Appendix A: Mathematical Formulae and Statistical Tables
|
|
- Alvin Thompson
- 5 years ago
- Views:
Transcription
1 Aedi A: Mathematical Formulae ad Statistical Tables Pure Mathematics Mesuratio Surface area of shere = r Area of curved surface of coe = r J slat height Trigoometry a * b & c ' bc cos A Arithmetic Series u * a & ( ' ) d S * ( a & l) * { a & ( ' ) d} Geometric Series u * ar ' S a( ' r ) * ' r a SE * for r ' r ) Summatios _ 6 r* r * ( & )( & ) r * ( & ) r* _ 8 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
2 Biomial Series ` j ` j ` & j a k & a k * a k b r l b r & l b r & l ` j ' ` j ' ` j ' r r ( a & b) * a & a k a b & a k a b & & a b & & b a k r b l b l b l ( W ) ` j! where a k * Cr * b r l r!( ' r)! r ( ' ) ( ' ) "( ' r & ) ( & ) * & & & " &..." r & " ( ), W' ) Logarithms ad Eoetials l e a * a Comle Numbers { r(cos & isi )} * r (cos & isi ) i e * cos & isi The roots of z * are give by k i z * e, for k * 0,,,, ' Maclauri s Series ( r) f( ) * f(0) & f C(0) & f CC(0) & & f (0) &! r! r r * * & & & &! e e( )! r & for all r& l( & ) * ' & ' &(' ) & (' ) D ) r r 5 r& r si * ' & ' & (' ) & for all! 5! ( r & )! r cos * ' & ' & (' ) & for all!! ( r )! r OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 85
3 ta ' 5 * ' & ' &(' ) 5 r& r & (' D D) r & 5 r& sih * & & & & & for all! 5! (r & )! r cosh * & & & & & for all!! ( r)! tah ' 5 r& * & & & & & 5 r & (' ) ) ) Hyerbolic Fuctios cosh ' sih * sih * sih cosh cosh * cosh & sih { } ' cosh * l & ' ( I) { } ' sih * l & & ' `& j tah * l ( ) a k ) b' l Coordiate Geometry The eredicular distace from ( h, k) to a & by & c * 0 is The acute agle betwee lies with gradiets m ad m is ta ah & bk & c a & b m ' m & m m ' 86 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
4 Trigoometric Idetities si( A H B) * si Acos B H cos Asi B cos( A H B) * cos Acos B $ si Asi B ta A H ta B ta( A H B) * ( A H B O ( k & ) ) $ ta Ata B For t * ta A : t si A *, & t ' t cos A * & t A & B A ' B si A & si B * si cos A & B A ' B si A ' si B * cos si A & B A ' B cos A & cos B * cos cos A & B A ' B cos A ' cos B * ' si si Vectors The resolved art of a i the directio of b is a.b b The oit dividig AB i the ratio : is a & & b Vector roduct: i a b ` ab ' ab j ˆ a k aj b * a b si * j a b * ab ' ab k a b a ab ' ab k b l If A is the oit with ositio vector a * ai & aj & ak ad the directio vector b is give by b * b i & b j & b k, the the straight lie through A with directio vector b has cartesia equatio ' a y ' a z ' a * * (* ) b b b OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 87
5 The lae through A with ormal vector * i & j & k has cartesia equatio & y & z & d * 0 where d * 'a. The lae through o-colliear oits A, B ad C has vector equatio r * a & ( b ' a) & ( c ' a) * ( ' ' ) a & b & c The lae through the oit with ositio vector a ad arallel to b ad c has equatio r * a & sb & tc The eredicular distace of (,, ) from & y & z & d * 0 is & & & d & & Matri Trasformatios Aticlockwise rotatio through about O : ` cos a b si ' si cos j k l Reflectio i the lie y * (ta ) : `cos si a b si ' cos j k l 88 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
6 Differetiatio f( ) f C( ) ta k si ' k sec k ' cos ' ' ' ta ' & sec sec ta cot cosec sih cosh tah sih cosh tah ' ' ' 'cosec ' cosec cot cosh sih sech & ' ' If f( ) y * the g( ) dy f C( )g( ) ' f( )g C( ) * d {g( )} OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 89
7 Itegratio (+ costat; a + 0 where relevat) f( ) f( )d f sec k ta cot ta k k l sec l si cosec ' l cosec & cot * l ta( ) sec l sec & ta * l ta( & ) sih cosh tah cosh sih l cosh a ' ' ` j si a k ( ) a) b a l a & ' a ta ' ` j a k a b a l cosh ' ` j a k or l { & ' a } ( + a) b a l a & a k b a l sih ' ` j or l{ & & a } a ' a & ' ` j l * tah a k ( ) a) a a ' a b a l ' a ' a l a & a f f dv du u d * uv ' v d d d 90 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
8 Area of a Sector r d A * f (olar coordiates) f ` dy d j A * y dt a ' k b dt dt l (arametric form) Numerical Mathematics Numerical Itegratio b The traezium rule: f y d Q h {( y 0 & y ) & ( y a & y & & y ) ' }, where b ' a h * b Simso s rule: f y d Q h {( y 0 & y ) & ( y a & y & & y' ) & ( y & y & & y ) ' }, where b ' a h * ad is eve Numerical Solutio of Equatios f( ) The Newto-Rahso iteratio for solvig f( ) * 0 : & * ' f C( ) Mechaics Motio i a Circle Trasverse velocity: v * r! Trasverse acceleratio: v! * r!! Radial acceleratio: v ' r! * ' r OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 9
9 Cetres of Mass (for uiform bodies) Triagular lamia: alog media from verte Solid hemishere, radius r : r from cetre Hemisherical shell, radius r : r from cetre Circular arc, radius r, agle at cetre 8 si : r from cetre Sector of circle, radius r, agle at cetre r si : from cetre Solid coe or yramid of height h : h above the base o the lie from cetre of base to verte Coical shell of height h : h above the base o the lie from cetre of base to verte Momets of Iertia (for uiform bodies of mass m ) Thi rod, legth l, about eredicular ais through cetre: ml Rectagular lamia about ais i lae bisectig edges of legth l : ml Thi rod, legth l, about eredicular ais through ed: ml Rectagular lamia about edge eredicular to edges of legth l : ml Rectagular lamia, sides a ad b, about eredicular ais through cetre: m( a & b ) Hoo or cylidrical shell of radius r about ais: mr Hoo of radius r about a diameter: mr Disc or solid cylider of radius r about ais: mr Disc of radius r about a diameter: mr Solid shere, radius r, about a diameter: 5 mr Sherical shell of radius r about a diameter: mr Parallel aes theorem: I * I & m( AG) A G Peredicular aes theorem: I z * I & I y (for a lamia i the -y lae) 9 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
