PLEASURE TEST SERIES (XI) - 04 By O.P. Gupta (For stuffs on Math, click at theopgupta.com)

Size: px
Start display at page:

Download "PLEASURE TEST SERIES (XI) - 04 By O.P. Gupta (For stuffs on Math, click at theopgupta.com)"

Transcription

1 wwwtheopguptacom wwwimathematiciacom For all the Math-Gya Buy books by OP Gupta A Compilatio By : OP Gupta ) For more stuffs o Maths, please visit : wwwtheopguptacom Time Allowed : 0 Miutes Max Marks : 00 SECTION A Questio umbers 0 to 0 carry mark each π Q0 Fid the value of si Q0 Write the derivative of x (3 6x ) with respect to x Fid f ( ), if f (x) cos x Q03 Write the real ad imagiary part of the zero complex umber Q0 If z 3 i, fid the value of zz SECTION B Questio umbers 05 to carry marks each Q05 If P(A) 3/5 ad, P(B) /5, fid P(A or B), if A ad B are mutually exclusive evets Q06 (i) Write the coverse of the followig statemet : If a umber is eve, the is eve (ii) Write the cotrapositive of the followig statemet : If you are bor i Idia, the you are a citize of Idia Q07 A committee of 5 is to be formed out of 6 males ad females I how may ways this ca be doe whe icluded females are i majority? Q0 Differetiate x w r t x x Q09 If ta x cot x, prove that ta x cot x, N Fid the value of ta(9π/) Q0 Fid the distace betwee the lies 5x y 3 ad 5x y 3 0 Check if the lies 3x y ad x 3y are perpedicular or ot Q State whether the sets {x : x is a eve iteger} ad {x : x is a odd iteger} are pair of disjoit sets or ot x 3 cos x e e Q Evaluate : Write the value of xπ/ (π x) x3 x 3 SECTION C Questio umbers 3 to 3 carry marks each Q3 Fid the term idepedet of x i the biomial expasio of (a) x 3x (b) x 3 3 x Q Fid the equatio of the circle passig through the poits (, 3) ad (, ) ad whose cetre is o the lie x 3y Fid the equatio of ellipse, with major axis alog the x-axis ad passig through the poits P(, 3) ad Q(, ) PLEASURE TEST SERIES (XI) - 0 By OP Gupta (For stuffs o Math, click at theopguptacom)

2 PTS-0 By OP Gupta (M ) Q5 Let A {x : x N, x 0} Defie a relatio R from A to A by R {(a,b) : a b 0; a,b N} Depict the relatio R usig roster form Write its domai ad rage also Q6 Fid the coordiates of a poit o y-axis which are at a distace of 5 from the poit (3,, 5) Q7 Determie the coordiates of the foot of perpedicular draw from the poit (, 3) from the lie 3x y 6 0 Fid the equatio of the circle which is circumscribed about the whose vertices are (, 3), (5, ) ad (6, ) Q If the sum of terms of a AP is 3 5 ad its m th term is 6, fid the value of m Q9 A girl has 3 library book passes ad books of her iterest are there i the library Of these books she does ot wat to borrow Mathematicia Vol uless Mathematicia Vol is also borrowed I how may ways ca she choose the three books to be borrowed? Q0 Fid the domai of f (x) [x] [x] 3 Fid the domai ad rage of the real valued fuctio f (x) x Q If o o x cos ycos 0 z cos 0, the fid the value of xy yz zx Q Three squares of a chess board are selected at radom, fid the probability of selectig two squares of oe colour ad the other of a differet colour Q3 Usig priciple of iductio, show that N ( )( 3) 3( 3) SECTION D Questio umbers to 9 carry 6 marks each Q The mea ad SD of a group of 00 observatios were foud to be 0 ad 3 respectively O recheckig, it was observed that three etries were icorrect, which were recorded as, ad, Fid the mea ad SD if the icorrect etries were omitted Q5 I a survey of 60 people, it was foud that 5 people read ewspaper H, 6 read ewspaper T ad 6 read ewspaper I, 9 read both Had I, read H ad T, read both T ad I ad 3 read all the three ewspapers Fid the umber of people who read (a) at least oe of the ewspapers (b) exactly oe ewspaper I a tow of 0000 families, it was foud that 0% families buy fruit A, 0% families buy fruit B, 0% families buy fruit C, 5% families buy A ad B, 3% buy B ad C ad, % buy A ad C If % families buy all the three kid of fruits, fid the umber of families which buy (a) fruit A oly (b) oe of A, B ad C Q6 (a) Fid the geeral solutio of the equatio ta 5x ta x 3 7 (b) Evaluate cos cos cos cos o o o o o o o o Prove that si0 si 30 si 50 si 70 Hece evaluate cos0 cos0 cos60 cos0 6 Q7 Let S to terms Differetiate S w r t (si x cos x) Evaluate : x si x Q Solve the system of iequatios graphically : x y, 3x y, x y, x 0, y 0 z Q9 If Im, the show that the locus of the poit represetig z i the Argad plae is a iz straight lie PLEASURE TEST SERIES (XI) - 0 By OP Gupta (For stuffs o Math, click at theopguptacom)

