REFERENCES AND FURTHER STUDIES

Similar documents
Deccan Education Society s FERGUSSON COLLEGE, PUNE (AUTONOMOUS) SYLLABUS UNDER AUTONOMY. FIRST YEAR B.Sc.(Computer Science) SEMESTER I

APPENDICES APPENDIX A. STATISTICAL TABLES AND CHARTS 651 APPENDIX B. BIBLIOGRAPHY 677 APPENDIX C. ANSWERS TO SELECTED EXERCISES 679

Subject CS1 Actuarial Statistics 1 Core Principles

Chapter Learning Objectives. Probability Distributions and Probability Density Functions. Continuous Random Variables

Probability and Stochastic Processes

Institute of Actuaries of India

Deccan Education Society s FERGUSSON COLLEGE, PUNE (AUTONOMOUS) SYLLABUS UNDER AUTOMONY. SECOND YEAR B.Sc. SEMESTER - III

8/29/2015 Connect Math Plus

Stat 5101 Lecture Notes

Practice Problems Section Problems

Formulas and Tables by Mario F. Triola

Two hours. To be supplied by the Examinations Office: Mathematical Formula Tables THE UNIVERSITY OF MANCHESTER. 21 June :45 11:45

Review. DS GA 1002 Statistical and Mathematical Models. Carlos Fernandez-Granda

AN INTRODUCTION TO PROBABILITY AND STATISTICS

HANDBOOK OF APPLICABLE MATHEMATICS

Statistical Methods in HYDROLOGY CHARLES T. HAAN. The Iowa State University Press / Ames

ACCURATE APPROXIMATION TO THE EXTREME ORDER STATISTICS OF GAUSSIAN SAMPLES

STAT 302 Introduction to Probability Learning Outcomes. Textbook: A First Course in Probability by Sheldon Ross, 8 th ed.

Week 1 Quantitative Analysis of Financial Markets Distributions A

TABLE OF CONTENTS CHAPTER 1 COMBINATORIAL PROBABILITY 1

Distribution Theory. Comparison Between Two Quantiles: The Normal and Exponential Cases

Introduction to Statistical Hypothesis Testing

STATISTICS; An Introductory Analysis. 2nd hidition TARO YAMANE NEW YORK UNIVERSITY A HARPER INTERNATIONAL EDITION

Learning Objectives for Stat 225

Fundamentals of Applied Probability and Random Processes

Introduction and Overview STAT 421, SP Course Instructor

Probability Distributions Columns (a) through (d)

Notation Precedence Diagram

Continuous Probability Distributions. Uniform Distribution

Plotting data is one method for selecting a probability distribution. The following

Paper-V: Probability Distributions-I Unit-1:Discrete Distributions: Poisson, Geometric and Negative Binomial Distribution (10)

Formulas and Tables. for Elementary Statistics, Tenth Edition, by Mario F. Triola Copyright 2006 Pearson Education, Inc. ˆp E p ˆp E Proportion

COPYRIGHTED MATERIAL CONTENTS. Preface Preface to the First Edition

Department of Mathematics

Continuous Probability Distributions. Uniform Distribution

Question Points Score Total: 76

Alternative Presentation of the Standard Normal Distribution

Asymptotic Statistics-III. Changliang Zou

Transformations and Expectations

Non-parametric Inference and Resampling

Spring 2012 Math 541B Exam 1

Exact Inference for the Two-Parameter Exponential Distribution Under Type-II Hybrid Censoring

Preface Introduction to Statistics and Data Analysis Overview: Statistical Inference, Samples, Populations, and Experimental Design The Role of

Problem 1 (20) Log-normal. f(x) Cauchy

Appendix F. Computational Statistics Toolbox. The Computational Statistics Toolbox can be downloaded from:

Statistical Methods in Particle Physics

Foundations of Probability and Statistics

FRANKLIN UNIVERSITY PROFICIENCY EXAM (FUPE) STUDY GUIDE

How do we compare the relative performance among competing models?

Department of Mathematics

Statistical Inference: Estimation and Confidence Intervals Hypothesis Testing

PART I INTRODUCTION The meaning of probability Basic definitions for frequentist statistics and Bayesian inference Bayesian inference Combinatorics

f (1 0.5)/n Z =

The University of Hong Kong Department of Statistics and Actuarial Science STAT2802 Statistical Models Tutorial Solutions Solutions to Problems 71-80

ECE 510 Lecture 6 Confidence Limits. Scott Johnson Glenn Shirley

* Tuesday 17 January :30-16:30 (2 hours) Recored on ESSE3 General introduction to the course.