10 Probability ad Statistics Probability P( A T B) * P( A) & P( B) ' P( A S B) P( A S B) * P( A)P( B A) P( B A)P( A) P( A B) * P( B A)P( A) & P( B AC)P( AC) Bayes Theorem: P( Aj ) P( B Aj ) P( Aj B) * / P( A ) P( B A ) i i Discrete Distributios For a discrete radom variable X takig values Eectatio (mea): E( X ) * * / i i i with robabilities i Variace: i i i i Var( X ) * * /( ' ) * / ' For a fuctio g( X ) : E(g( X )) * / g( ) The robability geeratig fuctio of X is G X ( t ) * E( t ), ad E( X ) * G C (), X i i X Var( X ) * G CC () & G C () '{G C ()} X X X For Z * X & Y, where X ad Y are ideedet: G ( t) * G ( t)g ( t) Z X Y OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 9
11 Stadard Discrete Distributios: Distributio of X P(X = ) Mea Variace P.G.F. ` j Biomial B(, ) a k ( ' ) b l ' ( ' ) ( ' & t) Poisso Po( ) e ' ( ) e t'! Geometric Geo () o,, ( ' ) ' ' t ' ( ' ) t Cotiuous Distributios For a cotiuous radom variable X havig robability desity fuctio f Eectatio (mea): E( X ) * * f f( )d Variace: f Var( X ) * * ( ' ) f( )d * f( )d ' f For a fuctio g( X ) : E(g( X )) * f g( )f( )d Cumulative distributio fuctio: F( ) * P( X D ) * f f( t) dt 'E tx The momet geeratig fuctio of X is M X ( t ) * E(e ) ad E( X ) * M C (0), X ( ) X E( X ) * M (0), Var( X ) * M CC (0) '{M C (0)} X X For Z * X & Y, where X ad Y are ideedet: M ( t) * M ( t)m ( t) Z X Y 9 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
12 Stadard Cotiuous Distributios: Distributio of X P.D.F. Mea Variace M.G.F. Uiform (Rectagular) o [ a, b] b ' a ( a b) ( b ' a) e ' e ( b ' a) t & bt at Eoetial e ' ' t Normal N(, ) e ' ' e t& t Eectatio Algebra Covariace: Cov( X, Y ) * E(( X ' )( Y ' )) * E( XY ) ' X Y X Y Var( ax H by ) * a Var( X ) & b Var( Y ) H abcov( X, Y ) Product momet correlatio coefficiet: Cov( X, Y ) * X Y If X * ax C & b ad Y * cyc & d, the Cov( X, Y ) * ac Cov( X C, YC) For ideedet radom variables X ad Y E( XY) * E( X )E( Y ) Var( ax H by ) * a Var( X ) & b Var( Y ) Samlig Distributios For a radom samle X, X,, X of ideedet observatios from a distributio havig mea ad variace X is a ubiased estimator of, with Var( X ) * S is a ubiased estimator of, where /( Xi ' X ) S * ' OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 95
13 For a radom samle of observatios from N(, ) X ' / ~ N(0, ) X ' S / ~ t ' (also valid i matched-airs situatios) If X is the observed umber of successes i ideedet Beroulli trials i each of which the X robability of success is, ad Y *, the E( Y ) * ad Var( Y ) * ( ' ) For a radom samle of y observatios from observatios from y N(, ) y N(, ) ad, ideedetly, a radom samle of ( X ' Y ) ' ( ' y ) ~ N(0, ) & y y If y * * (ukow) the ( X ' Y ) ' ( ' y ) ~ ` j S & a k b y l t & y ', where ' & y ' y ( ) S ( ) S S * & ' y Correlatio ad Regressio For a set of airs of values (, y ) i i (/ i ) S * /( i ' ) * / i ' (/ yi ) S yy * /( yi ' y) * / yi ' (/ i )(/ yi ) Sy * /( i ' )( yi ' y) * / i yi ' 96 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
14 The roduct momet correlatio coefficiet is (/ i )(/ yi ) S / ( )( ) i yi ' y / i ' yi ' y r * * * S S yy {/( i ' ) }{/( yi ' y) } ` (/ i ) j ` (/ yi ) j a / i ' / yi ' k a k b l b l Searma s rak correlatio coefficiet is 6/ d rs * ' ( ' ) The regressio coefficiet of y o is S /( ' )( y ' y) b * * S y i i /( i ' ) Least squares regressio lie of y o is y * a & b where a * y ' b Distributio-free (No-arametric) Tests Goodess-of-fit test ad cotigecy tables: _ ( O i ' E i ) E i ~ Aroimate distributios for large samles: Wilcoo Siged Rak test: T ~ N ( & ), ( & )( & ) Wilcoo Rak Sum test (samles of sizes m ad, with m D ): W ~ N m( m & & ), m( m & & ) OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 97
15 98 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0 CUMULATIVE BINOMIAL PROBABILITIES / / / / / / / / / / / / / / / / = 5 = 0 5 = 6 = = 7 = = 8 =
16 OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 99 CUMULATIVE BINOMIAL PROBABILITIES / / / / / / / / / / / / = 9 = = 0 = = =
17 00 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0 CUMULATIVE BINOMIAL PROBABILITIES / / / / / / / / = = = 6 =
18 OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 0 CUMULATIVE BINOMIAL PROBABILITIES / / / / / / / / = 8 = = 0 =
19 0 Aedi A: Mathematical Formulae ad Statistical Tables OCR 0 CUMULATIVE BINOMIAL PROBABILITIES / / / / = 5 =
20 OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 0 CUMULATIVE BINOMIAL PROBABILITIES / / / / = 0 =
21 CUMULATIVE POISSON PROBABILITIES = = = = Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
22 CUMULATIVE POISSON PROBABILITIES = = OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 05
23 CUMULATIVE POISSON PROBABILITIES = Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
24 CUMULATIVE POISSON PROBABILITIES = OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 07
