IUK 208 EXPERIMENTAL DESIGN WITH COMPUTER APPLICATIONS [REKABENTUK UJIKAJI DENGAN APLIKASI KOMPUTER]

MAA 111 Algebra for Sciences Students [Aljabar untuk Pelajar Sains]

UNIVERSITI SAINS MALAYSIA Second Semester Exmintion 20/202 Acdemic Session June 202 MAA Algebr for Sciences Students [Aljbr untuk Peljr Sins] Durtion : hours [Ms : jm] Plese check tht this exmintion pper

REG Teknologi Infrastruktur

UVERST SAS MALASA Peperksn Semester Pertm Sdng Akdemk 24/25 ktober 24 REG 265 - Teknolog nfrstruktur Ms : 3 jm Sl pstkn bhw kerts peperksn n mengndung TGA BELAS muk surt yng teretk sebelum nd memulkn peperksn

UNIVERSITI MALAYSIA PERLIS. EQT 102 Engineering Mathematics II [Matematik Kejuruteraan II]

SUIT UNIVERSITI MAAYSIA PERIS Peperikn Akhir Semeter Pertm Sidng Akdemik 15/16 Jnuri 16 EQT 1 Engineering Mthemtic II [Mtemtik Kejurutern II] M : 3 jm Plee mke ure tht thi quetion pper h SEVEN (7) printed

Applied Statistics Qualifier Examination

Appled Sttstcs Qulfer Exmnton Qul_june_8 Fll 8 Instructons: () The exmnton contns 4 Questons. You re to nswer 3 out of 4 of them. () You my use ny books nd clss notes tht you mght fnd helpful n solvng

Chapter 5 Supplemental Text Material R S T. ij i j ij ijk

Chpter 5 Supplementl Text Mterl 5-. Expected Men Squres n the Two-fctor Fctorl Consder the two-fctor fxed effects model y = µ + τ + β + ( τβ) + ε k R S T =,,, =,,, k =,,, n gven s Equton (5-) n the textook.

IUK 208 EXPERIMENTAL DESIGN WITH COMPUTER APPLICATIONS [REKABENTUK UJIKAJI DENGAN APLIKASI KOMPUTER]

UNIVERSITI SAINS MALAYSIA Second Semester Examination 2009/2010 Academic Session April/Ma 2010 IUK 208 EXPERIMENTAL DESIGN WITH COMPUTER APPLICATIONS [REKABENTUK UJIKAJI DENGAN APLIKASI KOMPUTER] Duration:

Statistics 423 Midterm Examination Winter 2009

Sttstcs 43 Mdterm Exmnton Wnter 009 Nme: e-ml: 1. Plese prnt your nme nd e-ml ddress n the bove spces.. Do not turn ths pge untl nstructed to do so. 3. Ths s closed book exmnton. You my hve your hnd clcultor

MATHEMATICS FOR MANAGEMENT BBMP1103

T o p i c M T R I X MTHEMTICS FOR MNGEMENT BBMP Ojectives: TOPIC : MTRIX. Define mtri. ssess the clssifictions of mtrices s well s know how to perform its opertions. Clculte the determinnt for squre mtri

CISE 301: Numerical Methods Lecture 5, Topic 4 Least Squares, Curve Fitting

CISE 3: umercl Methods Lecture 5 Topc 4 Lest Squres Curve Fttng Dr. Amr Khouh Term Red Chpter 7 of the tetoo c Khouh CISE3_Topc4_Lest Squre Motvton Gven set of epermentl dt 3 5. 5.9 6.3 The reltonshp etween

MSS 302 Real Analysis [Analisis Nyata]

UNIVERSITI SAINS MALAYSIA First Semester Exmitio 011/01 Acdemic Sessio Jury 01 MSS 30 Rel Alysis [Alisis Nyt] Durtio : 3 hours [Ms : 3 jm] Plese check tht this exmitio pper cosists o FIVE pges o prited

SULIT 47/1 Mtemtik Tmbhn Kerts 1 September 010 jm MAKTAB RENDAH SAINS MARA PEPERIKSAAN PERCUBAAN SIJIL PELAJARAN MALAYSIA 010 47/1 MATEMATIK TAMBAHAN Kerts 1 Du jm JANGAN BUKA KERTAS SOALAN INI SEHINGGA

4. Eccentric axial loading, cross-section core

. Eccentrc xl lodng, cross-secton core Introducton We re strtng to consder more generl cse when the xl force nd bxl bendng ct smultneousl n the cross-secton of the br. B vrtue of Snt-Vennt s prncple we

SULIT /1 The following formulae may be helpful in answering the questions. The symbols given are the ones commonly used. ALGEBRA. log.