375 PU M Sc Statistics

Reliability Engineering I

Contents. Preface to Second Edition Preface to First Edition Abbreviations PART I PRINCIPLES OF STATISTICAL THINKING AND ANALYSIS 1

Math Review Sheet, Fall 2008

Inference for P(Y<X) in Exponentiated Gumbel Distribution

Journal of Biostatistics and Epidemiology

Monte Carlo Simulations

PROBABILITY AND STOCHASTIC PROCESSES A Friendly Introduction for Electrical and Computer Engineers

STATISTICS ANCILLARY SYLLABUS. (W.E.F. the session ) Semester Paper Code Marks Credits Topic

STATISTICS SYLLABUS UNIT I

Monotonicity and Aging Properties of Random Sums

Random Variate Generation

Qualifying Exam CS 661: System Simulation Summer 2013 Prof. Marvin K. Nakayama

The comparative studies on reliability for Rayleigh models

MATH4427 Notebook 4 Fall Semester 2017/2018

5 Introduction to the Theory of Order Statistics and Rank Statistics

A comparison of inverse transform and composition methods of data simulation from the Lindley distribution

Asymptotic distribution of the sample average value-at-risk

Continuous RVs. 1. Suppose a random variable X has the following probability density function: π, zero otherwise. f ( x ) = sin x, 0 < x < 2

A Simulation Comparison Study for Estimating the Process Capability Index C pm with Asymmetric Tolerances

System Simulation Part II: Mathematical and Statistical Models Chapter 5: Statistical Models

Review of Probabilities and Basic Statistics

Testing Equality of Two Intercepts for the Parallel Regression Model with Non-sample Prior Information

11. Bootstrap Methods

The Nonparametric Bootstrap

Sampling Random Variables

The Bayesian Choice. Christian P. Robert. From Decision-Theoretic Foundations to Computational Implementation. Second Edition.

UQ, Semester 1, 2017, Companion to STAT2201/CIVL2530 Exam Formulae and Tables

CAM Ph.D. Qualifying Exam in Numerical Analysis CONTENTS

Factors affecting the Type II error and Power of a test

Kumaun University Nainital

Northwestern University Department of Electrical Engineering and Computer Science

Math 562 Homework 1 August 29, 2006 Dr. Ron Sahoo

Math 494: Mathematical Statistics

Review for the previous lecture

Reading Material for Students

Repairable Systems Reliability Trend Tests and Evaluation

Exploring Monte Carlo Methods

STAT 461/561- Assignments, Year 2015

Random Variables. Definition: A random variable (r.v.) X on the probability space (Ω, F, P) is a mapping

Dover- Sherborn High School Mathematics Curriculum Probability and Statistics

Research Article The Laplace Likelihood Ratio Test for Heteroscedasticity

Analysis of variance and linear contrasts in experimental design with generalized secant hyperbolic distribution

PERCENTILE ESTIMATES RELATED TO EXPONENTIAL AND PARETO DISTRIBUTIONS

Transcription:

REFERENCES AND FURTHER STUDIES by..0. on /0/. For personal use only.. Afifi, A. A., and Azen, S. P. (), Statistical Analysis A Computer Oriented Approach, Academic Press, New York.. Alvarez, A. R., Welter, D. J., and Johnson, M. (), "Problem Solving in the IC Industry Through Applied Statistics: Comparing Two Processes," Solid State Technology, pp. -.. Box, G. E. P. and Muller, M. E. (), "A Note on Generating of Normal Deviates,",wi. Math. Stat, pp. 0-.. David, H. A. (), Order Statistics, John Wiley & Sons, New York.. Duran, J. W., and Wiorkowski, J. J. (0), "Quantify Software Validity by Sampling," IEEE Transactions on Reliability, pp. -.. Edgington, E. S. (0), Randomization Tests, Marcel Dekker, New York.. Efron, B. (), The Jackknife, the Bootstrap and Other Resampling Plans, SIAM Press, Philadelphia.. Feller, W. (), An Introduction to Probability Theory and Its Applications, Vol. I, John Wiley & Sons, New York.. Goodman, L. A. (), "Serial Number Analysis," Journal of American Statistical Association, pp. -.