3 PTS-0 By OP Gupta (M ) 3 HINTS & ANSWERS for PTS XI 0 SECTION A Q0 π π π 3 si si π si Q0 Let y x (36x ) 5 y 3x 6x dy 5 O differetiatig w r t x, we get : 5x x dx We have f (x) cos x f (x) cos x si x six f ( ) si 0 Q03 Let z 0 0i Re(z) 0 ad Im(z) 0 Q0 7 SECTION B Q05 3 P(A or B) P(A) P(B) P(A ad B) [As A ad B are mutually exclusive evets so, P(A ad B) = 0 Q06 (i) If a umber is eve, the is eve (ii) If you are ot a citize of Idia, the you are ot bor i Idia Q07 36 x dy Q0 Let y x x dx (x ) Q09 As ta x cot x ta x (ta x ) 0 ta x ta x ta( /) x /, Z Now LHS: ta x cot x ta cot RHS cos si 9π π We have ta ta ta cos cos cos cos 9 ta Q0 Note that the lies 5x y 3 ad 5x y 3 0 are parallel lies as they have same slopes Writig them i slope-itercept form, we have : L : y x ad L : y x c c 65 Sice distace betwee two parallel lies uits m Slope of 3x y ad x 3y are respectively m ad m 3 3 Now m m so, these lies are perpedicular to each other 3 Q Let A {x : x is a eve iteger} ad B {x : x is a odd iteger} PLEASURE TEST SERIES (XI) - 0 By OP Gupta (For stuffs o Math, click at theopguptacom)

4 PTS-0 By OP Gupta (M ) So, A {,,0,,,} ad B {, 3,,,3,} Clearly A B A ad B are disjoit sets π π si x si x cos x () π π π x 0 π x0 π x0 π cos x Q xπ/ (π x) x x x x 3 3 x3 e e e (e ) 3 3 e e x3 x 3 x30 x 3 SECTION C Q3 (a) 7 th term ie, 9 C6 (b) 3 rd term ie, 0 C 6 0 Q6 (0,, 0), (0, 6, 0) Q 7 Q Let x cos k cos (i) k x So, k cos (ii) ad k cos (iii) 3 y 3 z Addig these equatios, we get : k cos k cos k cos x y z 3 3 yz zx zy k cos cos cos k cos cos xyz C C Q 6 C3 SECTION D Q5 (a) 5 (b) 30 Q6 (a) ta 5x cot x ta x 5x x x, Z (b) cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos cos Q7 Sice S a a 3 3 S 3 3 ( )() ( ) S 3 3 S ds Now differetiatig w r t, we get : 0 d ( ) ( ) (si x cos x) si x x 5 (si x cos x) ( ) (si x cos x) ( ) si xcosx 5 5 xy yz zx 0 PLEASURE TEST SERIES (XI) - 0 By OP Gupta (For stuffs o Math, click at theopguptacom)

5 PTS-0 By OP Gupta (M ) (si x cos x) ( ) (si x cos x) ( ) si xcosx 5( ) 5 (si x cos x) ( ) (si x cos x) ( ) ( ) x iy x iy y ix Q9 Let z x iy Im Im ix i y y ix y ix ( x y) i(y y x x) y y x x Im ( y) x ( y) x y y x x y y x x y 0, which is a straight lie PLEASURE TEST SERIES (XI) - 0 By OP Gupta (For stuffs o Math, click at theopguptacom)

Alpha Individual Solutions MAΘ National Convention 2013

Alpha Individual Solutions MAΘ National Convention 2013 Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5

More information

The Closest Line to a Data Set in the Plane. David Gurney Southeastern Louisiana University Hammond, Louisiana

The Closest Line to a Data Set in the Plane. David Gurney Southeastern Louisiana University Hammond, Louisiana The Closest Lie to a Data Set i the Plae David Gurey Southeaster Louisiaa Uiversity Hammod, Louisiaa ABSTRACT This paper looks at three differet measures of distace betwee a lie ad a data set i the plae:

More information

Mathematical Stat I: solutions of homework 1

Mathematical Stat I: solutions of homework 1 Mathematical Stat I: solutios of homework Name: Studet Id N:. Suppose we tur over cards simultaeously from two well shuffled decks of ordiary playig cards. We say we obtai a exact match o a particular

More information

Pattern Recognition Systems Lab 1 Least Mean Squares

Pattern Recognition Systems Lab 1 Least Mean Squares Patter Recogitio Systems Lab 1 Least Mea Squares 1. Objectives This laboratory work itroduces the OpeCV-based framework used throughout the course. I this assigmet a lie is fitted to a set of poits usig

More information

Arithmetic Sequences

Arithmetic Sequences . Arithmetic Sequeces COMMON CORE Learig Stadards HSF-IF.A. HSF-BF.A.1a HSF-BF.A. HSF-LE.A. Essetial Questio How ca you use a arithmetic sequece to describe a patter? A arithmetic sequece is a ordered

More information

Math Section 2.2 Polynomial Functions

Math Section 2.2 Polynomial Functions Math 1330 - Sectio. Polyomial Fuctios Our objectives i workig with polyomial fuctios will be, first, to gather iformatio about the graph of the fuctio ad, secod, to use that iformatio to geerate a reasoably

More information

EVALUATION OF TRIGONOMETRIC FUNCTIONS

EVALUATION OF TRIGONOMETRIC FUNCTIONS EVALUATION OF TRIGONOMETRIC FUNCTIONS Whe first exposed to trigoometric fuctios i high school studets are expected to memorize the values of the trigoometric fuctios of sie cosie taget for the special

More information

1.2 Binomial Coefficients and Subsets

1.2 Binomial Coefficients and Subsets 1.2. BINOMIAL COEFFICIENTS AND SUBSETS 13 1.2 Biomial Coefficiets ad Subsets 1.2-1 The loop below is part of a program to determie the umber of triagles formed by poits i the plae. for i =1 to for j =