Use SULIT 7/ The following formule my be helpful in nswering the questions. The symbols given re the ones commonly used. ALGEBRA b b c 8 log b log log c c b m n = m + n 9 Tn = + (n -)d m n = m n 0 S n

DCDM BUSINESS SCHOOL NUMERICAL METHODS (COS 233-8) Solutions to Assignment 3. x f(x)

DCDM BUSINESS SCHOOL NUMEICAL METHODS (COS -8) Solutons to Assgnment Queston Consder the followng dt: 5 f() 8 7 5 () Set up dfference tble through fourth dfferences. (b) Wht s the mnmum degree tht n nterpoltng

MSG 388 Mathematical Algorithms for Computer Graphics [Algoritma Matematik untuk Grafik Komputer]

UNIVERSITI SAINS MALAYSIA Frst Semester Examnaton 0/0 Academc Sesson January 0 MSG 88 Mathematcal Algorthms for Computer Graphcs [Algortma Matemat untu Graf Komputer] Duraton : hours [Masa : jam] Please

PEPERIKSAAN BERSAMA SEKOLAH-SEKOLAH MENENGAH NEGERI PAHANG NAMA TINGKATAN PEPERIKSAAN PERCUBAAN 00 / ADDITIONAL MATHEMATICS Kerts September 00 jm Du jm JANGAN BUKA KERTAS SOALAN INI SEHINGGA DIBERITAHU.

Lecture 5 Single factor design and analysis

Lectue 5 Sngle fcto desgn nd nlss Completel ndomzed desgn (CRD Completel ndomzed desgn In the desgn of expements, completel ndomzed desgns e fo studng the effects of one pm fcto wthout the need to tke

Principle Component Analysis

Prncple Component Anlyss Jng Go SUNY Bufflo Why Dmensonlty Reducton? We hve too mny dmensons o reson bout or obtn nsghts from o vsulze oo much nose n the dt Need to reduce them to smller set of fctors

CALIBRATION OF SMALL AREA ESTIMATES IN BUSINESS SURVEYS

CALIBRATION OF SMALL AREA ESTIMATES IN BUSINESS SURVES Rodolphe Prm, Ntle Shlomo Southmpton Sttstcl Scences Reserch Insttute Unverst of Southmpton Unted Kngdom SAE, August 20 The BLUE-ETS Project s fnnced

Model Fitting and Robust Regression Methods

Dertment o Comuter Engneerng Unverst o Clorn t Snt Cruz Model Fttng nd Robust Regresson Methods CMPE 64: Imge Anlss nd Comuter Vson H o Fttng lnes nd ellses to mge dt Dertment o Comuter Engneerng Unverst

Student Activity 3: Single Factor ANOVA

MATH 40 Student Activity 3: Single Fctor ANOVA Some Bsic Concepts In designed experiment, two or more tretments, or combintions of tretments, is pplied to experimentl units The number of tretments, whether

MATHEMATICAL MODEL AND STATISTICAL ANALYSIS OF THE TENSILE STRENGTH (Rm) OF THE STEEL QUALITY J55 API 5CT BEFORE AND AFTER THE FORMING OF THE PIPES

6 th Reserch/Exert Conference wth Interntonl Prtcton QUALITY 009, Neum, B&H, June 04 07, 009 MATHEMATICAL MODEL AND STATISTICAL ANALYSIS OF THE TENSILE STRENGTH (Rm) OF THE STEEL QUALITY J55 API 5CT BEFORE

Variable time amplitude amplification and quantum algorithms for linear algebra. Andris Ambainis University of Latvia

Vrble tme mpltude mplfcton nd quntum lgorthms for lner lgebr Andrs Ambns Unversty of Ltv Tlk outlne. ew verson of mpltude mplfcton;. Quntum lgorthm for testng f A s sngulr; 3. Quntum lgorthm for solvng

SULIT /1 The following formulae may be helpful in answering the questions. The symbols given are the ones commonly used. ALGEBRA. log.