25 THE NORMAL DISTRIBUTION FUNCTION If Z has a ormal distributio with mea 0 ad variace the, for each value of z, the table gives the value of.( z), where:.( z) * P( Z D z) For egative values of z use.(' z) * '.( z). z ADD Critical values for the ormal distributio If Z has a ormal distributio with mea 0 ad variace the, for each value of, the table gives the value of z such that: P( Z D z) * z Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
26 CRITICAL VALUES FOR THE t-distribution If T has a t-distributio with degrees of freedom the, for each air of values of ad, the table gives the value of t such that: P( T D t) * = E OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables 09
27 CRITICAL VALUES FOR THE -DISTRIBUTION If X has a -distributio with degrees of freedom the, for each air of values of ad of such that: P( X D ) *, the table gives the value = Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
28 WILCOXON SIGNED RANK TEST P is the sum of the raks corresodig to the ositive differeces, Q is the sum of the raks corresodig to the egative differeces, T is the smaller of P ad Q. For each value of the table gives the largest value of T which will lead to rejectio of the ull hyothesis at the level of sigificace idicated. Critical values of T Level of sigificace Oe Tail Two Tail = For larger values of, each of P ad Q ca be aroimated by the ormal distributio with mea ( & ) ad variace ( & )( & ). OCR 0 Aedi A: Mathematical Formulae ad Statistical Tables
29 WILCOXON RANK SUM TEST The two samles have sizes m ad, where m D. Rm is the sum of the raks of the items i the samle of size m. W is the smaller of Rm ad m( & m & ) ' Rm. For each air of values of m ad, the table gives the largest value of W which will lead to rejectio of the ull hyothesis at the level of sigificace idicated. Critical values of W Level of sigificace Oe Tail Two Tail m = m = m = 5 m = Level of sigificace Oe Tail Two Tail m = 7 m = 8 m = 9 m = For larger values of m ad, the ormal distributio with mea m( m & & ) ad variace m( m & & ) should be used as a aroimatio to the distributio of R m. Aedi A: Mathematical Formulae ad Statistical Tables OCR 0
Notation List. For Cambridge International Mathematics Qualifications. For use from 2020
Notatio List For Cambridge Iteratioal Mathematics Qualificatios For use from 2020 Notatio List for Cambridge Iteratioal Mathematics Qualificatios (For use from 2020) Mathematical otatio Eamiatios for CIE
More informationPearson Edexcel Level 3 Advanced Subsidiary and Advanced GCE in Statistics
Pearso Edecel Level 3 Advaced Subsidiary ad Advaced GCE i Statistics Statistical formulae ad tables For first certificatio from Jue 018 for: Advaced Subsidiary GCE i Statistics (8ST0) For first certificatio
More informationNANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS AO-LEVEL MATHEMATICS
NANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS AO-LEVEL MATHEMATICS STRUCTURE OF EXAMINATION PAPER. There will be oe 2-hour paper cosistig of 4 questios.
More informationIIT JAM Mathematical Statistics (MS) 2006 SECTION A
IIT JAM Mathematical Statistics (MS) 6 SECTION A. If a > for ad lim a / L >, the which of the followig series is ot coverget? (a) (b) (c) (d) (d) = = a = a = a a + / a lim a a / + = lim a / a / + = lim
More information= p x (1 p) 1 x. Var (X) =p(1 p) M X (t) =1+p(e t 1).
Prob. fuctio:, =1 () = 1, =0 = (1 ) 1 E(X) = Var (X) =(1 ) M X (t) =1+(e t 1). 1.1.2 Biomial distributio Parameter: 0 1; >0; MGF: M X (t) ={1+(e t 1)}. Cosider a sequece of ideedet Ber() trials. If X =
More informationPhysicsAndMathsTutor.com
PhysicsAdMathsTutor.com physicsadmathstutor.com Jue 005 3. The fuctio f is defied by (a) Show that 5 + 1 3 f:, > 1. + + f( ) =, > 1. 1 (4) (b) Fid f 1 (). (3) The fuctio g is defied by g: + 5, R. 1 4 (c)
More informationBITSAT MATHEMATICS PAPER III. For the followig liear programmig problem : miimize z = + y subject to the costraits + y, + y 8, y, 0, the solutio is (0, ) ad (, ) (0, ) ad ( /, ) (0, ) ad (, ) (d) (0, )
More information(5x 7) is. 63(5x 7) 42(5x 7) 50(5x 7) BUSINESS MATHEMATICS (Three hours and a quarter)
BUSINESS MATHEMATICS (Three hours ad a quarter) (The first 5 miutes of the examiatio are for readig the paper oly. Cadidate must NOT start writig durig this time). ------------------------------------------------------------------------------------------------------------------------
More informationSolving equations (incl. radical equations) involving these skills, but ultimately solvable by factoring/quadratic formula (no complex roots)
Evet A: Fuctios ad Algebraic Maipulatio Factorig Square of a sum: ( a + b) = a + ab + b Square of a differece: ( a b) = a ab + b Differece of squares: a b = ( a b )(a + b ) Differece of cubes: a 3 b 3
More informationProbability and statistics: basic terms
Probability ad statistics: basic terms M. Veeraraghava August 203 A radom variable is a rule that assigs a umerical value to each possible outcome of a experimet. Outcomes of a experimet form the sample
More informationMATHEMATICS (Three hours and a quarter)
MATHEMATICS (Three hours ad a quarter) (The first fiftee miutes of the eamiatio are for readig the paper oly. Cadidates must NOT start writig durig this time.) Aswer Questio from Sectio A ad questios from
More informationNANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS A-LEVEL MATHEMATICS
NANYANG TECHNOLOGICAL UNIVERSITY SYLLABUS FOR ENTRANCE EXAMINATION FOR INTERNATIONAL STUDENTS A-LEVEL MATHEMATICS STRUCTURE OF EXAMINATION PAPER 1. There will be oe -hour paper cosistig of 4 questios..