Understanding and Learning Statistics by Computer 0. Gay, F. A. (), "Evaluation of Maintenance Software in Real-Time System," IEEE Transactions on Computers, pp. -.. Huber, P. J. (), Robust Statistical Procedures, SIAM Press, Philadelphia. by..0. on /0/. For personal use only.. Johnson, N. L. and Kotz, S. (), Discrete Distributions, John Wiley & Sons, New York.. Johnson, N. L.andKotz,S.(0),Continuous UnivariateDistributions-, John Wiley & Sons, New York.. Kennedy, W. J., and Gentle, J. E. (0), Statistical Computing, Marcel DEkker, New York.. McClave, J. T., and Dietrich, F. H. (\S),Statistics, Dellen, San Francisco.. Mendenhall, W., Scheaffer, R. L., and Wackerly, D. (),Mathematical Statistics with Applications, Duxbury Press, North Scituate, Mass.. Myers, G. J. (), Software Reliability, Principles and Practices, John Wiley & Sons, New York.. Rubinstein, R. Y. (), Simulation and the Monte Carlo Method, John Wiley & Sons, New York.. Scheaffer, R. L. and McClave. J. T.(), Statistics for Engineers, Duxbury Press, Boston. 0. Trivedi, K. S. (), Probability and Statistics with Reliability, Queuing, and Computer Science Applications, Prentice-Hall, New Jersey.. Vitter, J. S. (), "Optimal Algorithm for Random Sampling Problems," IEEE Fundamental of Computers, pp. -.

Appendices Tables Table A.l Thez-table. F(:»-L y/r e~»" dt by..0. on /0/. For personal use only. X.00.0 0.0.0.0.0.0.0 0.0....... 0.........0...... F(x) 000.00.00.0.0...............0...0 0.0......0..0. - Fix) 000.0.0.0.0.0.....0....0..0...00.0.0......0.... 0 X.0.... 0..... 0......... 0....... F(x)..0.0.0.0...0............0....0.......0....0.0. 0.0. - F{x) 0.00.0.. 0.. 0.........0....0...00 0.0.00..0 X.00.0.0.0.0.0.0.0 0.0.0.......0..........0...... Fix)..... 0........0...0.0.0 /0....0....0..0 0 0.0.0. 0... - Fix)..... 0....... 0 0.0 0.... 0. 0. 0. 0. 00. 00. 0 0 0 0 0 00. 0. 0. 0. 0. 0.0....00.0. 00.0...............0......0.... 00 0.0. 0.0.....0..........0.....0.........0.. 0.0. 00.0.0 0 0.00...0..0

Understanding and Learning Statistics by Computer Table A.l (continued) Fix) - F(x) X F(x) - F(x) * Fix) - Fix).0...... 0. 0.0.0.00.0.00.0.0.0.0......0.0.0.0.00.0....0...00.000.00.00.00 by..0. on /0/. For personal use only......0........0.........0.........0........0......... 0.......... Q............0...... 0... 00.0.0.0 0.0 0.0.0.00.0.0.0.0.0.0 0.0 0.00 00.0. 0.0.0.0 0.0.0 0 0.0.00.00.0.0.0 0.0 0.0.00.0. 0.0.0.0.0.0.0.0.........0........0...... 0........0.0.....0.....0...........0...0.0.0.0.....0......00.0.0.0.0.0.0.00.0.0.0.0.00.0.0.0.0.0.0 0 0.0 0.0.00 00.00 00.00.00.00 00 00 00.00.00.000 00.00 00 00 00 00 00 00.....0........0..........0.......0.'................0.........*.0.............0.... 0..0......00.00.00.00.00.00.00.00.00.00.000.00.00.00.00 00.00.00.00.00.000.00.00.00 00.00.00 00.00 00.00.00.00.000.00.00.00.00.00 00.00.00 00 00.00.00.0 0S 0 00.00..00

Appendices - Tables Table A.l (continued) X Fix) - F(x) X Fix) - Fix).00 0.0.0.0......00.00.00.00.00.0...... 000 000 000 by..0. on /0/. For personal use only. 0.0.0.0 00.0....0 0.0........0..... 0.........0.0.0......................................00.00.00.000.000.000.000 000.000.000.000.000.000 000.000.000.000.000.000.000.000 000 000.000.000 000 000.000.000.000 000.000.000.000.000.000 000 000.000 000.....0.......0....0........ 0.......... 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 0. 00 Reprinted with permission from CRC Handbook of Tables for Probabi lity and Statistics. Copyright by CF,C Press In c, Boca R aton, Fl orida.