SULIT 47/1 The following formule my be helpful in nswering the questions. The symbols given re the ones commonly used. ALGEBRA 1 b b 4c x 8 log b log log c c b m x n = m + n 9 Tn = + (n -1)d m n = m n

Quiz: Experimental Physics Lab-I

Mxmum Mrks: 18 Totl tme llowed: 35 mn Quz: Expermentl Physcs Lb-I Nme: Roll no: Attempt ll questons. 1. In n experment, bll of mss 100 g s dropped from heght of 65 cm nto the snd contner, the mpct s clled

Dennis Bricker, 2001 Dept of Industrial Engineering The University of Iowa. MDP: Taxi page 1

Denns Brcker, 2001 Dept of Industrl Engneerng The Unversty of Iow MDP: Tx pge 1 A tx serves three djcent towns: A, B, nd C. Ech tme the tx dschrges pssenger, the drver must choose from three possble ctons:

Fall 2017 Exam 1 MARK BOX HAND IN PART PIN: 17

Fll 7 Exm problem MARK BOX points HAND IN PART 3-5=x5 NAME: Solutions PIN: 7 % INSTRUCTIONS This exm comes in two prts. () HAND IN PART. Hnd in only this prt. () STATEMENT OF MULTIPLE CHOICE PROBLEMS.

SVMs for regression Non-parametric/instance based classification method

S 75 Mchne ernng ecture Mos Huskrecht mos@cs.ptt.edu 539 Sennott Squre SVMs for regresson Non-prmetrc/nstnce sed cssfcton method S 75 Mchne ernng Soft-mrgn SVM Aos some fet on crossng the seprtng hperpne

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC

Introducton Rnk One Updte And the Google Mtrx y Al Bernsten Sgnl Scence, LLC www.sgnlscence.net here re two dfferent wys to perform mtrx multplctons. he frst uses dot product formulton nd the second uses

SULIT 7/. This question pper consists of 5 question. Kerts soln ini mengndungi 5 soln.. Answer ll questions. Jwb semu soln. INFORMATION FOR

sh@mozc008 SULIT 7/ NAMA. Mtemtik Tmbhn KELAS. Kerts September 008 jm PERSIDANGAN KEBANGSAAN PENGETUA SEMENANJUNG MALAYSIA PEPERIKSAAN PERCUBAAN SIJIL PELAJARAN MALAYSIA 008 MATEMATIK TAMBAHAN Kerts Du

ψ ij has the eigenvalue

Moller Plesset Perturbton Theory In Moller-Plesset (MP) perturbton theory one tes the unperturbed Hmltonn for n tom or molecule s the sum of the one prtcle Foc opertors H F() where the egenfunctons of

Regression Analysis. Regression Analysis

Regresson Analyss Smple Regresson Multvarate Regresson Stepwse Regresson Replcaton and Predcton Error 1 Regresson Analyss In general, we "ft" a model by mnmzng a metrc that represents the error. n mn (y

Least squares. Václav Hlaváč. Czech Technical University in Prague

Lest squres Václv Hlváč Czech echncl Unversty n Prgue hlvc@fel.cvut.cz http://cmp.felk.cvut.cz/~hlvc Courtesy: Fred Pghn nd J.P. Lews, SIGGRAPH 2007 Course; Outlne 2 Lner regresson Geometry of lest-squres

Fall 2012 Analysis of Experimental Measurements B. Eisenstein/rev. S. Errede. with respect to λ. 1. χ λ χ λ ( ) λ, and thus:

More on χ nd errors : uppose tht we re fttng for sngle -prmeter, mnmzng: If we epnd The vlue χ ( ( ( ; ( wth respect to. χ n Tlor seres n the vcnt of ts mnmum vlue χ ( mn χ χ χ χ + + + mn mnmzes χ, nd

Each term is formed by adding a constant to the previous term. Geometric progression

Chpter 4 Mthemticl Progressions PROGRESSION AND SEQUENCE Sequence A sequence is succession of numbers ech of which is formed ccording to definite lw tht is the sme throughout the sequence. Arithmetic Progression