More informationLecture 7: Properties of Random Samples
Lecture 7: Properties of Radom Samples 1 Cotiued From Last Class Theorem 1.1. Let X 1, X,...X be a radom sample from a populatio with mea µ ad variace σ
More informationIYGB. Special Extension Paper E. Time: 3 hours 30 minutes. Created by T. Madas. Created by T. Madas
YGB Special Extesio Paper E Time: 3 hours 30 miutes Cadidates may NOT use ay calculator. formatio for Cadidates This practice paper follows the Advaced Level Mathematics Core ad the Advaced Level Further
More informationTwo or more points can be used to describe a rigid body. This will eliminate the need to define rotational coordinates for the body!
OINTCOORDINATE FORMULATION Two or more poits ca be used to describe a rigid body. This will elimiate the eed to defie rotatioal coordiates for the body i z r i i, j r j j rimary oits: The coordiates of
More informationSINGLE CORRECT ANSWER TYPE QUESTIONS: TRIGONOMETRY 2 2
Class-Jr.X_E-E SIMPLE HOLIDAY PACKAGE CLASS-IX MATHEMATICS SUB BATCH : E-E SINGLE CORRECT ANSWER TYPE QUESTIONS: TRIGONOMETRY. siθ+cosθ + siθ cosθ = ) ) ). If a cos q, y bsi q, the a y b ) ) ). The value
More informationMathematical Statistics - MS
Paper Specific Istructios. The examiatio is of hours duratio. There are a total of 60 questios carryig 00 marks. The etire paper is divided ito three sectios, A, B ad C. All sectios are compulsory. Questios
More information2) 3 π. EAMCET Maths Practice Questions Examples with hints and short cuts from few important chapters
EAMCET Maths Practice Questios Examples with hits ad short cuts from few importat chapters. If the vectors pi j + 5k, i qj + 5k are colliear the (p,q) ) 0 ) 3) 4) Hit : p 5 p, q q 5.If the vectors i j
More informationLast time: Moments of the Poisson distribution from its generating function. Example: Using telescope to measure intensity of an object
6.3 Stochastic Estimatio ad Cotrol, Fall 004 Lecture 7 Last time: Momets of the Poisso distributio from its geeratig fuctio. Gs () e dg µ e ds dg µ ( s) µ ( s) µ ( s) µ e ds dg X µ ds X s dg dg + ds ds
More informationphysicsandmathstutor.com
physicsadmathstutor.com 8. The circle C, with cetre at the poit A, has equatio x 2 + y 2 10x + 9 = 0. Fid (a) the coordiates of A, (b) the radius of C, (c) the coordiates of the poits at which C crosses
More informationEton Education Centre JC 1 (2010) Consolidation quiz on Normal distribution By Wee WS (wenshih.wordpress.com) [ For SAJC group of students ]
JC (00) Cosolidatio quiz o Normal distributio By Wee WS (weshih.wordpress.com) [ For SAJC group of studets ] Sped miutes o this questio. Q [ TJC 0/JC ] Mr Fruiti is the ower of a fruit stall sellig a variety
More informationSome Basic Probability Concepts. 2.1 Experiments, Outcomes and Random Variables
Some Basic Probability Cocepts 2. Experimets, Outcomes ad Radom Variables A radom variable is a variable whose value is ukow util it is observed. The value of a radom variable results from a experimet;
More informationFINALTERM EXAMINATION Fall 9 Calculus & Aalytical Geometry-I Questio No: ( Mars: ) - Please choose oe Let f ( x) is a fuctio such that as x approaches a real umber a, either from left or right-had-side,
More informationMathematics Extension 2
004 HIGHER SCHOOL CERTIFICATE EXAMINATION Mathematics Etesio Geeral Istructios Readig time 5 miutes Workig time hours Write usig black or blue pe Board-approved calculators may be used A table of stadard
More informationImportant Formulas. Expectation: E (X) = Σ [X P(X)] = n p q σ = n p q. P(X) = n! X1! X 2! X 3! X k! p X. Chapter 6 The Normal Distribution.
Importat Formulas Chapter 3 Data Descriptio Mea for idividual data: X = _ ΣX Mea for grouped data: X= _ Σf X m Stadard deviatio for a sample: _ s = Σ(X _ X ) or s = 1 (Σ X ) (Σ X ) ( 1) Stadard deviatio
More information3/3/2014. CDS M Phil Econometrics. Types of Relationships. Types of Relationships. Types of Relationships. Vijayamohanan Pillai N.
3/3/04 CDS M Phil Old Least Squares (OLS) Vijayamohaa Pillai N CDS M Phil Vijayamoha CDS M Phil Vijayamoha Types of Relatioships Oly oe idepedet variable, Relatioship betwee ad is Liear relatioships Curviliear
More informationThis section is optional.
4 Momet Geeratig Fuctios* This sectio is optioal. The momet geeratig fuctio g : R R of a radom variable X is defied as g(t) = E[e tx ]. Propositio 1. We have g () (0) = E[X ] for = 1, 2,... Proof. Therefore
More informationAP Calculus BC Review Applications of Derivatives (Chapter 4) and f,
AP alculus B Review Applicatios of Derivatives (hapter ) Thigs to Kow ad Be Able to Do Defiitios of the followig i terms of derivatives, ad how to fid them: critical poit, global miima/maima, local (relative)
More informationAMS570 Lecture Notes #2
AMS570 Lecture Notes # Review of Probability (cotiued) Probability distributios. () Biomial distributio Biomial Experimet: ) It cosists of trials ) Each trial results i of possible outcomes, S or F 3)
More informationIndian Institute of Information Technology, Allahabad. End Semester Examination - Tentative Marking Scheme
Idia Istitute of Iformatio Techology, Allahabad Ed Semester Examiatio - Tetative Markig Scheme Course Name: Mathematics-I Course Code: SMAT3C MM: 75 Program: B.Tech st year (IT+ECE) ate of Exam:..7 ( st
More informationPhysicsAndMathsTutor.com
PhysicsAdMathsTutor.com physicsadmathstutor.com Jue 005 4. f(x) = 3e x 1 l x, x > 0. (a) Differetiate to fid f (x). (3) The curve with equatio y = f(x) has a turig poit at P. The x-coordiate of P is α.