Understanding and Learning Statistics by Computer Table A. Student's t-distribution PERCENTAGE POINTS, STUDENTS ^-DISTRIBUTION "' I'M^y* by..0. on /0/. For personal use only. r 0 0 0 0 0 0 00.0 ^........0.0.......................000......0.0.00.... 0...................0.0.....0.......0.....0.......0.0......0..0.. 0......0........0.0.0.0........0.0......0...0.0.0.0.0.0.0.00.0 0.0 00.0.0.0 0.0.0.000.0.0.............0.0......0.00........0......0.0.0.0..0.0.0.........0.......0 0.0.......0...0 0......0.0.0....0......0.0.....0.. Reprinted with permission from CRC Handbook of Tables for Probability and Statistics. Copyright by CRC Press Inc., Boca Raton, Florida.

by..0. on /0/. For personal use only. 0 0 0.00.000.0.0.......0.0..0.0..0....0... 0.......00.00.......0..0.......0...0. 0. 0.......0.0.000.00.......0...0.0....... 0..0......0. Table A. PERCENTAGE POINTS, CHI-SQUARE DISTRIBUTION.00.00.0................ 0. 0........... Fix*).00.0...0..0......0.0... 0. 0.....0....... 0. - ['-A-,*-? ^ * h *r(?).0.0.......0.0... 0 0.0.........0. 0..... Rep rinted with permission from Q KCHand book of Tables for Probability and Statistics. Copyright by CRC Press Inc. Boca Rate n, Florida.00.......... 0........... 0.......... e * dx.0.......0 0......0... 0......0... 0......00..... 0..0...0........0... 0..0..... 0..0............0...0... 0........ 0......0......0..0 0....... 0....... 0.....0.0....... 0....... 0..0..... 0...0.0.. 0... 0..... 0..0.......... 0.0........0. ^ -Q g- O- 00

by..0. on /0/. For personal use only. ^ 0 0 0 0 0 0 0 F-....0......0.0.0.0 0.........0....? - Sl 0.00,.. 0.....0..........0.0.... 0.... 0.........0.......0... 0....................... 0 0.. ' r F(F) " (.. 0...........0.....0.0.0.0.0.0.0 00..0..0...0.0.0............0.0 0.0.0.0 0 00 00... Table A. PERCENTAGE POINTS, tn + n n m ^ - ^-m* r- TO n z _K H..0.......0 0 0 0.0 0............ 0..0...0 0.0 0.00.....0 in F-DISTRIBUTION. where t\ n/ «? - Si/ m and *\ - St/n ar e indepen dent mean squares e stimating a coramor i variance * and based on m and n degrees of freedom, respectively..............0 0.0 00........... 0 0... 0..0......0 0 0 00....0.......... 0 \n + 0...0.0..0...0.0 0...........0...0 mi).. 0........0.0.0.......0...... 0.. m+n dx -.0 0.........0.0..0.0..........0.......00......0...0.0.. 0......0....... j. 0.....0.....0 0..........0.......... I 0....0...... 0...............0......0 j 0..........0..0.. I.0.......... 0. 0.0.......0.00..........0........0.......0....0..0..0...........0.....00 O s I " * Q, t- S* < Co CO* O* C* o ««$

v by..0. on /0/. For personal use only. 0 0 0 0 0 0 0 * F = I 0.......0..0. 0...0.00 a* ml 00. 0.... 0. 0 00. where n.. 0. 0 0 0 0 0 0.. 0... 0 0 0.. 0... 0. F(F) 0.0 0. 0 0 0. 0.... 0 Table A. (continued) PERCENTAGE POINTS, F-DISTRIBUTION ff T(^^) * -, ± \ * / (fho.0... 0 00.. 0. 0.... 0..0....0 0..... 0. 0 0. 0 0 0. 0 0 0 0.. 00. 0 0 0 0. 0 0?x (n + mx) 0.0.. 0. 0. 0. 0..0.. S? - Si/ m and s\ = Si/n ar t indepenc ent mean squares e sttmating a common variance a and hased on m and n degrees of freedom, respectively... 00. 0. 0....0 IS 0 0 00...0 m +n dx =...0..0..0. 0 0 0 0 0 0 I 0 0.0. 0 0 0 0 0.0 0 0 0 0.0 0 0 0.. 0.. 0..0.. 0.0 0. 0.. 0.... 0.. 0 0 0 0.. 0 0....0.0..0.. 0 0.. 0.. 0.. 0 0... 0 0 0... 0.. 0. 0 0 0 0. L 00 ^ * v

