Special Instructions / Useful Data

Similar documents
UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

JAM 2015: General Instructions during Examination

Chapter 5 Properties of a Random Sample

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

ENGI 4421 Joint Probability Distributions Page Joint Probability Distributions [Navidi sections 2.5 and 2.6; Devore sections

Qualifying Exam Statistical Theory Problem Solutions August 2005

X ε ) = 0, or equivalently, lim

Lecture 3. Sampling, sampling distributions, and parameter estimation

Summary of the lecture in Biostatistics

22 Nonparametric Methods.

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Parameter, Statistic and Random Samples

Law of Large Numbers

Chapter 4 Multiple Random Variables

Lecture Notes Types of economic variables

Chapter 4 Multiple Random Variables

Continuous Distributions

STK4011 and STK9011 Autumn 2016

ρ < 1 be five real numbers. The

Chapter 14 Logistic Regression Models

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA

Econometric Methods. Review of Estimation

Dr. Shalabh. Indian Institute of Technology Kanpur

Mathematics HL and Further mathematics HL Formula booklet

STATISTICAL INFERENCE

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model

Point Estimation: definition of estimators

Simulation Output Analysis

ENGI 3423 Simple Linear Regression Page 12-01

1 Solution to Problem 6.40

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

Chapter 8: Statistical Analysis of Simulated Data

Midterm Exam 1, section 2 (Solution) Thursday, February hour, 15 minutes

Midterm Exam 1, section 1 (Solution) Thursday, February hour, 15 minutes

THE ROYAL STATISTICAL SOCIETY HIGHER CERTIFICATE

STA 105-M BASIC STATISTICS (This is a multiple choice paper.)

Class 13,14 June 17, 19, 2015

Multivariate Transformation of Variables and Maximum Likelihood Estimation

X X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then

LINEAR REGRESSION ANALYSIS

THE ROYAL STATISTICAL SOCIETY 2010 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA MODULE 2 STATISTICAL INFERENCE

CHAPTER VI Statistical Analysis of Experimental Data

THE ROYAL STATISTICAL SOCIETY 2016 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE MODULE 5

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Module 7: Probability and Statistics

Likelihood Ratio, Wald, and Lagrange Multiplier (Score) Tests. Soccer Goals in European Premier Leagues

Lecture Notes to Rice Chapter 5

Simple Linear Regression

Random Variate Generation ENM 307 SIMULATION. Anadolu Üniversitesi, Endüstri Mühendisliği Bölümü. Yrd. Doç. Dr. Gürkan ÖZTÜRK.

THE ROYAL STATISTICAL SOCIETY 2009 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA MODULAR FORMAT MODULE 2 STATISTICAL INFERENCE

THE ROYAL STATISTICAL SOCIETY 2016 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA MODULE 2

STA302/1001-Fall 2008 Midterm Test October 21, 2008

Introduction to Probability

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b

Chapter 8. Inferences about More Than Two Population Central Values

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

MS exam problems Fall 2012

Chapter 11 The Analysis of Variance

ENGI 4421 Propagation of Error Page 8-01

Random Variables. ECE 313 Probability with Engineering Applications Lecture 8 Professor Ravi K. Iyer University of Illinois

Econometrics. 3) Statistical properties of the OLS estimator

Extreme Value Theory: An Introduction

Introduction to local (nonparametric) density estimation. methods

STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1

Maximum Likelihood Estimation

Chapter 13 Student Lecture Notes 13-1

INTERNATIONAL BACCALAUREATE ORGANIZATION GROUP 5 MATHEMATICS FORMULAE AND STATISTICAL TABLES

2.28 The Wall Street Journal is probably referring to the average number of cubes used per glass measured for some population that they have chosen.