More informationTHE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA STATISTICAL THEORY AND METHODS PAPER I
THE ROYAL STATISTICAL SOCIETY 5 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA STATISTICAL THEORY AND METHODS PAPER I The Society provides these solutios to assist cadidates preparig for the examiatios i future
More informationVIVEKANANDA VIDYALAYA MATRIC HR SEC SCHOOL FIRST MODEL EXAM (A) 10th Standard Reg.No. : MATHEMATICS - MOD EXAM 1(A)
Time : 0:30:00 Hrs VIVEKANANDA VIDYALAYA MATRIC HR SEC SCHOOL FIRST MODEL EXAM 018-19(A) 10th Stadard Reg.No. : MATHEMATICS - MOD EXAM 1(A) Total Mark : 100 I. CHOOSE THE BEST ANSWER WITH CORRECT OPTION:-
More informationCEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering
CEE 5 Autum 005 Ucertaity Cocepts for Geotechical Egieerig Basic Termiology Set A set is a collectio of (mutually exclusive) objects or evets. The sample space is the (collectively exhaustive) collectio
More informationAIEEE 2004 (MATHEMATICS)
AIEEE 00 (MATHEMATICS) Importat Istructios: i) The test is of hours duratio. ii) The test cosists of 75 questios. iii) The maimum marks are 5. iv) For each correct aswer you will get marks ad for a wrog
More informationWBJEE Answer Keys by Aakash Institute, Kolkata Centre
WBJEE - 7 Aswer Keys by, Kolkata Cetre MATHEMATICS Q.No. B A C B A C A B 3 D C B B 4 B C D D 5 D A B B 6 C D B B 7 B C C A 8 B B A A 9 A * B D C C B B D A A D B B C B 3 A D D D 4 C B A A 5 C B B B 6 C
More informationDirection: This test is worth 150 points. You are required to complete this test within 55 minutes.
Term Test 3 (Part A) November 1, 004 Name Math 6 Studet Number Directio: This test is worth 10 poits. You are required to complete this test withi miutes. I order to receive full credit, aswer each problem
More informationMTH112 Trigonometry 2 2 2, 2. 5π 6. cscθ = 1 sinθ = r y. secθ = 1 cosθ = r x. cotθ = 1 tanθ = cosθ. central angle time. = θ t.
MTH Trigoometry,, 5, 50 5 0 y 90 0, 5 0,, 80 0 0 0 (, 0) x, 7, 0 5 5 0, 00 5 5 0 7,,, Defiitios: siθ = opp. hyp. = y r cosθ = adj. hyp. = x r taθ = opp. adj. = siθ cosθ = y x cscθ = siθ = r y secθ = cosθ
More informationJEE(Advanced) 2018 TEST PAPER WITH SOLUTION (HELD ON SUNDAY 20 th MAY, 2018)
JEE(Advaced) 08 TEST PAPER WITH SOLUTION (HELD ON SUNDAY 0 th MAY, 08) PART- : JEE(Advaced) 08/Paper- SECTION. For ay positive iteger, defie ƒ : (0, ) as ƒ () j ta j j for all (0, ). (Here, the iverse
More informationUnbiased Estimation. February 7-12, 2008
Ubiased Estimatio February 7-2, 2008 We begi with a sample X = (X,..., X ) of radom variables chose accordig to oe of a family of probabilities P θ where θ is elemet from the parameter space Θ. For radom
More information4. Basic probability theory
Cotets Basic cocepts Discrete radom variables Discrete distributios (br distributios) Cotiuous radom variables Cotiuous distributios (time distributios) Other radom variables Lect04.ppt S-38.45 - Itroductio
More informationMATH 320: Probability and Statistics 9. Estimation and Testing of Parameters. Readings: Pruim, Chapter 4
MATH 30: Probability ad Statistics 9. Estimatio ad Testig of Parameters Estimatio ad Testig of Parameters We have bee dealig situatios i which we have full kowledge of the distributio of a radom variable.