by..0. on /0/. For personal use only. ^ s t i 0 IS IS SO a 0 0 0 0 0 0..0.... 0. 0.0...0... 0..0.0.......0...0...00 0.00 0...0..0. 0............ 0... 0........ 0.0.......0............0.....0.... 0.........0.0.0.... Table A. (continued) PERCENTAGE POINTS, F-DISTRIBUTION ( m + n \ m n m m+n F(F) > * An?n*z (n + mx)~ «)' - ( ' $ dx -..0.. 0.....0...0......0.0...0.....0....0... 0.....0..0...0.0.0..........0....»M... 0..... 0......0... 0....0.....0.......0 0..0.0.0..0.0..00.............0..... 0... 0..........0...0...0..0......0.0.... '-rj/r- k?-*/-!-*/.. D squares estiraataf a e B variance #» and baaed on w and a degrees of freedom, respectively. Reprinted with permission from CRC Handbook of Tables for Probability and Statistics. Copyright by CRC Press Inc., Boca Raton, Florida. 0 0.0.. 0.0.......0.0..0...........0.0.0.00..0... 0..0........0...0.....0....0.0....0....0.....0.......0.......0.0.........0....0 0 00...0..0.....0......0.00......0...0...0.0..0....0....0......0.00...0..0.......... SO..0....0....0....0.00........0...0.0..0 0.............0.............0.... 0....0.0..0..0.....0......0..0.......0... 0........0.00..0.....0... 0...... - 0.. 0S.... 0. 00..... 0 0 0 0.0 0..00 St I'

Appendices Tables Table A. The Binomial Tablep(x) = (*) d x (l-d) n ~ INDIVIDUAL TERMS, BINOMIAL DISTRIBUTION n x.0 0.0 e..0..0..0 0.00.000.000.000.00.00.000.000.00 00.000.000.00.00.000.000.00.00.000.000 by..0. on /0/. For personal use only. 0 0 0 0 0 0.0.00.00..00...0..0.0.00...00.00...00.00.00.00.000 0.0.00 000.0.00.0 0.0.00.000..0.0.00 000..0.0.00.00.0.0..0.00 0..0.0....0.00....0.00.000.0.0.0.0.00.00.00.00.000 0.0 00.000 0.0..0.00..0.0.0.00.000..0.0.00 0.0..0 00 000 0.0.. 0.0.0.0.00....0.0.000.0.0...00.00...0.0.0.00.00.00.000.0.0.0 00 0...0.00..0.0. 0.00..0...0.00.000.0...0.00.00. 0....0.0.00.0....0.00.0. 0..0.00.00 00....0.00.000.00.00.00.0.0.0.00.....0.0...0.0.00.0..0...0.00.00.0..0..0.0.00.0.0.0..0..0.0...00.00.00.0....0.0..0.0..00.00.0.0.0....00.00.00.000.00.0.0.0.0.0.00.0.00.0.0.....0.0.0....0.0.00.0.....0.00 0...0.00.000.0.0 00... 0.0. 0.00 0..0 0.0....0.....0.0.00...00.0....00.0.0...000.00.00.00.0.00 000.0.000.00.00.0.00..0.00.000..00.0.00..0.0.00 Linear interpolations with respect to 0 will in general be accurate at most to two decimal places.