Definition of Tracking

Trckng Defnton of Trckng Trckng: Generte some conclusons bout the moton of the scene, objects, or the cmer, gven sequence of mges. Knowng ths moton, predct where thngs re gong to project n the net mge,

Lecture 6: Introduction to Linear Regression

Lecture 6: Introducton to Lnear Regresson An Manchakul amancha@jhsph.edu 24 Aprl 27 Lnear regresson: man dea Lnear regresson can be used to study an outcome as a lnear functon of a predctor Example: 6

Fitting a Polynomial to Heat Capacity as a Function of Temperature for Ag. Mathematical Background Document

Fttng Polynol to Het Cpcty s Functon of Teperture for Ag. thetcl Bckground Docuent by Theres Jul Zelnsk Deprtent of Chestry, edcl Technology, nd Physcs onouth Unversty West ong Brnch, J 7764-898 tzelns@onouth.edu

MAJLIS PENGETUA SEKOLAH MALAYSIA NEGERI KEDAH DARUL AMAN JANGAN BUKA KERTAS SOALAN INI SEHINGGA DIBERITAHU

1 347/ MEI 014 MAJLIS PENGETUA SEKOLAH MALAYSIA NEGERI KEDAH DARUL AMAN MODUL PENINGKATAN PRESTASI TINGKATAN LIMA 014 MATEMATIK TAMBAHAN KERTAS MODUL 1 1 jm 347/ Du jm tig puluh minit JANGAN BUKA KERTAS

AQA Further Pure 2. Hyperbolic Functions. Section 2: The inverse hyperbolic functions

Hperbolic Functions Section : The inverse hperbolic functions Notes nd Emples These notes contin subsections on The inverse hperbolic functions Integrtion using the inverse hperbolic functions Logrithmic

Spring 2017 Exam 1 MARK BOX HAND IN PART PIN: 17

Spring 07 Exm problem MARK BOX points HAND IN PART 0 5-55=x5 0 NAME: Solutions 3 0 0 PIN: 7 % 00 INSTRUCTIONS This exm comes in two prts. () HAND IN PART. Hnd in only this prt. () STATEMENT OF MULTIPLE

INTERPOLATION(1) ELM1222 Numerical Analysis. ELM1222 Numerical Analysis Dr Muharrem Mercimek

ELM Numercl Anlss Dr Muhrrem Mercmek INTEPOLATION ELM Numercl Anlss Some of the contents re dopted from Lurene V. Fusett, Appled Numercl Anlss usng MATLAB. Prentce Hll Inc., 999 ELM Numercl Anlss Dr Muhrrem

PENILAIAN PERCUBAAN SPM NEGERI PAHANG 2017

SULIT / / Tingktn Additionl Mthemtics Kerts Ogos jm NAMA : KELAS : ANGKA GILIRAN: NO KP: PENILAIAN PERCUBAAN SPM NEGERI PAHANG 0 ADDITIONAL MATHEMATICS Kerts Jm JANGAN BUKA KERTAS SOALAN INI SEHINGGA DIBERITAHU.

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Chpter.4 Newton-Rphson Method of Solvng Nonlner Equton After redng ths chpter, you should be ble to:. derve the Newton-Rphson method formul,. develop the lgorthm of the Newton-Rphson method,. use the Newton-Rphson

Level I MAML Olympiad 2001 Page 1 of 6 (A) 90 (B) 92 (C) 94 (D) 96 (E) 98 (A) 48 (B) 54 (C) 60 (D) 66 (E) 72 (A) 9 (B) 13 (C) 17 (D) 25 (E) 38

Level I MAML Olympid 00 Pge of 6. Si students in smll clss took n em on the scheduled dte. The verge of their grdes ws 75. The seventh student in the clss ws ill tht dy nd took the em lte. When her score

Math 1051 Diagnostic Pretest Key and Homework

Mth 1051 Dignostic Pretest Ke nd Hoework HW1 The dignostic test is designed to give us n ide of our level of skill in doing high school lgebr s ou begin Mth 1051. You should be ble to do these probles

STRAND B: NUMBER THEORY

Mthemtics SKE, Strnd B UNIT B Indices nd Fctors: Tet STRAND B: NUMBER THEORY B Indices nd Fctors Tet Contents Section B. Squres, Cubes, Squre Roots nd Cube Roots B. Inde Nottion B. Fctors B. Prime Fctors,

MATH FIELD DAY Contestants Insructions Team Essay. 1. Your team has forty minutes to answer this set of questions.