More informationMathematics Extension 1
016 Bored of Studies Trial Eamiatios Mathematics Etesio 1 3 rd ctober 016 Geeral Istructios Total Marks 70 Readig time 5 miutes Workig time hours Write usig black or blue pe Black pe is preferred Board-approved
More informationHigher Course Plan. Calculus and Relationships Expressions and Functions
Higher Course Pla Applicatios Calculus ad Relatioships Expressios ad Fuctios Topic 1: The Straight Lie Fid the gradiet of a lie Colliearity Kow the features of gradiets of: parallel lies perpedicular lies
More informationMathematics Extension 2
009 HIGHER SCHOOL CERTIFICATE EXAMINATION Mathematics Etesio Geeral Istructios Readig time 5 miutes Workig time hours Write usig black or blue pe Board-approved calculators may be used A table of stadard
More informationAgenda: Recap. Lecture. Chapter 12. Homework. Chapt 12 #1, 2, 3 SAS Problems 3 & 4 by hand. Marquette University MATH 4740/MSCS 5740
Ageda: Recap. Lecture. Chapter Homework. Chapt #,, 3 SAS Problems 3 & 4 by had. Copyright 06 by D.B. Rowe Recap. 6: Statistical Iferece: Procedures for μ -μ 6. Statistical Iferece Cocerig μ -μ Recall yes
More informationSongklanakarin Journal of Science and Technology SJST R1 Teerapabolarn
Soglaaari Joural of Sciece ad Techology SJST--.R Teeraabolar A No-uiform Boud o Biomial Aroimatio to the Beta Biomial Cumulative Distributio Fuctio Joural: Soglaaari Joural of Sciece ad Techology For Review
More informationVITEEE 2018 MATHEMATICS QUESTION BANK
VITEEE 8 MTHEMTICS QUESTION BNK, C = {,, 6}, the (B C) Ques. Give the sets {,,},B {, } is {} {,,, } {,,, } {,,,,, 6} Ques. s. d ( si cos ) c ta log( ta 6 Ques. The greatest umer amog 9,, 7 is ) c c cot
More informationAdvanced Engineering Mathematics Exercises on Module 4: Probability and Statistics
Advaced Egieerig Mathematics Eercises o Module 4: Probability ad Statistics. A survey of people i give regio showed that 5% drak regularly. The probability of death due to liver disease, give that a perso
More informationEE 4TM4: Digital Communications II Probability Theory
1 EE 4TM4: Digital Commuicatios II Probability Theory I. RANDOM VARIABLES A radom variable is a real-valued fuctio defied o the sample space. Example: Suppose that our experimet cosists of tossig two fair
More informationSTATISTICAL METHODS FOR BUSINESS
STATISTICAL METHODS FOR BUSINESS UNIT 5. Joit aalysis ad limit theorems. 5.1.- -dimesio distributios. Margial ad coditioal distributios 5.2.- Sequeces of idepedet radom variables. Properties 5.3.- Sums
More informationExponential Families and Bayesian Inference
Computer Visio Expoetial Families ad Bayesia Iferece Lecture Expoetial Families A expoetial family of distributios is a d-parameter family f(x; havig the followig form: f(x; = h(xe g(t T (x B(, (. where
More information2. The volume of the solid of revolution generated by revolving the area bounded by the
IIT JAM Mathematical Statistics (MS) Solved Paper. A eigevector of the matrix M= ( ) is (a) ( ) (b) ( ) (c) ( ) (d) ( ) Solutio: (a) Eigevalue of M = ( ) is. x So, let x = ( y) be the eigevector. z (M
More informationGULF MATHEMATICS OLYMPIAD 2014 CLASS : XII
GULF MATHEMATICS OLYMPIAD 04 CLASS : XII Date of Eamiatio: Maimum Marks : 50 Time : 0:30 a.m. to :30 p.m. Duratio: Hours Istructios to cadidates. This questio paper cosists of 50 questios. All questios
More information[ ] ( ) ( ) [ ] ( ) 1 [ ] [ ] Sums of Random Variables Y = a 1 X 1 + a 2 X 2 + +a n X n The expected value of Y is:
PROBABILITY FUNCTIONS A radom variable X has a probabilit associated with each of its possible values. The probabilit is termed a discrete probabilit if X ca assume ol discrete values, or X = x, x, x 3,,
More informationSS3 QUESTIONS FOR 2018 MATHSCHAMP. 3. How many vertices has a hexagonal prism? A. 6 B. 8 C. 10 D. 12
SS3 QUESTIONS FOR 8 MATHSCHAMP. P ad Q are two matrices such that their dimesios are 3 by 4 ad 4 by 3 respectively. What is the dimesio of the product PQ? 3 by 3 4 by 4 3 by 4 4 by 3. What is the smallest
More informationSECTION A (100 Marks) Duration: Three Hours Maximum Marks: A matrix M has eigen values 1 and 4 with corresponding eigen vectors 1, 1.
MATHEMATICS Duratio: Three Hours Maimum Marks: 50 Read the followig istructios carefully. Write all the aswers i the aswer book.. This questio aer cosists of TWO SECTIONS: A ad B. 3. Sectio A has Eight
More informationReview Questions, Chapters 8, 9. f(y) = 0, elsewhere. F (y) = f Y(1) = n ( e y/θ) n 1 1 θ e y/θ = n θ e yn
Stat 366 Lab 2 Solutios (September 2, 2006) page TA: Yury Petracheko, CAB 484, yuryp@ualberta.ca, http://www.ualberta.ca/ yuryp/ Review Questios, Chapters 8, 9 8.5 Suppose that Y, Y 2,..., Y deote a radom
More informationNATIONAL SENIOR CERTIFICATE GRADE 12
NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS P FEBRUARY/MARCH 009 MARKS: 50 TIME: 3 hours This questio paper cosists of 0 pages, a iformatio sheet ad 3 diagram sheets. Please tur over Mathematics/P DoE/Feb.
More informationGCE. Mathematics (MEI) Mark Scheme for January Advanced GCE Unit 4756: Further Methods for Advanced Mathematics PMT
GCE Mathematics (MEI) Advaced GCE Uit 476: Further Methods for Advaced Mathematics Mark Scheme for Jauar Oford Cambridge ad RSA Eamiatios 476 Mark Scheme Jauar (a) (i) a d ta a sec M Differetiatig with
More informationMathematics Extension 2 SOLUTIONS
3 HSC Examiatio Mathematics Extesio SOLUIONS Writte by Carrotstics. Multiple Choice. B 6. D. A 7. C 3. D 8. C 4. A 9. B 5. B. A Brief Explaatios Questio Questio Basic itegral. Maipulate ad calculate as
More informationHypothesis Testing. H 0 : θ 1 1. H a : θ 1 1 (but > 0... required in distribution) Simple Hypothesis - only checks 1 value
Hyothesis estig ME's are oit estimates of arameters/coefficiets really have a distributio Basic Cocet - develo regio i which we accet the hyothesis ad oe where we reject it H - reresets all ossible values
More informationEDEXCEL STUDENT CONFERENCE 2006 A2 MATHEMATICS STUDENT NOTES
EDEXCEL STUDENT CONFERENCE 006 A MATHEMATICS STUDENT NOTES South: Thursday 3rd March 006, Lodo EXAMINATION HINTS Before the eamiatio Obtai a copy of the formulae book ad use it! Write a list of ad LEARN
More informationFinal Review. Fall 2013 Prof. Yao Xie, H. Milton Stewart School of Industrial Systems & Engineering Georgia Tech
Fial Review Fall 2013 Prof. Yao Xie, yao.xie@isye.gatech.edu H. Milto Stewart School of Idustrial Systems & Egieerig Georgia Tech 1 Radom samplig model radom samples populatio radom samples: x 1,..., x
More informationPresentation of complex number in Cartesian and polar coordinate system
a + bi, aεr, bεr i = z = a + bi a = Re(z), b = Im(z) give z = a + bi & w = c + di, a + bi = c + di a = c & b = d The complex cojugate of z = a + bi is z = a bi The sum of complex cojugates is real: z +
More informationLecture 2: Poisson Sta*s*cs Probability Density Func*ons Expecta*on and Variance Es*mators
Lecture 2: Poisso Sta*s*cs Probability Desity Fuc*os Expecta*o ad Variace Es*mators Biomial Distribu*o: P (k successes i attempts) =! k!( k)! p k s( p s ) k prob of each success Poisso Distributio Note
More information( ) = is larger than. the variance of X V
Stat 400, sectio 6. Methods of Poit Estimatio otes by Tim Pilachoski A oit estimate of a arameter is a sigle umber that ca be regarded as a sesible value for The selected statistic is called the oit estimator
More informationClassical Mechanics Qualifying Exam Solutions Problem 1.