Linear Regression with One Regressor

BASICS ON DISTRIBUTIONS

Problem Solutions for BST 695: Special Topics in Statistical Theory, Kui Zhang, Solutions from Previous Homework

Random Variables and Probability Distributions

STK3100 and STK4100 Autumn 2017

Module 7. Lecture 7: Statistical parameter estimation

9 U-STATISTICS. Eh =(m!) 1 Eh(X (1),..., X (m ) ) i.i.d

Functions of Random Variables

Lecture Note to Rice Chapter 8

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance

STK3100 and STK4100 Autumn 2018

= 2. Statistic - function that doesn't depend on any of the known parameters; examples:

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

Chapter 3 Sampling For Proportions and Percentages

Wu-Hausman Test: But if X and ε are independent, βˆ. ECON 324 Page 1

4. Standard Regression Model and Spatial Dependence Tests

Estimation of the Loss and Risk Functions of Parameter of Maxwell Distribution

Analysis of Variance with Weibull Data

M2S1 - EXERCISES 8: SOLUTIONS

Logistic regression (continued)

ECON 5360 Class Notes GMM

5.1 Properties of Random Numbers

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Sampling Theory MODULE X LECTURE - 35 TWO STAGE SAMPLING (SUB SAMPLING)

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Training Sample Model: Given n observations, [[( Yi, x i the sample model can be expressed as (1) where, zero and variance σ

Simple Linear Regression - Scalar Form

BIOREPS Problem Set #11 The Evolution of DNA Strands

A New Family of Transformations for Lifetime Data

Section 2 Notes. Elizabeth Stone and Charles Wang. January 15, Expectation and Conditional Expectation of a Random Variable.

Handout #8. X\Y f(x) 0 1/16 1/ / /16 3/ / /16 3/16 0 3/ /16 1/16 1/8 g(y) 1/16 1/4 3/8 1/4 1/16 1

Transcription:

JAM 6 Set of all real umbers P A..d. B, p Posso Specal Istructos / Useful Data x,, :,,, x x Probablty of a evet A Idepedetly ad detcally dstrbuted Bomal dstrbuto wth parameters ad p Posso dstrbuto wth mea N, Normal dstrbuto wth mea ad varace Exp The expoetal dstrbuto wth probablty desty fucto x e, x, f x,, otherwse t Studet s t dstrbuto wth degrees of freedom Ch-square dstrbuto wth degrees of freedom, A costat such that PW,, x Cumulatve dstrbuto fucto of N, x Probablty desty fucto of N, where W has dstrbuto C A E Var Complemet of a evet A Expectato of a radom varable Varace of a radom varable m Bm, x f x x dx, m, The greatest teger less tha or equal to real umber x Dervatve of fucto f.5.5987,.5.695,.65.7,.7.76,.8,.5.8697,.977 MS /8

JAM 6 SECTION A MULTIPLE CHOICE QUESTIONS (MCQ) Q. Q. carry oe mark each. Q. Let P. 7 The rak of P equals Q. Let,, be real umbers such that ad. Suppose P ad P P. The ad ad ad ad, Q. Let m. The volume of the sold geerated by revolvg the rego betwee the y-axs ad the curve xy, y m, about the y-axs s 5. The value of m s 5 6 7 Q. Cosder the rego S eclosed by the surface ad y. The volume of S s z y ad the plaes z, x, x, y MS /8

JAM 6 Q.5 Let be a dscrete radom varable wth the momet geeratg fucto The P equals.5 M t e, t. e t e e e e e Q.6 Let E ad F be two depedet evets wth P E F P F E, P E The PE equals F ad PF PE. 9 Q.7 Let be a cotuous radom varable wth the probablty desty fucto The E ( ) f( x), x. / ( x ) equals equals equals does ot exst Q.8 The probablty desty fucto of a radom varable s gve by x, x f( x),., otherwse The the dstrbuto of the radom varable Y log e s Q.9 Let,, be a sequece of..d. N (,) radom varables. The, as, coverges probablty to.5 MS /8

JAM 6 Q. Cosder the smple lear regresso model wth radom observatos Y x,,,,. ad are ukow parameters, x,, x are observed values of the regressor varable ad, are error radom varables wth E,,,, ad for,, f j,, j,,, Cov, j., f j ubased estmator of, the For real costats a,, a, f ay s a a ad a x a ad a x a ad a x a ad a x Q. Q. carry two marks each. Q. Let (, Y ) have the jot probablty desty fucto x ye, f y x, f( x, y), otherwse. The PY ( ) equals 8 7 9 Q. Let,, be a sequece of..d. radom varables havg the probablty desty fucto 5 x x, x, f( x) B(6,), otherwse. Let Y ad U Y., the a possble value of s If the dstrbuto of U coverges to N, as 7 5 MS 5/8