MATH FIELD DAY 2012 Contestnts Insructions Tem Essy 1. Your tem hs forty minutes to nswer this set of questions. 2. All nswers must be justified with complete explntions. Your nswers should be cler, grmmticlly

A B= ( ) because from A to B is 3 right, 2 down.

8. Vectors nd vector nottion Questions re trgeted t the grdes indicted Remember: mgnitude mens size. The vector ( ) mens move left nd up. On Resource sheet 8. drw ccurtely nd lbel the following vectors.

Support vector machines for regression

S 75 Mchne ernng ecture 5 Support vector mchnes for regresson Mos Huskrecht mos@cs.ptt.edu 539 Sennott Squre S 75 Mchne ernng he decson oundr: ˆ he decson: Support vector mchnes ˆ α SV ˆ sgn αˆ SV!!: Decson

NEARLY-OPTIMUM SELECTION OF STRENGTH t ORTHOGONAL ARRAYS: A STRENGTH AND EFFICIENCY APPRAISAL

Interntonl Journl of GEOMAE Oct. 08 Vol.5 Issue 50 pp. 6-66 IN: 86-98 (P) 86-990 (O) Jpn DOI: https://do.org/0.660/08.50. 793 pecl Issue on cence Engneerng & Envronment NEARLY-OPIMUM ELECION OF RENGH t

Individual Contest. English Version. Time limit: 90 minutes. Instructions:

Elementry Mthemtics Interntionl Contest Instructions: Individul Contest Time limit: 90 minutes Do not turn to the first pge until you re told to do so. Write down your nme, your contestnt numer nd your

Fall 2012 Analysis of Experimental Measurements B. Eisenstein/rev. S. Errede

Fll Anlss of Epermentl Mesurements B. Esensten/rev. S. Errede Monte Crlo Methods/Technques: These re mong the most powerful tools for dt nlss nd smulton of eperments. The growth of ther mportnce s closel

Substitution Matrices and Alignment Statistics. Substitution Matrices

Susttuton Mtrces nd Algnment Sttstcs BMI/CS 776 www.ostt.wsc.edu/~crven/776.html Mrk Crven crven@ostt.wsc.edu Ferur 2002 Susttuton Mtrces two oulr sets of mtrces for roten seuences PAM mtrces [Dhoff et

Haddow s Experiment:

schemtc drwng of Hddow's expermentl set-up movng pston non-contctng moton sensor bems of sprng steel poston vres to djust frequences blocks of sold steel shker Hddow s Experment: terr frm Theoretcl nd

Course Review Introduction to Computer Methods

Course Revew Wht you hopefully hve lerned:. How to nvgte nsde MIT computer system: Athen, UNIX, emcs etc. (GCR). Generl des bout progrmmng (GCR): formultng the problem, codng n Englsh trnslton nto computer

Lecture 4: Piecewise Cubic Interpolation

Lecture notes on Vrtonl nd Approxmte Methods n Appled Mthemtcs - A Perce UBC Lecture 4: Pecewse Cubc Interpolton Compled 6 August 7 In ths lecture we consder pecewse cubc nterpolton n whch cubc polynoml

Department of Mechanical Engineering, University of Bath. Mathematics ME Problem sheet 11 Least Squares Fitting of data

Deprtment of Mechncl Engneerng, Unversty of Bth Mthemtcs ME10305 Prolem sheet 11 Lest Squres Fttng of dt NOTE: If you re gettng just lttle t concerned y the length of these questons, then do hve look t

7.2 Volume. A cross section is the shape we get when cutting straight through an object.

7. Volume Let s revew the volume of smple sold, cylnder frst. Cylnder s volume=se re heght. As llustrted n Fgure (). Fgure ( nd (c) re specl cylnders. Fgure () s rght crculr cylnder. Fgure (c) s ox. A

SUMMER KNOWHOW STUDY AND LEARNING CENTRE

SUMMER KNOWHOW STUDY AND LEARNING CENTRE Indices & Logrithms 2 Contents Indices.2 Frctionl Indices.4 Logrithms 6 Exponentil equtions. Simplifying Surds 13 Opertions on Surds..16 Scientific Nottion..18