Jauary 4, Uiversity of Illiois at Chicago Departmet of Physics Classical Mechaics Qualifyig Exam Solutios Prolem. A cylider of a o-uiform radial desity with mass M, legth l ad radius R rolls without slippig
More informationCARIBBEAN EXAMINATIONS COUNCIL CARIBBEAN SECONDARY EDUCATION EXAMINATION ADDITIONAL MATHEMATICS. Paper 02 - General Proficiency
TEST CODE 01254020 FORM TP 2015037 MAY/JUNE 2015 CARIBBEAN EXAMINATIONS COUNCIL CARIBBEAN SECONDARY EDUCATION CERTIFICATE@ EXAMINATION ADDITIONAL MATHEMATICS Paper 02 - Geeral Proficiecy 2 hours 40 miutes
More informationStochastic Structural Dynamics. Lecture-28. Monte Carlo simulation approach-4
Stochastic Structural Dyamics Lecture-8 Mote Carlo simulatio approach-4 Dr C S Maohar Departmet of Civil Egieerig Professor of Structural Egieerig Idia Istitute of Sciece Bagalore 56 Idia maohar@civil.iisc.eret.i
More information4. Partial Sums and the Central Limit Theorem
1 of 10 7/16/2009 6:05 AM Virtual Laboratories > 6. Radom Samples > 1 2 3 4 5 6 7 4. Partial Sums ad the Cetral Limit Theorem The cetral limit theorem ad the law of large umbers are the two fudametal theorems
More informationCALCULUS BASIC SUMMER REVIEW
CALCULUS BASIC SUMMER REVIEW NAME rise y y y Slope of a o vertical lie: m ru Poit Slope Equatio: y y m( ) The slope is m ad a poit o your lie is, ). ( y Slope-Itercept Equatio: y m b slope= m y-itercept=
More informationChapter 2 Transformations and Expectations
Chapter Trasformatios a Epectatios Chapter Distributios of Fuctios of a Raom Variable Problem: Let be a raom variable with cf F ( ) If we efie ay fuctio of, say g( ) g( ) is also a raom variable whose
More informationphysicsandmathstutor.com
physicsadmathstutor.com 1. Fid the coordiates of the statioary poit o the curve with equatio y = 1. (4) Q1 (Total 4 marks) *N349B038* 3 Tur over 10. Figure 1 y 8 y = + 5 P R Q O Figure 1 shows part of
More informationRay Optics Theory and Mode Theory. Dr. Mohammad Faisal Dept. of EEE, BUET
Ray Optics Theory ad Mode Theory Dr. Mohammad Faisal Dept. of, BUT Optical Fiber WG For light to be trasmitted through fiber core, i.e., for total iteral reflectio i medium, > Ray Theory Trasmissio Ray
More informationStatistics Revision Solutions
Statistics Revisio Solutios (i) H ~N (00, ) ad W ~N (7, 9 ) P ( 7. 0) 0. 978 P (iii) H + W ~N (7, ) P ( H + W > A) > 0.9 P( H + W < A) < 0.0 A< ivnorm(0.0,
More informationTopic 5 [434 marks] (i) Find the range of values of n for which. (ii) Write down the value of x dx in terms of n, when it does exist.
Topic 5 [44 marks] 1a (i) Fid the rage of values of for which eists 1 Write dow the value of i terms of 1, whe it does eist Fid the solutio to the differetial equatio 1b give that y = 1 whe = π (cos si
More informationFundamental Concepts: Surfaces and Curves
UNDAMENTAL CONCEPTS: SURACES AND CURVES CHAPTER udametal Cocepts: Surfaces ad Curves. INTRODUCTION This chapter describes two geometrical objects, vi., surfaces ad curves because the pla a ver importat
More informationStat 319 Theory of Statistics (2) Exercises
Kig Saud Uiversity College of Sciece Statistics ad Operatios Research Departmet Stat 39 Theory of Statistics () Exercises Refereces:. Itroductio to Mathematical Statistics, Sixth Editio, by R. Hogg, J.