More information

9 x and g(x) = 4. x. Find (x) 3.6. I. Combining Functions. A. From Equations. Example: Let f(x) = and its domain. Example: Let f(x) = and g(x) = x x 4

9 x and g(x) = 4. x. Find (x) 3.6. I. Combining Functions. A. From Equations. Example: Let f(x) = and its domain. Example: Let f(x) = and g(x) = x x 4 1 3.6 I. Combiig Fuctios A. From Equatios Example: Let f(x) = 9 x ad g(x) = 4 f x. Fid (x) g ad its domai. 4 Example: Let f(x) = ad g(x) = x x 4. Fid (f-g)(x) B. From Graphs: Graphical Additio. Example:

More information

Recursive Estimation

Recursive Estimation Recursive Estimatio Raffaello D Adrea Sprig 2 Problem Set: Probability Review Last updated: February 28, 2 Notes: Notatio: Uless otherwise oted, x, y, ad z deote radom variables, f x (x) (or the short

More information

The isoperimetric problem on the hypercube

The isoperimetric problem on the hypercube The isoperimetric problem o the hypercube Prepared by: Steve Butler November 2, 2005 1 The isoperimetric problem We will cosider the -dimesioal hypercube Q Recall that the hypercube Q is a graph whose

More information

2) Give an example of a polynomial function of degree 4 with leading coefficient of -6

2) Give an example of a polynomial function of degree 4 with leading coefficient of -6 Math 165 Read ahead some cocepts from sectios 4.1 Read the book or the power poit presetatios for this sectio to complete pages 1 ad 2 Please, do ot complete the other pages of the hadout If you wat to

More information

Intro to Scientific Computing: Solutions

Intro to Scientific Computing: Solutions Itro to Scietific Computig: Solutios Dr. David M. Goulet. How may steps does it take to separate 3 objects ito groups of 4? We start with 5 objects ad apply 3 steps of the algorithm to reduce the pile

More information

Math 10C Long Range Plans

Math 10C Long Range Plans Math 10C Log Rage Plas Uits: Evaluatio: Homework, projects ad assigmets 10% Uit Tests. 70% Fial Examiatio.. 20% Ay Uit Test may be rewritte for a higher mark. If the retest mark is higher, that mark will

More information

CS 683: Advanced Design and Analysis of Algorithms

CS 683: Advanced Design and Analysis of Algorithms CS 683: Advaced Desig ad Aalysis of Algorithms Lecture 6, February 1, 2008 Lecturer: Joh Hopcroft Scribes: Shaomei Wu, Etha Feldma February 7, 2008 1 Threshold for k CNF Satisfiability I the previous lecture,

More information

South Slave Divisional Education Council. Math 10C

South Slave Divisional Education Council. Math 10C South Slave Divisioal Educatio Coucil Math 10C Curriculum Package February 2012 12 Strad: Measuremet Geeral Outcome: Develop spatial sese ad proportioal reasoig It is expected that studets will: 1. Solve

More information

EM375 STATISTICS AND MEASUREMENT UNCERTAINTY LEAST SQUARES LINEAR REGRESSION ANALYSIS

EM375 STATISTICS AND MEASUREMENT UNCERTAINTY LEAST SQUARES LINEAR REGRESSION ANALYSIS EM375 STATISTICS AND MEASUREMENT UNCERTAINTY LEAST SQUARES LINEAR REGRESSION ANALYSIS I this uit of the course we ivestigate fittig a straight lie to measured (x, y) data pairs. The equatio we wat to fit

More information

condition w i B i S maximum u i

condition w i B i S maximum u i ecture 10 Dyamic Programmig 10.1 Kapsack Problem November 1, 2004 ecturer: Kamal Jai Notes: Tobias Holgers We are give a set of items U = {a 1, a 2,..., a }. Each item has a weight w i Z + ad a utility

More information

Name Date Hr. ALGEBRA 1-2 SPRING FINAL MULTIPLE CHOICE REVIEW #1

Name Date Hr. ALGEBRA 1-2 SPRING FINAL MULTIPLE CHOICE REVIEW #1 Name Date Hr. ALGEBRA - SPRING FINAL MULTIPLE CHOICE REVIEW #. The high temperatures for Phoeix i October of 009 are listed below. Which measure of ceter will provide the most accurate estimatio of the

More information

Counting Regions in the Plane and More 1

Counting Regions in the Plane and More 1 Coutig Regios i the Plae ad More 1 by Zvezdelia Stakova Berkeley Math Circle Itermediate I Group September 016 1. Overarchig Problem Problem 1 Regios i a Circle. The vertices of a polygos are arraged o

More information

Parabolic Path to a Best Best-Fit Line:

Parabolic Path to a Best Best-Fit Line: Studet Activity : Fidig the Least Squares Regressio Lie By Explorig the Relatioship betwee Slope ad Residuals Objective: How does oe determie a best best-fit lie for a set of data? Eyeballig it may be

More information

CONTINUI TY. JEE-Mathematics. Illustration 1 : Solution : Illustration 2 : 1. CONTINUOUS FUNCTIONS :

CONTINUI TY. JEE-Mathematics. Illustration 1 : Solution : Illustration 2 : 1. CONTINUOUS FUNCTIONS : J-Mathematics. CONTINUOUS FUNCTIONS : CONTINUI TY A fuctio for which a small chage i the idepedet variable causes oly a small chage ad ot a sudde jump i the depedet variable are called cotiuous fuctios.