JAM 6 Q. Let,, be a radom sample from a populato wth the probablty desty fucto f e, x, x, otherwse x,. If T m,,, the T s ubased ad cosstet estmator of T s based ad cosstet estmator of T s ubased but NOT cosstet estmator of T s NEITHER ubased NOR cosstet estmator of Q. Let,, be..d. radom varables wth the probablty desty fucto If ( ) f x x e, x,, otherwse. max,,, the lm P ( ) loge equals e e e Q.5 Let ad Y be two depedet, e e.5 e e N radom varables. The P Y equals e e e e Q.6 Let be a radom varable wth the cumulatve dstrbuto fucto The E equals, x, x, x, 8 x, x, 6, x. F x MS 6/8

JAM 6 Q.7 Let,, be a radom sample from a populato wth the probablty desty fucto x f x e, x,. For a sutable costat K, the crtcal rego of the most powerful test for testg H : agast H : s of the form K K K K Q.8 Let,,,,,,, m m be a radom sample from N, ; m,. If ad, the the dstrbuto of the radom m varable s T m m m t m t m m t m m t m Q.9 Let,, be a radom sample from a Posso populato,, ad T. The the uformly mmum varace ubased estmator of s T T T T T T T MS 7/8

JAM 6 Q. Let be a radom varable whose probablty mass fuctos H ) ad hypothess f x H (uder the ull f x H (uder the alteratve hypothess H ) are gve by x f x H.... f x H.... For testg the ull hypothess : ~ H f x H agast the alteratve hypothess H: ~ f x H, cosder the test gve by: Reject H f If sze of the test ad power of the test, the. ad.. ad.7.7 ad..7 ad.7. Q. Let,, be a radom sample from a, estmator for s N populato,. A cosstet 5 5 5 Q. A sttute purchases laptops from ether vedor V or vedor V wth equal probablty. The lfetmes ( years) of laptops from vedor V have a U, dstrbuto, ad the lfetmes ( years) of laptops from vedor V have a Exp dstrbuto. If a radomly selected laptop the sttute has lfetme more tha two years, the the probablty that t was suppled by vedor V s e e e e MS 8/8

JAM 6 Q. Let y ( x ) be the soluto to the dfferetal equato The y s dy s ;,. dx x x y x y x 6 Q. Let s a e b e s for. The ad a coverges but b b coverges but a both NEITHER a ad b coverge a NOR b does NOT coverge does NOT coverge coverges Q.5 Let f x x x x, x, s,, ad g x x s x s x, x,, x. The f s dfferetable at but g s NOT dfferetable at g s dfferetable at but f s NOT dfferetable at f ad g are both dfferetable at NEITHER f NOR g s dfferetable at MS 9/8

JAM 6 Q.6 Let f :, be a twce dfferetable fucto. Further, let f f f. The there does NOT exst ay x, such that fx there exst x, ad x, such that f x f x f x for all x, f x for all x,, ad Q.7 Let f xy, x xy for all local mmum at local mmum at local mmum both at local mmum NEITHER at xy,. The f attas ts, but NOT at,, but NOT at,, ad,, NOR at, Q.8 Let y x be the soluto to the dfferetal equato The y equals d y d y 9 y, y(), y(). dx dx e 5 e e 7 e Q.9 Let g :, be defed by The area betwee the curve x g x x t e dt. t ad the x-axs over the terval y g x e e e 8e, s MS /8

JAM 6 Q. Let P be a sgular matrx such that Pv v for a ozero vector v ad The 7 5 P 7 P P P 7 P P P 7 P P P P P 5 P. 5 MS /8

JAM 6 Q. Q. carry two marks each. SECTION - B MULTIPLE SELECT QUESTIONS (MSQ) Q. For two ozero real umbers a ad b, cosder the system of lear equatos a b x b. b a y a Whch of the followg statemets s (are) TRUE? If a b, the solutos of the system le o the le x y If a b, the solutos of the system le o the le y x If a b, the system has o soluto If a b, the system has a uque soluto Q. For, let a, f sodd,, f seve. Whch of the followg statemets s (are) TRUE? The sequece a coverges The sequece a coverges The seres The seres a coverges a coverges Q. Let f :, be defed by f x x e. x x Whch of the followg statemets s (are) TRUE? lm f x x lm x f x x exsts lm x f x x exsts exsts There exsts m such that lm x m f x x does NOT exst. MS /8