Understanding and Learning Statistics by Computer Table A. (continued) INDIVIDUAL TERMS, BINOMIAL DISTRIBUTION n x 0 I 0 0 0 0 0 0 0.0.0..0.00.000...0.00.000...0.0.00.0..0.0.00.0....0.00.000....0.0.00....00.0.00.000...0.0.0.00.....0.0.000.000.....00.00.00....0.0.00.000..0..0.0.0.000.000.0..00.00..0.0.00.000.0. 00 0.0.0.00.000.0....0.0.00.00.0 0....0.0.00 e..0..00.0.00.00 0...0 0.0.0.00.000 0.....00.0.00.00.0....0.00.0.00.000.0.00....0.00.00.000.0...00.0.0.000.00.0 0...0..0.0.00.0.0.....0.0.00.00.00.00...0.00.00.0.0....0.0.00.00.0....0.0.0.00.00.00.0.0...0..0.0.00.000 0.00.00. 0.0. 0 0 00.000 000.00.0.0.0.00..0.00.00.00.0.0. *.0..00.0.00.000.00.0.0..0..00.00.0.00.000..00.0 0.00. 0. 00.00.000.00.00.0..0..0.0.00.000.00.0.0..00.0...0.0 00.000.00.0.0.00....0.0.00.000.0.000 0 00...00 0.000.000.00.0..0.0..0.00.000.000.00.0.00.....00 0.00.00.0.0.0....0.0.0.00 by..0. on /0/. For personal use only.

Appendices Tables Table A. (continued) INDIVIDUAL TERMS, BINOMIAL DISTRIBUTION e n x.0.0. 0. 0..0..0 by..0. on /0/. For personal use only.. 0.0.00 000....0.0.00.000 000.0...00.0.0.00.00.00. 0.. 0 00.00 00.0.0.0.0..0.0 00.000.00-.00....0 00.0.0.00.00.0 0....0.0.00.00.0.0.0.....0.0.000.00.00.00.0....0.0.00.00.0.0..0.0..0 0 000.00.00.0.0.000.00.00.00.00 0 0 0..0.00 000. 0(KX)..00 00.000...0. 0.00 00 0...0.00.00.000.0.0.0.0.00.00.000 0....0.0.000 000.00. 0.0.0.00.0 00.000 000.0 0.0..0.00.0.00 000.0.0.0.0.0. 0.00.00 00 000.0.0....0.0.0.00.00.00 0. 0 0 00 00.00.00.0.00.0. 0.0 0.00.0.0..0..0.00.0.00.000 00 0.0.0...0..00.0.000.00.0.0. 0.0..0 00.0.00.00.0.0..0...0.00.0.0.00.0.0...0 0.00.00.00.000.0.00.0..0..0.000.00.0.0...0..0.0.00.000.00.0.0.0.... 0.000.000.000 000.00.00.000.0.00.00.000.0.0.00.000.0.0.0.00

Understanding and Learning Statistics by Computer Table A. (continued) INDIVIDUAL TERMS, BINOMIAL DISTRIBUTION n x 0 0 0 0 0 0.0.0.0..0.00.000....0.0.000....0.00.00.0.....0.0.00.000..0.00..00.0.00.000.0.00.0.000.0.00.000..0.0....0.00.00.000.0.....0.0.00.00.000.0.0..0..0.00.00.00.000.0.0....00.0.00.0.00.00.0.0...0..00.0.00.00.000.00.0....0.0.00.00.00.000 e.000.0..0..0.0.0.0.00.00.00.0...0...0.0.00.00 OOOO.00.0.0.0.0...00.0.0.00.000.0.00.0.0..00.0..00.0.0.00.00.00.0.0...0..0.0.0.00.00.000.00.0.0.0..0...0.0.0.00..000.00.0.0..00...0.0.0.00.00.000.000.00.00.0.....0.0.000.00..000.00.00.0.0.....0.0.0.0.000.000.00.0.0.....00.0.0.000.000.00.00.0.0....0.00.0.0.00.00.000.00.00.0.0......0.0..000.00.0.0......0.0.0.00.00.0.0.0....0.00.0.0.00.00.000.000.00.00.0.0......0.0.00.00.0.0......0.0.00.00.000.00.0.0.0.....0.0.0.00.000.000.00.0.0.00..... by..0. on /0/. For personal use only.