More information

Module 8-7: Pascal s Triangle and the Binomial Theorem

Module 8-7: Pascal s Triangle and the Binomial Theorem Module 8-7: Pascal s Triagle ad the Biomial Theorem Gregory V. Bard April 5, 017 A Note about Notatio Just to recall, all of the followig mea the same thig: ( 7 7C 4 C4 7 7C4 5 4 ad they are (all proouced

More information

Computational Geometry

Computational Geometry Computatioal Geometry Chapter 4 Liear programmig Duality Smallest eclosig disk O the Ageda Liear Programmig Slides courtesy of Craig Gotsma 4. 4. Liear Programmig - Example Defie: (amout amout cosumed

More information

SD vs. SD + One of the most important uses of sample statistics is to estimate the corresponding population parameters.

SD vs. SD + One of the most important uses of sample statistics is to estimate the corresponding population parameters. SD vs. SD + Oe of the most importat uses of sample statistics is to estimate the correspodig populatio parameters. The mea of a represetative sample is a good estimate of the mea of the populatio that

More information

Numerical Methods Lecture 6 - Curve Fitting Techniques

Numerical Methods Lecture 6 - Curve Fitting Techniques Numerical Methods Lecture 6 - Curve Fittig Techiques Topics motivatio iterpolatio liear regressio higher order polyomial form expoetial form Curve fittig - motivatio For root fidig, we used a give fuctio

More information

Section 7.2: Direction Fields and Euler s Methods

Section 7.2: Direction Fields and Euler s Methods Sectio 7.: Directio ields ad Euler s Methods Practice HW from Stewart Tetbook ot to had i p. 5 # -3 9-3 odd or a give differetial equatio we wat to look at was to fid its solutio. I this chapter we will

More information

The Graphs of Polynomial Functions

The Graphs of Polynomial Functions Sectio 4.3 The Graphs of Polyomial Fuctios Objective 1: Uderstadig the Defiitio of a Polyomial Fuctio Defiitio Polyomial Fuctio 1 2 The fuctio ax a 1x a 2x a1x a0 is a polyomial fuctio of degree where

More information

Pseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance

Pseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Pseudocode ( 1.1) High-level descriptio of a algorithm More structured

More information

n n B. How many subsets of C are there of cardinality n. We are selecting elements for such a

n n B. How many subsets of C are there of cardinality n. We are selecting elements for such a 4. [10] Usig a combiatorial argumet, prove that for 1: = 0 = Let A ad B be disjoit sets of cardiality each ad C = A B. How may subsets of C are there of cardiality. We are selectig elemets for such a subset

More information

Spherical Mirrors. Types of spherical mirrors. Lecture convex mirror: the. geometrical center is on the. opposite side of the mirror as

Spherical Mirrors. Types of spherical mirrors. Lecture convex mirror: the. geometrical center is on the. opposite side of the mirror as Lecture 14-1 Spherical Mirrors Types of spherical mirrors covex mirror: the geometrical ceter is o the opposite side of the mirror as the object. cocave mirror: the geometrical ceter is o the same side

More information

Ones Assignment Method for Solving Traveling Salesman Problem

Ones Assignment Method for Solving Traveling Salesman Problem Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:

More information

Project 2.5 Improved Euler Implementation

Project 2.5 Improved Euler Implementation Project 2.5 Improved Euler Implemetatio Figure 2.5.10 i the text lists TI-85 ad BASIC programs implemetig the improved Euler method to approximate the solutio of the iitial value problem dy dx = x+ y,

More information

FINITE DIFFERENCE TIME DOMAIN METHOD (FDTD)

FINITE DIFFERENCE TIME DOMAIN METHOD (FDTD) FINIT DIFFRNC TIM DOMAIN MTOD (FDTD) The FDTD method, proposed b Yee, 1966, is aother umerical method, used widel for the solutio of M problems. It is used to solve ope-regio scatterig, radiatio, diffusio,

More information

Polynomial Functions and Models. Learning Objectives. Polynomials. P (x) = a n x n + a n 1 x n a 1 x + a 0, a n 0

Polynomial Functions and Models. Learning Objectives. Polynomials. P (x) = a n x n + a n 1 x n a 1 x + a 0, a n 0 Polyomial Fuctios ad Models 1 Learig Objectives 1. Idetify polyomial fuctios ad their degree 2. Graph polyomial fuctios usig trasformatios 3. Idetify the real zeros of a polyomial fuctio ad their multiplicity

More information

ENGI 4421 Probability and Statistics Faculty of Engineering and Applied Science Problem Set 1 Descriptive Statistics

ENGI 4421 Probability and Statistics Faculty of Engineering and Applied Science Problem Set 1 Descriptive Statistics ENGI 44 Probability ad Statistics Faculty of Egieerig ad Applied Sciece Problem Set Descriptive Statistics. If, i the set of values {,, 3, 4, 5, 6, 7 } a error causes the value 5 to be replaced by 50,

More information

Assignment 5; Due Friday, February 10

Assignment 5; Due Friday, February 10 Assigmet 5; Due Friday, February 10 17.9b The set X is just two circles joied at a poit, ad the set X is a grid i the plae, without the iteriors of the small squares. The picture below shows that the iteriors

More information

. Written in factored form it is easy to see that the roots are 2, 2, i,

. Written in factored form it is easy to see that the roots are 2, 2, i, CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or

More information

CS Polygon Scan Conversion. Slide 1

CS Polygon Scan Conversion. Slide 1 CS 112 - Polygo Sca Coversio Slide 1 Polygo Classificatio Covex All iterior agles are less tha 180 degrees Cocave Iterior agles ca be greater tha 180 degrees Degeerate polygos If all vertices are colliear