More informationPhysicsAndMathsTutor.com
PhysicsAdMthsTutor.com PhysicsAdMthsTutor.com Jue 009 4. Give tht y rsih ( ), > 0, () fid d y d, givig your swer s simplified frctio. () Leve lk () Hece, or otherwise, fid 4 d, 4 [ ( )] givig your swer
More informationS Y Y = ΣY 2 n. Using the above expressions, the correlation coefficient is. r = SXX S Y Y
1 Sociology 405/805 Revised February 4, 004 Summary of Formulae for Bivariate Regressio ad Correlatio Let X be a idepedet variable ad Y a depedet variable, with observatios for each of the values of these
More informationDescribing the Relation between Two Variables
Copyright 010 Pearso Educatio, Ic. Tables ad Formulas for Sulliva, Statistics: Iformed Decisios Usig Data 010 Pearso Educatio, Ic Chapter Orgaizig ad Summarizig Data Relative frequecy = frequecy sum of
More informationMTH Assignment 1 : Real Numbers, Sequences
MTH -26 Assigmet : Real Numbers, Sequeces. Fid the supremum of the set { m m+ : N, m Z}. 2. Let A be a o-empty subset of R ad α R. Show that α = supa if ad oly if α is ot a upper boud of A but α + is a
More informationTAMS24: Notations and Formulas
TAMS4: Notatios ad Formulas Basic otatios ad defiitios X: radom variable stokastiska variabel Mea Vätevärde: µ = X = by Xiagfeg Yag kpx k, if X is discrete, xf Xxdx, if X is cotiuous Variace Varias: =
More informationMATHEMATICS. The assessment objectives of the Compulsory Part are to test the candidates :
MATHEMATICS INTRODUCTION The public assessmet of this subject is based o the Curriculum ad Assessmet Guide (Secodary 4 6) Mathematics joitly prepared by the Curriculum Developmet Coucil ad the Hog Kog
More informationPAPER : IIT-JAM 2010
MATHEMATICS-MA (CODE A) Q.-Q.5: Oly oe optio is correct for each questio. Each questio carries (+6) marks for correct aswer ad ( ) marks for icorrect aswer.. Which of the followig coditios does NOT esure
More information3 Show in each case that there is a root of the given equation in the given interval. a x 3 = 12 4
C Worksheet A Show i each case that there is a root of the equatio f() = 0 i the give iterval a f() = + 7 (, ) f() = 5 cos (05, ) c f() = e + + 5 ( 6, 5) d f() = 4 5 + (, ) e f() = l (4 ) + (04, 05) f
More informationCalculus 2 Test File Spring Test #1
Calculus Test File Sprig 009 Test #.) Without usig your calculator, fid the eact area betwee the curves f() = - ad g() = +..) Without usig your calculator, fid the eact area betwee the curves f() = ad
More informationEcon 325/327 Notes on Sample Mean, Sample Proportion, Central Limit Theorem, Chi-square Distribution, Student s t distribution 1.
Eco 325/327 Notes o Sample Mea, Sample Proportio, Cetral Limit Theorem, Chi-square Distributio, Studet s t distributio 1 Sample Mea By Hiro Kasahara We cosider a radom sample from a populatio. Defiitio
More informationLogit regression Logit regression
Logit regressio Logit regressio models the probability of Y= as the cumulative stadard logistic distributio fuctio, evaluated at z = β 0 + β X: Pr(Y = X) = F(β 0 + β X) F is the cumulative logistic distributio
More informationHKDSE Exam Questions Distribution
HKDSE Eam Questios Distributio Sample Paper Practice Paper DSE 0 Topics A B A B A B. Biomial Theorem. Mathematical Iductio 0 3 3 3. More about Trigoometric Fuctios, 0, 3 0 3. Limits 6. Differetiatio 7
More informationMath 143 Review for Quiz 14 page 1
Math Review for Quiz age. Solve each of the followig iequalities. x + a) < x + x c) x d) x x +
More informationStatistics 300: Elementary Statistics
Statistics 300: Elemetary Statistics Sectios 7-, 7-3, 7-4, 7-5 Parameter Estimatio Poit Estimate Best sigle value to use Questio What is the probability this estimate is the correct value? Parameter Estimatio
More informationEECS564 Estimation, Filtering, and Detection Hwk 2 Solns. Winter p θ (z) = (2θz + 1 θ), 0 z 1
EECS564 Estimatio, Filterig, ad Detectio Hwk 2 Sols. Witer 25 4. Let Z be a sigle observatio havig desity fuctio where. p (z) = (2z + ), z (a) Assumig that is a oradom parameter, fid ad plot the maximum
More informationNovember 2002 Course 4 solutions
November Course 4 solutios Questio # Aswer: B φ ρ = = 5. φ φ ρ = φ + =. φ Solvig simultaeously gives: φ = 8. φ = 6. Questio # Aswer: C g = [(.45)] = [5.4] = 5; h= 5.4 5 =.4. ˆ π =.6 x +.4 x =.6(36) +.4(4)
More informationAssignment 1 : Real Numbers, Sequences. for n 1. Show that (x n ) converges. Further, by observing that x n+2 + x n+1
Assigmet : Real Numbers, Sequeces. Let A be a o-empty subset of R ad α R. Show that α = supa if ad oly if α is ot a upper boud of A but α + is a upper boud of A for every N. 2. Let y (, ) ad x (, ). Evaluate
More informationTMA4245 Statistics. Corrected 30 May and 4 June Norwegian University of Science and Technology Department of Mathematical Sciences.
Norwegia Uiversity of Sciece ad Techology Departmet of Mathematical Scieces Corrected 3 May ad 4 Jue Solutios TMA445 Statistics Saturday 6 May 9: 3: Problem Sow desity a The probability is.9.5 6x x dx
More informationJoint Probability Distributions and Random Samples. Jointly Distributed Random Variables. Chapter { }
UCLA STAT A Applied Probability & Statistics for Egieers Istructor: Ivo Diov, Asst. Prof. I Statistics ad Neurology Teachig Assistat: Neda Farziia, UCLA Statistics Uiversity of Califoria, Los Ageles, Sprig
More informationof the matrix is =-85, so it is not positive definite. Thus, the first
BOSTON COLLEGE Departmet of Ecoomics EC771: Ecoometrics Sprig 4 Prof. Baum, Ms. Uysal Solutio Key for Problem Set 1 1. Are the followig quadratic forms positive for all values of x? (a) y = x 1 8x 1 x
More informationENGI 4421 Discrete Probability Distributions Page Discrete Probability Distributions [Navidi sections ; Devore sections
ENGI 441 Discrete Probability Distributios Page 9-01 Discrete Probability Distributios [Navidi sectios 4.1-4.4; Devore sectios 3.4-3.6] Chater 5 itroduced the cocet of robability mass fuctios for discrete
More information