Table A. (continued) INDIVIDUAL TERMS, BINOMIAL DISTRIBUTION Appendices Tables n x.0.0..0 e..0..0..0 by..0. on /0/. For personal use only. 0 0 0 0 0.....0.0.00... 0 0.00.000.......0.0.00 00..0..0.0 0.00.000.000 000...0....00.0.0.00.000..0... 0.0.00.00.00.0 0.0...0.0 0 00.00.000.0 0..0..0.0.0 00.000 000.00.0.00. 0. 0..0.0 0.00.00.000. 00.0.0...0...00 0.00.000.000.00.00.00.0.0...0.0.00.00.00.000.00.0.0 0.... 0.00 00.00.000.00.00 000 oooo'.000.00.0.0.00.....00.0.0.00.00.000.000.000.0.0.....0.0.0.00.00.0.00.00.000.00.0.0.0.....0.0.0.00.00.00.0.00.0......00.0.0.00.0.0.00.000.00.00.00.0.0....00.0.0.00.00.000.000.0.0.0......0.0.00.00.0.0.00.000.000.00.00.0.0.0.....0.0.0.00.00.000.00.00.0.00.0.0.0..0.0.0.00 i 0.000.00.000.00.00.0.00.00 Reprinted with permission from CRC Handbook of Tables for Probability and Statistics. Copyright by CRC Press Inc., Boca Raton, Florida.

Understanding and Learning Statistics by Computer Table A. Random Numbers (The first decimals). Line/Col. 0 0 0 0 0 0 () 00 0 0 0 0 0 0 0 0 00 00 0 00 0 00 00 0H 0 0 000 0 0 0 0 0 () 0 0 0 00 0 0 0 00 0 0 0 0 0 0 00 0 () 0 0 00 0 0 0 0 0 0 0 0 0 0 0 00 00 0 (> 00 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 () 0 0 0 00 0 0 00 0 0 0 0 00 00 00 0 0 0 0 () 0 0 0 0 0 0 0 0 0 00 00 0 0 00 0 0 0 0 0 0 0 0 () 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 () 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 i 0 0 0 00 () 0 0 0 0 0 0 00 0 00 0 0 0 000 00 00 0 0 I 0 00 0 0 (0) 0 0 0 00 0 0 0 00 0 0 00 00 0 0 0 0 0 0 0 0 000 000 () 0 00 00 0 0 0 00 0 0 0 00 0 0 0 0 0 00 0 0 0 () 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 00 00 00 00 () 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 000 0 0 0 () 000 0 0 0 0 00 0 0 0 0 0 0 00 0 0 00 0 0 0 0 00 I Reprinted with permission from CRC Handbook of Tables for Probability and Statistics. Copyright by CRC Press Inc., Boca Raton, Florida. by..0. on /0/. For personal use only.