More information

Ch 9.3 Geometric Sequences and Series Lessons

Ch 9.3 Geometric Sequences and Series Lessons Ch 9.3 Geometric Sequeces ad Series Lessos SKILLS OBJECTIVES Recogize a geometric sequece. Fid the geeral, th term of a geometric sequece. Evaluate a fiite geometric series. Evaluate a ifiite geometric

More information

( n+1 2 ) , position=(7+1)/2 =4,(median is observation #4) Median=10lb

( n+1 2 ) , position=(7+1)/2 =4,(median is observation #4) Median=10lb Chapter 3 Descriptive Measures Measures of Ceter (Cetral Tedecy) These measures will tell us where is the ceter of our data or where most typical value of a data set lies Mode the value that occurs most

More information

Counting II 3, 7 3, 2 3, 9 7, 2 7, 9 2, 9

Counting II 3, 7 3, 2 3, 9 7, 2 7, 9 2, 9 Coutig II Sometimes we will wat to choose objects from a set of objects, ad we wo t be iterested i orderig them For example, if you are leavig for vacatio ad you wat to pac your suitcase with three of

More information

On Infinite Groups that are Isomorphic to its Proper Infinite Subgroup. Jaymar Talledo Balihon. Abstract

On Infinite Groups that are Isomorphic to its Proper Infinite Subgroup. Jaymar Talledo Balihon. Abstract O Ifiite Groups that are Isomorphic to its Proper Ifiite Subgroup Jaymar Talledo Baliho Abstract Two groups are isomorphic if there exists a isomorphism betwee them Lagrage Theorem states that the order

More information

FURTHER INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

FURTHER INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS) Mathematics Revisio Guides More Trigoometric ad Log Itegrals Page of 7 MK HOME TUITION Mathematics Revisio Guides Level: AS / A Level AQA : C Edexcel: C OCR: C OCR MEI: C FURTHER INTEGRATION TECHNIQUES

More information

The Platonic solids The five regular polyhedra

The Platonic solids The five regular polyhedra The Platoic solids The five regular polyhedra Ole Witt-Hase jauary 7 www.olewitthase.dk Cotets. Polygos.... Topologically cosideratios.... Euler s polyhedro theorem.... Regular ets o a sphere.... The dihedral

More information

Lecture 1: Introduction and Strassen s Algorithm

Lecture 1: Introduction and Strassen s Algorithm 5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access

More information

9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence

9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence _9.qxd // : AM Page Chapter 9 Sequeces, Series, ad Probability 9. Sequeces ad Series What you should lear Use sequece otatio to write the terms of sequeces. Use factorial otatio. Use summatio otatio to

More information

Integration: Reduction Formulas Any positive integer power of sin x can be integrated by using a reduction formula.

Integration: Reduction Formulas Any positive integer power of sin x can be integrated by using a reduction formula. Itegratio: Reductio Formulas Ay positive iteger power of si x ca be itegrated by usig a reductio formula. Prove that for ay iteger 2, si xdx = 1 si 1 x cos x + 1 si Solutio. Weuseitegratiobyparts. Let

More information

Visualization of Gauss-Bonnet Theorem

Visualization of Gauss-Bonnet Theorem Visualizatio of Gauss-Boet Theorem Yoichi Maeda maeda@keyaki.cc.u-tokai.ac.jp Departmet of Mathematics Tokai Uiversity Japa Abstract: The sum of exteral agles of a polygo is always costat, π. There are

More information

A study on Interior Domination in Graphs

A study on Interior Domination in Graphs IOSR Joural of Mathematics (IOSR-JM) e-issn: 2278-5728, p-issn: 219-765X. Volume 12, Issue 2 Ver. VI (Mar. - Apr. 2016), PP 55-59 www.iosrjourals.org A study o Iterior Domiatio i Graphs A. Ato Kisley 1,

More information

Major CSL Write your name and entry no on every sheet of the answer script. Time 2 Hrs Max Marks 70

Major CSL Write your name and entry no on every sheet of the answer script. Time 2 Hrs Max Marks 70 NOTE:. Attempt all seve questios. Major CSL 02 2. Write your ame ad etry o o every sheet of the aswer script. Time 2 Hrs Max Marks 70 Q No Q Q 2 Q 3 Q 4 Q 5 Q 6 Q 7 Total MM 6 2 4 0 8 4 6 70 Q. Write a

More information

The Nature of Light. Chapter 22. Geometric Optics Using a Ray Approximation. Ray Approximation

The Nature of Light. Chapter 22. Geometric Optics Using a Ray Approximation. Ray Approximation The Nature of Light Chapter Reflectio ad Refractio of Light Sectios: 5, 8 Problems: 6, 7, 4, 30, 34, 38 Particles of light are called photos Each photo has a particular eergy E = h ƒ h is Plack s costat

More information

Solution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Spring, Instructions:

Solution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Spring, Instructions: CS 604 Data Structures Midterm Sprig, 00 VIRG INIA POLYTECHNIC INSTITUTE AND STATE U T PROSI M UNI VERSI TY Istructios: Prit your ame i the space provided below. This examiatio is closed book ad closed

More information

5.3 Recursive definitions and structural induction

5.3 Recursive definitions and structural induction /8/05 5.3 Recursive defiitios ad structural iductio CSE03 Discrete Computatioal Structures Lecture 6 A recursively defied picture Recursive defiitios e sequece of powers of is give by a = for =0,,, Ca

More information

Recursive Procedures. How can you model the relationship between consecutive terms of a sequence?