JAM 6 Q. For x, defe f x cos x x statemets s (are) TRUE? f x s cotuous at x g x s cotuous at x f x gx s cotuous at x f x g x s cotuous at x ad g x x s. Whch of the followg Q.5 Let E ad F be two evets wth PE, PF ad PE F PE of the followg statemets s (are) TRUE? PF E PF C P E F PE C PF E PF E ad F are depedet. Whch Q.6 Let,, be a radom sample from a U, m,,, Y max,,. Y maxmum lkelhood estmator (s) of? Y Y Y Y 6 Y Y 8 populato,, ad Whch of the followg statstcs s (are) Every statstc T satsfyg T,, Q.7 Let,,,, be a radom sample from a, Y Y N populato,. Whch of the x,, x : x, as the most followg testg problems has (have) the rego powerful crtcal rego of level? H H H H : agast H : : agast H : : agast H : : agast H :.5 MS /8

JAM 6 Q.8 Let,, N, populato,. Whch of the followg statemets s (are) TRUE? s suffcet ad complete s suffcet but NOT complete be a radom sample from a s suffcet ad complete s the uformly mmum varace ubased estmator for Q.9 Let,, be a radom sample from a populato wth the probablty desty fucto Whch of the followg s (are) f x e, x, x,., otherwse % cofdece terval(s) for?,,,,,,,,,,, Q. The cumulatve dstrbuto fucto of a radom varable s gve by, x, 7 Fx x, x,, x. Whch of the followg statemets s (are) TRUE? Fx s cotuous everywhere Fx creases oly by jumps P 6 5 P MS /8

JAM 6 SECTION C NUMERICAL ANSWER TYPE (NAT) Q. Q. 5 carry oe mark each. Q. be a radom sample from a,,, Let Y Y Y. If 7 N populato. Suppose Y 6 6 ad has a dstrbuto, the the value of s Q. Let be a cotuous radom varable wth the probablty desty fucto f x x, x, 9, otherwse. The the upper boud of P usg Chebyshev s equalty s Q. Let ad Y be cotuous radom varables wth the jot probablty desty fucto The P Y f x, y x y e, x, y,, otherwse. Q. Let ad Y be cotuous radom varables wth the jot probablty desty fucto x y f x, y e, x, y. The P, Y Q.5 Let Y be a B 7, radom varable. Usg ormal approxmato to bomal dstrbuto, P Y 8 s a approxmate value of MS 5/8

JAM 6 Q.6 Let be a B, p radom varable ad Y be a, 5 9 P, the PY B p radom varable, p. If Q.7 Cosder the lear trasformato The rak of T s T x, y, z x y z, x z, x y z. Q.8 lm cos s The value of e s Q.9 Let f :, be defed by fucto f o x f x x e x 5 6. The mmum value of the, s Q.5 Cosder a dfferetable fucto f o, wth the dervatve f x x. legth of the curve y f x, x, s The arc Q. 5 Q. 6 carry two marks each. Q.5 Let m be a real umber such that m. If m the m x e y dy dx dz e, Q.5 Let P 5 6. The product of the ege values of P s MS 6/8

JAM 6 Q.5 The value of the real umber m the followg equato s x x y dy dx d d r r x m Q.5 Let a ad a for. The a a coverges to Q.55 Let,, be a sequece of..d. radom varables wth the probablty desty fucto f x x xe, x,, otherwse ad let S. The lm P S s Q.56 Let ad Y be cotuous radom varables wth the jot probablty desty fucto cx, x, y, f x, y y,, otherwse where c s a sutable costat. The E Q.57 Two pots are chose at radom o a le segmet of legth 9 cm. The probablty that the dstace betwee these two pots s less tha cm s MS 7/8

JAM 6 Q.58 Let be a cotuous radom varable wth the probablty desty fucto f x x, x,, otherwse. The P Q.59 If s a U, radom varable, the P m, Q.6 I a coloy all famles have at least oe chld. The probablty that a radomly chose famly from k ths coloy has exactly k chldre s.5 ; k,,. A chld s ether a male or a female wth equal probablty. The probablty that such a famly cossts of at least oe male chld ad at least oe female chld s END OF THE QUESTION PAPER MS 8/8