Lecture 2e Orthogonal Complement (pages )

Lecture 2e Orthogonl Complement (pges -) We hve now seen tht n orthonorml sis is nice wy to descrie suspce, ut knowing tht we wnt n orthonorml sis doesn t mke one fll into our lp. In theory, the process

Read section 3.3, 3.4 Announcements:

Dte: 3/1/13 Objective: SWBAT pply properties of exponentil functions nd will pply properties of rithms. Bell Ringer: 1. f x = 3x 6, find the inverse, f 1 x., Using your grphing clcultor, Grph 1. f x,f

Polynomial Regression Models

LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance

First Year Examination Department of Statistics, University of Florida

Frst Year Examnaton Department of Statstcs, Unversty of Florda May 7, 010, 8:00 am - 1:00 noon Instructons: 1. You have four hours to answer questons n ths examnaton.. You must show your work to receve

Department of Statistics University of Toronto STA305H1S / 1004 HS Design and Analysis of Experiments Term Test - Winter Solution

Department of Statstcs Unversty of Toronto STA35HS / HS Desgn and Analyss of Experments Term Test - Wnter - Soluton February, Last Name: Frst Name: Student Number: Instructons: Tme: hours. Ads: a non-programmable

Geometric Correction or Georeferencing

Geoetrc Correcton or Georeferencng GEOREFERENCING: fro ge to p Coordntes on erth: (λ, φ) ge: (, ) p: (, ) rel nteger Trnsfortons (nvolvng deforton): erth-to-ge: χ erth-to-p: ψ (crtogrphc proecton) ge-to-p:

4 7x =250; 5 3x =500; Read section 3.3, 3.4 Announcements: Bell Ringer: Use your calculator to solve

Dte: 3/14/13 Objective: SWBAT pply properties of exponentil functions nd will pply properties of rithms. Bell Ringer: Use your clcultor to solve 4 7x =250; 5 3x =500; HW Requests: Properties of Log Equtions

Gravitational Acceleration: A case of constant acceleration (approx. 2 hr.) (6/7/11)

Gravtatonal Acceleraton: A case of constant acceleraton (approx. hr.) (6/7/11) Introducton The gravtatonal force s one of the fundamental forces of nature. Under the nfluence of ths force all objects havng

Review of linear algebra. Nuno Vasconcelos UCSD

Revew of lner lgebr Nuno Vsconcelos UCSD Vector spces Defnton: vector spce s set H where ddton nd sclr multplcton re defned nd stsf: ) +( + ) (+ )+ 5) λ H 2) + + H 6) 3) H, + 7) λ(λ ) (λλ ) 4) H, - + 8)

Trigonometry. Trigonometry. Solutions. Curriculum Ready ACMMG: 223, 224, 245.

Trgonometry Trgonometry Solutons Currulum Redy CMMG:, 4, 4 www.mthlets.om Trgonometry Solutons Bss Pge questons. Identfy f the followng trngles re rght ngled or not. Trngles,, d, e re rght ngled ndted

Solution for Assignment 1 : Intro to Probability and Statistics, PAC learning

Solution for Assignment 1 : Intro to Probbility nd Sttistics, PAC lerning 10-701/15-781: Mchine Lerning (Fll 004) Due: Sept. 30th 004, Thursdy, Strt of clss Question 1. Bsic Probbility ( 18 pts) 1.1 (

Learning Enhancement Team

Lernng Enhnement Tem Worsheet: The Cross Produt These re the model nswers for the worsheet tht hs questons on the ross produt etween vetors. The Cross Produt study gude. z x y. Loong t mge, you n see tht

Katholieke Universiteit Leuven Department of Computer Science

Updte Rules for Weghted Non-negtve FH*G Fctorzton Peter Peers Phlp Dutré Report CW 440, Aprl 006 Ktholeke Unverstet Leuven Deprtment of Computer Scence Celestjnenln 00A B-3001 Heverlee (Belgum) Updte Rules

Abhilasha Classes Class- XII Date: SOLUTION (Chap - 9,10,12) MM 50 Mob no

hlsh Clsses Clss- XII Dte: 0- - SOLUTION Chp - 9,0, MM 50 Mo no-996 If nd re poston vets of nd B respetvel, fnd the poston vet of pont C n B produed suh tht C B vet r C B = where = hs length nd dreton