Recursive Procedures. How can you model the relationship between consecutive terms of a sequence? 6. Recursive Procedures I Sectio 6.1, you used fuctio otatio to write a explicit formula to determie the value of ay term i a Sometimes it is easier to calculate oe term i a sequece usig the previous terms.

More information

Apparent Depth. B' l'

Apparent Depth. B' l' REFRACTION by PLANE SURFACES Apparet Depth Suppose we have a object B i a medium of idex which is viewed from a medium of idex '. If '

More information

The number n of subintervals times the length h of subintervals gives length of interval (b-a).

The number n of subintervals times the length h of subintervals gives length of interval (b-a). Simulator with MadMath Kit: Riema Sums (Teacher s pages) I your kit: 1. GeoGebra file: Ready-to-use projector sized simulator: RiemaSumMM.ggb 2. RiemaSumMM.pdf (this file) ad RiemaSumMMEd.pdf (educator's

More information

MATHEMATICAL METHODS OF ANALYSIS AND EXPERIMENTAL DATA PROCESSING (Or Methods of Curve Fitting)

MATHEMATICAL METHODS OF ANALYSIS AND EXPERIMENTAL DATA PROCESSING (Or Methods of Curve Fitting) MATHEMATICAL METHODS OF ANALYSIS AND EXPERIMENTAL DATA PROCESSING (Or Methods of Curve Fittig) I this chapter, we will eamie some methods of aalysis ad data processig; data obtaied as a result of a give

More information

Area As A Limit & Sigma Notation

Area As A Limit & Sigma Notation Area As A Limit & Sigma Notatio SUGGESTED REFERENCE MATERIAL: As you work through the problems listed below, you should referece Chapter 5.4 of the recommeded textbook (or the equivalet chapter i your

More information

Test 4 Review. dy du 9 5. sin5 zdz. dt. 5 Ê. x 2 È 1, 3. 2cos( x) dx is less than using Simpson's. ,1 t 5 t 2. ft () t2 4.

Test 4 Review. dy du 9 5. sin5 zdz. dt. 5 Ê. x 2 È 1, 3. 2cos( x) dx is less than using Simpson's. ,1 t 5 t 2. ft () t2 4. Name: Class: Date: ID: A Test Review Short Aswer. Fid the geeral solutio of the differetial equatio below ad check the result by differetiatio. dy du 9 u. Use the error formula to estimate the error i

More information

Learning to Shoot a Goal Lecture 8: Learning Models and Skills

Learning to Shoot a Goal Lecture 8: Learning Models and Skills Learig to Shoot a Goal Lecture 8: Learig Models ad Skills How do we acquire skill at shootig goals? CS 344R/393R: Robotics Bejami Kuipers Learig to Shoot a Goal The robot eeds to shoot the ball i the goal.

More information

OCR Statistics 1. Working with data. Section 3: Measures of spread

OCR Statistics 1. Working with data. Section 3: Measures of spread Notes ad Eamples OCR Statistics 1 Workig with data Sectio 3: Measures of spread Just as there are several differet measures of cetral tedec (averages), there are a variet of statistical measures of spread.

More information

A Resource for Free-standing Mathematics Qualifications

A Resource for Free-standing Mathematics Qualifications Ope.ls The first sheet is show elow. It is set up to show graphs with equatios of the form = m + c At preset the values of m ad c are oth zero. You ca chage these values usig the scroll ars. Leave the

More information

ENGR Spring Exam 1

ENGR Spring Exam 1 ENGR 300 Sprig 03 Exam INSTRUCTIONS: Duratio: 60 miutes Keep your eyes o your ow work! Keep your work covered at all times!. Each studet is resposible for followig directios. Read carefully.. MATLAB ad

More information

3. b. Present a combinatorial argument that for all positive integers n : : 2 n

3. b. Present a combinatorial argument that for all positive integers n : : 2 n . b. Preset a combiatorial argumet that for all positive itegers : : Cosider two distict sets A ad B each of size. Sice they are distict, the cardiality of A B is. The umber of ways of choosig a pair of

More information

CS473-Algorithms I. Lecture 2. Asymptotic Notation. CS 473 Lecture 2 1

CS473-Algorithms I. Lecture 2. Asymptotic Notation. CS 473 Lecture 2 1 CS473-Algorithms I Lecture Asymptotic Notatio CS 473 Lecture 1 O-otatio (upper bouds) f() = O(g()) if positive costats c, 0 such that e.g., = O( 3 ) 0 f() cg(), 0 c 3 c c = 1 & 0 = or c = & 0 = 1 Asymptotic

More information

Aberrations in Lens & Mirrors (Hecht 6.3)

Aberrations in Lens & Mirrors (Hecht 6.3) Aberratios i Les & Mirrors (Hecht 6.3) Aberratios are failures to focus to a "poit" Both mirrors ad les suffer from these Some are failures of paraxial assumptio 3 5 θ θ si( θ ) = θ + L 3! 5! Paraxial

More information

CHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs

CHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs CHAPTER IV: GRAPH THEORY Sectio : Itroductio to Graphs Sice this class is called Number-Theoretic ad Discrete Structures, it would be a crime to oly focus o umber theory regardless how woderful those topics

More information

Chapter 11. Friends, Overloaded Operators, and Arrays in Classes. Copyright 2014 Pearson Addison-Wesley. All rights reserved.

