
Διαβάστε περισσότεραMath221: HW# 1 solutions
Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin
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 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 περισσότεραΣτα επόμενα θεωρούμε ότι όλα συμβαίνουν σε ένα χώρο πιθανότητας ( Ω,,P) Modes of convergence: Οι τρόποι σύγκλισης μιας ακολουθίας τ.μ.
Στα πόμνα θωρούμ ότι όλα συμβαίνουν σ ένα χώρο πιθανότητας ( Ω,,). Modes of covergece: Οι τρόποι σύγκλισης μιας ακολουθίας τ.μ. { } ίναι οι ξής: σ μια τ.μ.. Ισχυρή σύγκλιση strog covergece { } lim = =.
Διαβάστε περισσότεραOrdinal Arithmetic: Addition, Multiplication, Exponentiation and Limit
Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ting Zhang Stanford May 11, 2001 Stanford, 5/11/2001 1 Outline Ordinal Classification Ordinal Addition Ordinal Multiplication Ordinal
Διαβάστε περισσότεραThe Normal and Lognormal Distributions
The Normal and Lognormal Distributions John Norstad j-norstad@northwestern.edu http://www.norstad.org February, 999 Updated: November 3, Abstract The basic properties of the normal and lognormal distributions,
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 περισσότεραApproximation of distance between locations on earth given by latitude and longitude
Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth
Διαβάστε περισσότεραBy R.L. Snyder (Revised March 24, 2005)
Humidity Conversion By R.L. Snyder (Revised March 24, 2005) This Web page provides the equations used to make humidity conversions and tables o saturation vapor pressure. For a pd ile o this document,
Διαβάστε περισσότεραHomework 8 Model Solution Section
MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx
Διαβάστε περισσότεραProbability theory STATISTICAL MODELING OF MULTIVARIATE EXTREMES, FMSN15/MASM23 TABLE OF FORMULÆ. Basic probability theory
Lud Istitute of Techology Cetre for Mathematical Scieces Mathematical Statistics STATISTICAL MODELING OF MULTIVARIATE EXTREMES, FMSN5/MASM3 Probability theory Basic probability theory TABLE OF FORMULÆ
Διαβάστε περισσότεραP AND P. P : actual probability. P : risk neutral probability. Realtionship: mutual absolute continuity P P. For example:
(B t, S (t) t P AND P,..., S (p) t ): securities P : actual probability P : risk neutral probability Realtionship: mutual absolute continuity P P For example: P : ds t = µ t S t dt + σ t S t dw t P : ds
Διαβάστε περισσότεραDERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C
DERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C By Tom Irvine Email: tomirvine@aol.com August 6, 8 Introduction The obective is to derive a Miles equation which gives the overall response
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 περισσότερα2. Let H 1 and H 2 be Hilbert spaces and let T : H 1 H 2 be a bounded linear operator. Prove that [T (H 1 )] = N (T ). (6p)
Uppsala Universitet Matematiska Institutionen Andreas Strömbergsson Prov i matematik Funktionalanalys Kurs: F3B, F4Sy, NVP 2005-03-08 Skrivtid: 9 14 Tillåtna hjälpmedel: Manuella skrivdon, Kreyszigs bok
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 περισσότεραLecture 2. Soundness and completeness of propositional logic
Lecture 2 Soundness and completeness of propositional logic February 9, 2004 1 Overview Review of natural deduction. Soundness and completeness. Semantics of propositional formulas. Soundness proof. Completeness
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 περισσότεραSection 7.6 Double and Half Angle Formulas
09 Section 7. Double and Half Angle Fmulas To derive the double-angles fmulas, we will use the sum of two angles fmulas that we developed in the last section. We will let α θ and β θ: cos(θ) cos(θ + θ)
Διαβάστε περισσότεραPartial Differential Equations in Biology The boundary element method. March 26, 2013
The boundary element method March 26, 203 Introduction and notation The problem: u = f in D R d u = ϕ in Γ D u n = g on Γ N, where D = Γ D Γ N, Γ D Γ N = (possibly, Γ D = [Neumann problem] or Γ N = [Dirichlet
Διαβάστε περισσότεραΕγχειρίδια Μαθηµατικών και Χταποδάκι στα Κάρβουνα
[ 1 ] Πανεπιστήµιο Κύπρου Εγχειρίδια Μαθηµατικών και Χταποδάκι στα Κάρβουνα Νίκος Στυλιανόπουλος, Πανεπιστήµιο Κύπρου Λευκωσία, εκέµβριος 2009 [ 2 ] Πανεπιστήµιο Κύπρου Πόσο σηµαντική είναι η απόδειξη
Διαβάστε περισσότεραExercises to Statistics of Material Fatigue No. 5
Prof. Dr. Christine Müller Dipl.-Math. Christoph Kustosz Eercises to Statistics of Material Fatigue No. 5 E. 9 (5 a Show, that a Fisher information matri for a two dimensional parameter θ (θ,θ 2 R 2, can
Διαβάστε περισσότεραο αεροσολσ σλοω χλιµατιχ ωαρµινγ? Ηαλτινγ τηε σπρεαδ οφ ΑΙ Σ. Χαν παρτιχλε πηψσιχσ χοµε βαχκ?