Topic 1 Notes Jeremy Orloff

Topic 1 Notes Jerem Orloff 1 Introduction to differentil equtions 1.1 Gols 1. Know the definition of differentil eqution. 2. Know our first nd second most importnt equtions nd their solutions. 3. Be ble

STAT 3008 Applied Regression Analysis

STAT 3008 Appled Regresson Analyss Tutoral : Smple Lnear Regresson LAI Chun He Department of Statstcs, The Chnese Unversty of Hong Kong 1 Model Assumpton To quantfy the relatonshp between two factors,

Algebra & Functions (Maths ) opposite side

Instructor: Dr. R.A.G. Seel Trigonometr Algebr & Functions (Mths 0 0) 0th Prctice Assignment hpotenuse hpotenuse side opposite side sin = opposite hpotenuse tn = opposite. Find sin, cos nd tn in 9 sin

SVMs for regression Multilayer neural networks

Lecture SVMs for regresson Muter neur netors Mos Husrecht mos@cs.ptt.edu 539 Sennott Squre Support vector mchne SVM SVM mmze the mrgn round the seprtng hperpne. he decson functon s fu specfed suset of

Counting intersections of spirals on a torus

Counting intersections of spirls on torus 1 The problem Consider unit squre with opposite sides identified. For emple, if we leve the centre of the squre trveling long line of slope 2 (s shown in the first

Introduction to Algebra - Part 2

Alger Module A Introduction to Alger - Prt Copright This puliction The Northern Alert Institute of Technolog 00. All Rights Reserved. LAST REVISED Oct., 008 Introduction to Alger - Prt Sttement of Prerequisite

1 Linear Least Squares

Lest Squres Pge 1 1 Liner Lest Squres I will try to be consistent in nottion, with n being the number of dt points, nd m < n being the number of prmeters in model function. We re interested in solving

Math 497C Sep 17, Curves and Surfaces Fall 2004, PSU

Mth 497C Sep 17, 004 1 Curves nd Surfces Fll 004, PSU Lecture Notes 3 1.8 The generl defnton of curvture; Fox-Mlnor s Theorem Let α: [, b] R n be curve nd P = {t 0,...,t n } be prtton of [, b], then the

Proof that if Voting is Perfect in One Dimension, then the First. Eigenvector Extracted from the Double-Centered Transformed

Proof tht f Votng s Perfect n One Dmenson, then the Frst Egenvector Extrcted from the Doule-Centered Trnsformed Agreement Score Mtrx hs the Sme Rn Orderng s the True Dt Keth T Poole Unversty of Houston

PART 1 MULTIPLE CHOICE Circle the appropriate response to each of the questions below. Each question has a value of 1 point.

PART MULTIPLE CHOICE Circle the pproprite response to ech of the questions below. Ech question hs vlue of point.. If in sequence the second level difference is constnt, thn the sequence is:. rithmetic

Consolidation Worksheet

Cmbridge Essentils Mthemtics Core 8 NConsolidtion Worksheet N Consolidtion Worksheet Work these out. 8 b 7 + 0 c 6 + 7 5 Use the number line to help. 2 Remember + 2 2 +2 2 2 + 2 Adding negtive number is

6 Roots of Equations: Open Methods

HK Km Slghtly modfed 3//9, /8/6 Frstly wrtten t Mrch 5 6 Roots of Equtons: Open Methods Smple Fed-Pont Iterton Newton-Rphson Secnt Methods MATLAB Functon: fzero Polynomls Cse Study: Ppe Frcton Brcketng

6.6 The Marquardt Algorithm

6.6 The Mqudt Algothm lmttons of the gdent nd Tylo expnson methods ecstng the Tylo expnson n tems of ch-sque devtves ecstng the gdent sech nto n tetve mtx fomlsm Mqudt's lgothm utomtclly combnes the gdent

Name Date. In Exercises 1 6, tell whether x and y show direct variation, inverse variation, or neither.

1 Prctice A In Eercises 1 6, tell whether nd show direct vrition, inverse vrition, or neither.. 7. 6. 10. 8 6. In Eercises 7 10, tell whether nd show direct vrition, inverse vrition, or neither. 8 10 8.