Chapter 11. Friends, Overloaded Operators, and Arrays in Classes. Copyright 2014 Pearson Addison-Wesley. All rights reserved. Chapter 11 Frieds, Overloaded Operators, ad Arrays i Classes Copyright 2014 Pearso Addiso-Wesley. All rights reserved. Overview 11.1 Fried Fuctios 11.2 Overloadig Operators 11.3 Arrays ad Classes 11.4

More information

A Comparative Study of Positive and Negative Factorials

A Comparative Study of Positive and Negative Factorials A Comparative Study of Positive ad Negative Factorials A. M. Ibrahim, A. E. Ezugwu, M. Isa Departmet of Mathematics, Ahmadu Bello Uiversity, Zaria Abstract. This paper preset a comparative study of the

More information

Performance Plus Software Parameter Definitions

Performance Plus Software Parameter Definitions Performace Plus+ Software Parameter Defiitios/ Performace Plus Software Parameter Defiitios Chapma Techical Note-TG-5 paramete.doc ev-0-03 Performace Plus+ Software Parameter Defiitios/2 Backgroud ad Defiitios

More information

Some non-existence results on Leech trees

Some non-existence results on Leech trees Some o-existece results o Leech trees László A.Székely Hua Wag Yog Zhag Uiversity of South Carolia This paper is dedicated to the memory of Domiique de Cae, who itroduced LAS to Leech trees.. Abstract

More information

Which movie we can suggest to Anne?

Which movie we can suggest to Anne? ECOLE CENTRALE SUPELEC MASTER DSBI DECISION MODELING TUTORIAL COLLABORATIVE FILTERING AS A MODEL OF GROUP DECISION-MAKING You kow that the low-tech way to get recommedatios for products, movies, or etertaiig

More information

WebAssign Lesson 6-1b Geometric Series (Homework)

WebAssign Lesson 6-1b Geometric Series (Homework) WebAssig Lesso 6-b Geometric Series (Homework) Curret Score : / 49 Due : Wedesday, July 30 204 :0 AM MDT Jaimos Skriletz Math 75, sectio 3, Summer 2 204 Istructor: Jaimos Skriletz. /2 poitsrogac alcet2

More information

Civil Engineering Computation

Civil Engineering Computation Civil Egieerig Computatio Fidig Roots of No-Liear Equatios March 14, 1945 World War II The R.A.F. first operatioal use of the Grad Slam bomb, Bielefeld, Germay. Cotets 2 Root basics Excel solver Newto-Raphso

More information

CSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS)

CSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS) CSC165H1, Witer 018 Learig Objectives By the ed of this worksheet, you will: Aalyse the ruig time of fuctios cotaiig ested loops. 1. Nested loop variatios. Each of the followig fuctios takes as iput a

More information

Random Graphs and Complex Networks T

Random Graphs and Complex Networks T Radom Graphs ad Complex Networks T-79.7003 Charalampos E. Tsourakakis Aalto Uiversity Lecture 3 7 September 013 Aoucemet Homework 1 is out, due i two weeks from ow. Exercises: Probabilistic iequalities

More information

Normal Distributions

Normal Distributions Normal Distributios Stacey Hacock Look at these three differet data sets Each histogram is overlaid with a curve : A B C A) Weights (g) of ewly bor lab rat pups B) Mea aual temperatures ( F ) i A Arbor,

More information

Redundancy Allocation for Series Parallel Systems with Multiple Constraints and Sensitivity Analysis

Redundancy Allocation for Series Parallel Systems with Multiple Constraints and Sensitivity Analysis IOSR Joural of Egieerig Redudacy Allocatio for Series Parallel Systems with Multiple Costraits ad Sesitivity Aalysis S. V. Suresh Babu, D.Maheswar 2, G. Ragaath 3 Y.Viaya Kumar d G.Sakaraiah e (Mechaical

More information

Logic Spring Final Review

Logic Spring Final Review Idirect Argumet: Cotrdictios d Cotrpositio. Prove the followig by cotrdictio d by cotrpositio. Give two seprte proofs. The egtive of y irrtiol umber is irrtiol. b. For ll iteger, if ² is odd the is odd.

More information

Bezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only

Bezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only Edited: Yeh-Liag Hsu (998--; recommeded: Yeh-Liag Hsu (--9; last updated: Yeh-Liag Hsu (9--7. Note: This is the course material for ME55 Geometric modelig ad computer graphics, Yua Ze Uiversity. art of

More information

Data Structures and Algorithms. Analysis of Algorithms

Data Structures and Algorithms. Analysis of Algorithms Data Structures ad Algorithms Aalysis of Algorithms Outlie Ruig time Pseudo-code Big-oh otatio Big-theta otatio Big-omega otatio Asymptotic algorithm aalysis Aalysis of Algorithms Iput Algorithm Output

More information

CMPT 125 Assignment 2 Solutions

CMPT 125 Assignment 2 Solutions CMPT 25 Assigmet 2 Solutios Questio (20 marks total) a) Let s cosider a iteger array of size 0. (0 marks, each part is 2 marks) it a[0]; I. How would you assig a poiter, called pa, to store the address

More information

INSCRIBED CIRCLE OF GENERAL SEMI-REGULAR POLYGON AND SOME OF ITS FEATURES

INSCRIBED CIRCLE OF GENERAL SEMI-REGULAR POLYGON AND SOME OF ITS FEATURES INTERNATIONAL JOURNAL OF GEOMETRY Vol. 2 (2013), No. 1, 5-22 INSCRIBED CIRCLE OF GENERAL SEMI-REGULAR POLYGON AND SOME OF ITS FEATURES NENAD U. STOJANOVIĆ Abstract. If above each side of a regular polygo

More information

Hash Tables. Presentation for use with the textbook Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015.