ΦΕΒΡΥΑΡΨ 1994 3.95 ο αεροσολσ σλοω χλιµατιχ ωαρµινγ? Ηαλτινγ τηε σπρεαδ οφ ΑΙ Σ. Χαν παρτιχλε πηψσιχσ χοµε βαχκ? ιγιταλ φοργερψ χαν χρεατε πηοτογραπηιχ εϖιδενχε φορ εϖεντσ τηατ νεϖερ ηαππενεδ. Φεβρυαρψ
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 περισσότεραOn Inclusion Relation of Absolute Summability
It. J. Cotemp. Math. Scieces, Vol. 5, 2010, o. 53, 2641-2646 O Iclusio Relatio of Absolute Summability Aradhaa Dutt Jauhari A/66 Suresh Sharma Nagar Bareilly UP) Idia-243006 aditya jauhari@rediffmail.com
Διαβάστε περισσότεραΠαραμύθια τησ Χαλιμϊσ, τομ. A Σελύδα 1
Παραμύθια τησ Χαλιμϊσ, τομ. A Σελύδα 1 Παραμύθια τησ Χαλιμϊσ, τομ. A Σελύδα 2 Dervish Abu Bekr, «Παραμύθια τησ Χαλιμϊσ, τομ. Α» Ιούνιοσ 2013 Φωτo εξωφύλλου: Βαςιλεύα Αςπαςύα Μαςούρα Επιμϋλεια ϋκδοςησ:
Διαβάστε περισσότερα2 Composition. Invertible Mappings
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,
Διαβάστε περισσότεραNMBTC.COM /
Common Common Vibration Test:... Conforms to JIS C 60068-2-6, Amplitude: 1.5mm, Frequency 10 to 55 Hz, 1 hour in each of the X, Y and Z directions. Shock Test:...Conforms to JIS C 60068-2-27, Acceleration
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 περισσότεραAREAS AND LENGTHS IN POLAR COORDINATES. 25. Find the area inside the larger loop and outside the smaller loop
SECTIN 9. AREAS AND LENGTHS IN PLAR CRDINATES 9. AREAS AND LENGTHS IN PLAR CRDINATES A Click here for answers. S Click here for solutions. 8 Find the area of the region that is bounded by the given curve
Διαβάστε περισσότεραw o = R 1 p. (1) R = p =. = 1
Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 205 ιδάσκων : Α. Μουχτάρης Τριτη Σειρά Ασκήσεων Λύσεις Ασκηση 3. 5.2 (a) From the Wiener-Hopf equation we have:
Διαβάστε περισσότεραPaper Reference. Paper Reference(s) 6665/01 Edexcel GCE Core Mathematics C3 Advanced. Thursday 11 June 2009 Morning Time: 1 hour 30 minutes
Centre No. Candidate No. Paper Reference(s) 6665/01 Edexcel GCE Core Mathematics C3 Advanced Thursday 11 June 2009 Morning Time: 1 hour 30 minutes Materials required for examination Mathematical Formulae
Διαβάστε περισσότεραProblem Set 3: Solutions
CMPSCI 69GG Applied Information Theory Fall 006 Problem Set 3: Solutions. [Cover and Thomas 7.] a Define the following notation, C I p xx; Y max X; Y C I p xx; Ỹ max I X; Ỹ We would like to show that C
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 περισσότεραΠτυχιακή Εργασία. Παραδοσιακά Προϊόντα Διατροφική Αξία και η Πιστοποίηση τους
ΑΛΕΞΑΝΔΡΕΙΟ ΤΕΧΝΟΛΟΓΙΚΟ ΕΚΠΑΙΔΕΥΤΙΚΟ ΙΔΡΥΜΑ ΣΧΟΛΗ ΤΕΧΝΟΛΟΓΙΑΣ ΤΡΟΦΙΜΩΝ ΚΑΙ ΔΙΑΤΡΟΦΗΣ ΤΜΗΜΑ ΔΙΑΤΡΟΦΗΣ ΚΑΙ ΔΙΑΙΤΟΛΟΓΙΑΣ Πτυχιακή Εργασία Παραδοσιακά Προϊόντα Διατροφική Αξία και η Πιστοποίηση τους Εκπόνηση:
Διαβάστε περισσότεραProbability and Random Processes (Part II)
Probability and Random Processes (Part II) 1. If the variance σ x of d(n) = x(n) x(n 1) is one-tenth the variance σ x of a stationary zero-mean discrete-time signal x(n), then the normalized autocorrelation
Διαβάστε περισσότερα2 2 2 The correct formula for the cosine of the sum of two angles is given by the following theorem.