Quotient Rule: am a n = am n (a 0) Negative Exponents: a n = 1 (a 0) an Power Rules: (a m ) n = a m n (ab) m = a m b m

Formuls nd Concepts MAT 099: Intermedite Algebr repring for Tests: The formuls nd concepts here m not be inclusive. You should first tke our prctice test with no notes or help to see wht mteril ou re comfortble

Lecture 20: Hypothesis testing

Lecture : Hpothess testng Much of statstcs nvolves hpothess testng compare a new nterestng hpothess, H (the Alternatve hpothess to the borng, old, well-known case, H (the Null Hpothess or, decde whether

LINEAR ALGEBRA APPLIED

5.5 Applictions of Inner Product Spces 5.5 Applictions of Inner Product Spces 7 Find the cross product of two vectors in R. Find the liner or qudrtic lest squres pproimtion of function. Find the nth-order

MACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression

11 MACHINE APPLIED MACHINE LEARNING LEARNING MACHINE LEARNING Gaussan Mture Regresson 22 MACHINE APPLIED MACHINE LEARNING LEARNING Bref summary of last week s lecture 33 MACHINE APPLIED MACHINE LEARNING

Math 259 Winter Solutions to Homework #9

Mth 59 Winter 9 Solutions to Homework #9 Prolems from Pges 658-659 (Section.8). Given f(, y, z) = + y + z nd the constrint g(, y, z) = + y + z =, the three equtions tht we get y setting up the Lgrnge multiplier

This section consists of FOUR (4) structured questions. Answer ALL questions.

SULIT PBM104: ADVACED MATHEMATICS 1 STRUCTURE (100 MARKS) ISTRUCTIO: This sectio cosists of FOUR (4) structured questios. Aswer ALL questios. ARAHA : Bhgi ii megdugi EMPAT (4) sol berstruktur. Jwb semu

Minnesota State University, Mankato 44 th Annual High School Mathematics Contest April 12, 2017

Minnesot Stte University, Mnkto 44 th Annul High School Mthemtics Contest April, 07. A 5 ft. ldder is plced ginst verticl wll of uilding. The foot of the ldder rests on the floor nd is 7 ft. from the wll.

Physics 121 Sample Common Exam 2 Rev2 NOTE: ANSWERS ARE ON PAGE 7. Instructions:

Physcs 121 Smple Common Exm 2 Rev2 NOTE: ANSWERS ARE ON PAGE 7 Nme (Prnt): 4 Dgt ID: Secton: Instructons: Answer ll 27 multple choce questons. You my need to do some clculton. Answer ech queston on the

8 Laplace s Method and Local Limit Theorems

8 Lplce s Method nd Locl Limit Theorems 8. Fourier Anlysis in Higher DImensions Most of the theorems of Fourier nlysis tht we hve proved hve nturl generliztions to higher dimensions, nd these cn be proved

On the Statistical Uncertainties of Time-domain-based Assessment of Stability Failures: Confidence Interval for the Mean and Variance of a Time Series

Interntonl Shp Stblt Workshop 3 Proceedngs of the 3 th Interntonl Shp Stblt Workshop, Brest 3-6 September On the Sttstcl Uncertntes of Tme-domn-bsed Assessment of Stblt Flures: Confdence Intervl for the

x yi In chapter 14, we want to perform inference (i.e. calculate confidence intervals and perform tests of significance) in this setting.

The Practce of Statstcs, nd ed. Chapter 14 Inference for Regresson Introducton In chapter 3 we used a least-squares regresson lne (LSRL) to represent a lnear relatonshp etween two quanttatve explanator

PEPERIKSAAN PERCUBAAN BERSAMA SIJIL PELAJARAN MALAYSIA 2011 ADDITIONAL MATHEMATICS

NAMA :. TINGKATAN :. SULIT 7/ Additionl Mthemtics Pper Ogos 0 Jm PEPERIKSAAN PERCUBAAN BERSAMA SIJIL PELAJARAN MALAYSIA 0 ANJURAN MAJLIS PENGETUA SEKOLAH MALAYSIA (MPSM) CAWANGAN PERLIS ADDITIONAL MATHEMATICS