Hash Tables. Presentation for use with the textbook Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015. Presetatio for use with the textbook Algorithm Desig ad Applicatios, by M. T. Goodrich ad R. Tamassia, Wiley, 2015 Hash Tables xkcd. http://xkcd.com/221/. Radom Number. Used with permissio uder Creative

More information

New Results on Energy of Graphs of Small Order

New Results on Energy of Graphs of Small Order Global Joural of Pure ad Applied Mathematics. ISSN 0973-1768 Volume 13, Number 7 (2017), pp. 2837-2848 Research Idia Publicatios http://www.ripublicatio.com New Results o Eergy of Graphs of Small Order

More information

Orientation. Orientation 10/28/15

Orientation. Orientation 10/28/15 Orietatio Orietatio We will defie orietatio to mea a object s istataeous rotatioal cofiguratio Thik of it as the rotatioal equivalet of positio 1 Represetig Positios Cartesia coordiates (x,y,z) are a easy

More information

On (K t e)-saturated Graphs

On (K t e)-saturated Graphs Noame mauscript No. (will be iserted by the editor O (K t e-saturated Graphs Jessica Fuller Roald J. Gould the date of receipt ad acceptace should be iserted later Abstract Give a graph H, we say a graph

More information

CSC 220: Computer Organization Unit 11 Basic Computer Organization and Design

CSC 220: Computer Organization Unit 11 Basic Computer Organization and Design College of Computer ad Iformatio Scieces Departmet of Computer Sciece CSC 220: Computer Orgaizatio Uit 11 Basic Computer Orgaizatio ad Desig 1 For the rest of the semester, we ll focus o computer architecture:

More information

How do we evaluate algorithms?

How do we evaluate algorithms? F2 Readig referece: chapter 2 + slides Algorithm complexity Big O ad big Ω To calculate ruig time Aalysis of recursive Algorithms Next time: Litterature: slides mostly The first Algorithm desig methods:

More information

Name of the Student: Unit I (Logic and Proofs) 1) Truth Table: Conjunction Disjunction Conditional Biconditional

Name of the Student: Unit I (Logic and Proofs) 1) Truth Table: Conjunction Disjunction Conditional Biconditional SUBJECT NAME : Discrete Mathematics SUBJECT CODE : MA 2265 MATERIAL NAME : Formula Material MATERIAL CODE : JM08ADM009 (Sca the above QR code for the direct dowload of this material) Name of the Studet:

More information

Big-O Analysis. Asymptotics

Big-O Analysis. Asymptotics Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses

More information

Chapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.

Chapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved. Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3

More information

Our starting point is the following sketch of part of one of these polygons having n vertexes and side-length s-

Our starting point is the following sketch of part of one of these polygons having n vertexes and side-length s- PROPERTIES OF REGULAR POLYGONS The simplest D close figures which ca be costructe by the cocateatio of equal legth straight lies are the regular polygos icluig the equilateral triagle, the petago, a the

More information

Homework 1 Solutions MA 522 Fall 2017

Homework 1 Solutions MA 522 Fall 2017 Homework 1 Solutios MA 5 Fall 017 1. Cosider the searchig problem: Iput A sequece of umbers A = [a 1,..., a ] ad a value v. Output A idex i such that v = A[i] or the special value NIL if v does ot appear

More information

Mathematics and Art Activity - Basic Plane Tessellation with GeoGebra

Mathematics and Art Activity - Basic Plane Tessellation with GeoGebra 1 Mathematics ad Art Activity - Basic Plae Tessellatio with GeoGebra Worksheet: Explorig Regular Edge-Edge Tessellatios of the Cartesia Plae ad the Mathematics behid it. Goal: To eable Maths educators

More information

CONVERGENCE OF THE RATIO OF PERIMETER OF A REGULAR POLYGON TO THE LENGTH OF ITS LONGEST DIAGONAL AS THE NUMBER OF SIDES OF POLYGON INCREASES

CONVERGENCE OF THE RATIO OF PERIMETER OF A REGULAR POLYGON TO THE LENGTH OF ITS LONGEST DIAGONAL AS THE NUMBER OF SIDES OF POLYGON INCREASES CONVERGENCE OF THE RATIO OF PERIMETER OF A REGULAR POLYGON TO THE LENGTH OF ITS LONGEST DIAGONAL AS THE NUMBER OF SIDES OF POLYGON INCREASES Pawa Kumar Bishwakarma Idepedet Researcher Correspodig Author:

More information

Running Time. Analysis of Algorithms. Experimental Studies. Limitations of Experiments

Running Time. Analysis of Algorithms. Experimental Studies. Limitations of Experiments Ruig Time Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Most algorithms trasform iput objects ito output objects. The

More information

Protected points in ordered trees

Protected points in ordered trees Applied Mathematics Letters 008 56 50 www.elsevier.com/locate/aml Protected poits i ordered trees Gi-Sag Cheo a, Louis W. Shapiro b, a Departmet of Mathematics, Sugkyukwa Uiversity, Suwo 440-746, Republic

More information

Classes and Objects. Again: Distance between points within the first quadrant. José Valente de Oliveira 4-1

Classes and Objects. Again: Distance between points within the first quadrant. José Valente de Oliveira 4-1 Classes ad Objects jvo@ualg.pt José Valete de Oliveira 4-1 Agai: Distace betwee poits withi the first quadrat Sample iput Sample output 1 1 3 4 2 jvo@ualg.pt José Valete de Oliveira 4-2 1 The simplest

More information