5 TRIGONOMETRIC FORMULAS FOR SUMS AND DIFFERENCES The fundamental trignmetric identities cnsidered earlier express relatinships amng trignmetric functins f a single variable In this sectin we develp trignmetric
Διαβάστε περισσότερα2 2 2 The correct formula for the cosine of the sum of two angles is given by the following theorem.
5 TRIGONOMETRIC FORMULAS FOR SUMS AND DIFFERENCES The fundamental trignmetric identities cnsidered earlier express relatinships amng trignmetric functins f a single variable In this sectin we develp trignmetric
Διαβάστε περισσότεραVBA Microsoft Excel. J. Comput. Chem. Jpn., Vol. 5, No. 1, pp (2006)
J. Comput. Chem. Jpn., Vol. 5, No. 1, pp. 29 38 (2006) Microsoft Excel, 184-8588 2-24-16 e-mail: yosimura@cc.tuat.ac.jp (Received: July 28, 2005; Accepted for publication: October 24, 2005; Published on
Διαβάστε περισσότερα: Monte Carlo EM 313, Louis (1982) EM, EM Newton-Raphson, /. EM, 2 Monte Carlo EM Newton-Raphson, Monte Carlo EM, Monte Carlo EM, /. 3, Monte Carlo EM
2008 6 Chinese Journal of Applied Probability and Statistics Vol.24 No.3 Jun. 2008 Monte Carlo EM 1,2 ( 1,, 200241; 2,, 310018) EM, E,,. Monte Carlo EM, EM E Monte Carlo,. EM, Monte Carlo EM,,,,. Newton-Raphson.
Διαβάστε περισσότεραECE598: Information-theoretic methods in high-dimensional statistics Spring 2016
ECE598: Information-theoretic methods in high-dimensional statistics Spring 06 Lecture 7: Information bound Lecturer: Yihong Wu Scribe: Shiyu Liang, Feb 6, 06 [Ed. Mar 9] Recall the Chi-squared divergence
Διαβάστε περισσότεραPotential Dividers. 46 minutes. 46 marks. Page 1 of 11
Potential Dividers 46 minutes 46 marks Page 1 of 11 Q1. In the circuit shown in the figure below, the battery, of negligible internal resistance, has an emf of 30 V. The pd across the lamp is 6.0 V and
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 περισσότεραDuPont Suva 95 Refrigerant
Technical Information T-95 SI DuPont Suva refrigerants Thermodynamic Properties of DuPont Suva 95 Refrigerant (R-508B) The DuPont Oval Logo, The miracles of science, and Suva, are trademarks or registered
Διαβάστε περισσότεραOutline. M/M/1 Queue (infinite buffer) M/M/1/N (finite buffer) Networks of M/M/1 Queues M/G/1 Priority Queue
Queueig Aalysis Outlie M/M/ Queue (ifiite buffer M/M//N (fiite buffer M/M// (Erlag s B forula M/M/ (Erlag s C forula Networks of M/M/ Queues M/G/ Priority Queue M/M/ M: Markovia/Meoryless Arrival process
Διαβάστε περισσότεραSolution Concepts. Παύλος Στ. Εφραιµίδης. Τοµέας Λογισµικού και Ανάπτυξης Εφαρµογών Τµήµα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών
Παύλος Στ. Εφραιµίδης Τοµέας Λογισµικού και Ανάπτυξης Εφαρµογών Τµήµα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών Ισορροπία Nash αγνές στρατηγικές µικτές στρατηγικές Κυρίαρχες στρατηγικές Rationalizability
Διαβάστε περισσότεραΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΤΜΗΜΑ ΟΔΟΝΤΙΑΤΡΙΚΗΣ ΕΡΓΑΣΤΗΡΙΟ ΟΔΟΝΤΙΚΗΣ ΚΑΙ ΑΝΩΤΕΡΑΣ ΠΡΟΣΘΕΤΙΚΗΣ
ΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΤΜΗΜΑ ΟΔΟΝΤΙΑΤΡΙΚΗΣ ΕΡΓΑΣΤΗΡΙΟ ΟΔΟΝΤΙΚΗΣ ΚΑΙ ΑΝΩΤΕΡΑΣ ΠΡΟΣΘΕΤΙΚΗΣ ΣΥΓΚΡΙΤΙΚΗ ΜΕΛΕΤΗ ΤΗΣ ΣΥΓΚΡΑΤΗΤΙΚΗΣ ΙΚΑΝΟΤΗΤΑΣ ΟΡΙΣΜΕΝΩΝ ΠΡΟΚΑΤΑΣΚΕΥΑΣΜΕΝΩΝ ΣΥΝΔΕΣΜΩΝ ΑΚΡΙΒΕΙΑΣ
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 περισσότεραDuPont Suva 95 Refrigerant
Technical Information T-95 ENG DuPont Suva refrigerants Thermodynamic Properties of DuPont Suva 95 Refrigerant (R-508B) The DuPont Oval Logo, The miracles of science, and Suva, are trademarks or registered
Διαβάστε περισσότερα«ΙΕΡΕΥΝΗΣΗ ΤΩΝ ΠΑΡΑΓΟΝΤΩΝ ΠΟΥ ΕΠΙ ΡΟΥΝ ΣΤΗΝ ΑΦΟΣΙΩΣΗ ΤΟΥ ΠΕΛΑΤΗ ΣΕ ΕΠΩΝΥΜΑ ΠΡΟΪΟΝΤΑ ΤΡΟΦΙΜΩΝ. Η ΠΕΡΙΠΤΩΣΗ ΤΩΝ ΕΠΩΝΥΜΩΝ ΓΑΛΑΚΤΟΚΟΜΙΚΩΝ ΠΡΟΪΟΝΤΩΝ»
ΓΕΩΠΟΝΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΤΜΗΜΑ ΑΓΡΟΤΙΚΗΣ ΟΙΚΟΝΟΜΙΑΣ ΚΑΙ ΑΝΑΠΤΥΞΗΣ ΠΡΟΓΡΑΜΜΑ ΜΕΤΑΠΤΥΧΙΑΚΩΝ ΣΠΟΥ ΩΝ ΟΡΓΑΝΩΣΗ ΚΑΙ ΙΟΙΚΗΣΗ ΕΠΙΧΕΙΡΗΣΕΩΝ ΤΡΟΦΙΜΩΝ & ΓΕΩΡΓΙΑΣ ΣΥΝΕΡΓΑΖΟΜΕΝΟ ΤΜΗΜΑ: ΕΠΙΣΤΗΜΗΣ & ΤΕΧΝΟΛΟΓΙΑΣ
Διαβάστε περισσότεραAdditional Results for the Pareto/NBD Model
Additional Results for the Pareto/NBD Model Peter S. Fader www.petefader.com Bruce G. S. Hardie www.brucehardie.com January 24 Abstract This note derives expressions for i) the raw moments of the posterior
Διαβάστε περισσότεραΜία path-based προσέγγιση στατιστικής ανάλυσης καθυστέρησης ψηφιακών κυκλωμάτων
ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΙΑΣ - ΠΟΛΥΤΕΧΝΙΚΗ ΣΧΟΛΗ ΤΜΗΜΑ ΜΗΧΑΝΙΚΩΝ Η/Υ ΤΗΛΕΠΙΚΟΙΝΩΝΙΩΝ ΚΑΙ ΔΙΚΤΥΩΝ ΠΤΥΧΙΑΚΗ ΕΡΓΑΣΙΑ Χατζηπαρασκευάς Γεώργιος Μία path-based προσέγγιση στατιστικής ανάλυσης καθυστέρησης ψηφιακών
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 περισσότεραCRASH COURSE IN PRECALCULUS
CRASH COURSE IN PRECALCULUS Shiah-Sen Wang The graphs are prepared by Chien-Lun Lai Based on : Precalculus: Mathematics for Calculus by J. Stuwart, L. Redin & S. Watson, 6th edition, 01, Brooks/Cole Chapter
Διαβάστε περισσότεραORDINAL ARITHMETIC JULIAN J. SCHLÖDER
ORDINAL ARITHMETIC JULIAN J. SCHLÖDER Abstract. We define ordinal arithmetic and show laws of Left- Monotonicity, Associativity, Distributivity, some minor related properties and the Cantor Normal Form.
Διαβάστε περισσότεραInstruction Execution Times
1 C Execution Times InThisAppendix... Introduction DL330 Execution Times DL330P Execution Times DL340 Execution Times C-2 Execution Times Introduction Data Registers This appendix contains several tables
Διαβάστε περισσότερα