Table A. Standard Normal Deviates (M = 0, o = ). Appendices Tables 0 0 0 0 0 0 0 0 0 0. 0.00..0. 0. -. -0. -0. -0.. -0. -0.. 0.0-0. -0. 0.. 0. -0.0 0. 0. 0.. 0. -. -. -0. 0. 0. 0. -0.. -.0-0. 0. 0 0 0-0. -0.0 0. -0. 0 - -0. -0.0 by..0. on /0/. For personal use only. 0.0. -.0-0.0. -0. -. -.00-0.00. -. -0.0 -..0 0. -.0 -. 0. -0. -. 0. 0.. 0.0 -. 0. 0. -0. 0..0 -. -0. 0. -..0 0.0 0. -.0-0. -0.0-0. -.0-0. 0. 0.. -0.0 0. -0. -. -0. -0.. 0. -.0 -.00.0 -. 0. -0.0 0.0 0. 0.0-0.0 -.0 0.0 -. -0. -0..0. -0. -0. 0. -0. -0. -. 0. -0. 0. -0. 0.00-0. -. 0. -0.0. -0. 0.0-0. -. -0. 0. 0. -.. -. 0. -.0-0. 0.0 0. 0. -. -0. 0.0. -0. -0. -0. -0. -.0-0. 0. 0. -. -0.0 0. 0. 0. -0. -0. 0. -. -0.. -0...0 0.0 0.. -0. 0. 0. -.0 0. -0. -0. 0.0-0. 0.0 0. 0.0 0. -0. -.0-0. -0.0 0. -0.0 0..0 0.00-0. -. -0. -. 0. 0..0-0. 0. -0. -0. 0.0. -0. -0.0-0 0. 0. - 0 0.0. -0. -0. -0-0 -. 0. -0. 0. -. -0..0-0. -. -0. -0..0 -.0. 0. -0. 0. 0.. -0. 0. 0.0 -.0-0. 0. -0. 0. -0. -0.. -.0-0. -. -.0 - -0. -0 0 0. 0.0 0.. -0.. 0. - 0. 0.0 0.00 0.0. -0. -. -0. 0. 0. -0. -0. -0..0.00..00 0. -0. 0 0-0. 0. -0..0-0. -. -.0.0.0 0.0 0. 0.0 0. -0. -0. 0.0 0..0 0.0-0.0 0. -0. -.. -.0 0. 0...0-0. -0.0.0-0. 0. -0. 0. -0. -.0 -. 0. 0. 0. -. -0. -. 0. -.00 0.0 0.0-0. -0.0-0. 0. 0.00 -. -. -0. -. -0.0-0. -0. -0. -. 0.00-0. -0..0 0.. -0..00. 0. -. -0. -0. 0. -0.0 -.0 0. -0. -. -0. -0. -.0 -. 0. -0. 0-0 0 0.0-0.0 0. -.0-0. -0. 0. -0. -0. -0.0 0. 0.0 -.00 0. -0.0.0 0.0 0.0 0. 0. -0. -0. 0.0 0. -0.0-0. -0. 0.0-0. -0. -.0 0. 0.0 0. -.. -0. 0. -.0 0..0-0.0-0.00-0. -.0 -. 0. -.0 0. 0. 0.0 0. 0. 0...0 0. 0., -0..0 0. -0. -.0 0. 0. 0. 0. -0. -0. 0. -0. -0. 0.0 0.. -0. -0.0 0. 0. -.0-0.0-0. 0. -0.0 -. 0. -0 0.0 0. -. -0-0. 0.. 0 0-0 -.0 -.. -0.0 0.0. 0C 0. -0. -0..0-0. -.. Reprinted with permission from CRC Handbook of Tables for Probability and Statistics. Copyright by CRC Press Inc., Boca Raton, Florida.

by..0. on /0/. For personal use only. This page is intentionally left blank

INDEX by..0. on /0/. For personal use only. acceptance-rejection method bootstrap 0 Central Limit Theorem confidence interval, contingency table correlation correlation fallacy cumulative distribution function (CDF), cumulative frequency 0 data distribution Bernoulli beta 0 binomial, chi-square, Erlang exponential F, gamma geometric hypergeometric normal,,, normal, bivariate Poisson t, uniform, efficiency of estimator frequency table statistical inference 0 histogram hypothesis testing, alternative hypothesis composite null hypothesis p-value, risk in simple Type I error Type II error invariant statistic inverse CDF method jackknife 0 least squares estimator linear congruential generator maximum concentration criterion 0 maximum likelihood estimation 0 mean mean, statistical inference one sample two sample paired sample

0 Understanding and Learning Statistics by Computer by..0. on /0/. For personal use only. minimum variance unbiased estimator (MVUE) modulus operation moments Monte Carlo integration 0 Monte Carlo method no nparametric inference 0,0 permutation test Poisson process population probabilistic algorithm 0 probability, axiom of conditional probability density function (PDF) proportion, statistical inference quicksort random number subset variable regression robust inference 0,0 sample mean median 00,0 sample size determination for confidence interval for hypothesis testing software reliability trimmed mean 0 unbiased estimator variance statistical inference

Answers to Selected Exercises by..0. on /0/. For personal use only. Exercise.,,. No, it can generate at most different numbers.. See whether it is uniform.. (iii) 0,.,..,0. No integer division is used for modulus operation.. S= {(i, j) i, j =,,,,, } (a) / (b) / (c) / (d) /. (a) / (b) /. (a) /,000 (b) /0. (a) 0. (b) 0. Exercise. JU =., a =.. (0., 0.), (0., 0.), (0., 0.). (a) 0. (b). 0 =0.. 0. (i) 0. (ii) 0. (iii) 0. (iv) 0. (v) 0.. 0.0.0. /X. e' '. Pr{Waiting time longer than T} = Pr {No call in the interval [ 0, T ]}. Ag. average time: Agl =., Ag =.. (i) (ii) (iii) (iv) (Your answer may differ some.). (i) Acceptance-rejection (ii) Inverse CDF (ii) Acceptance-rejection Exercise. (0.,0.).. No. Riskprob. = 0.. Yes. Riskprob. = 0.00. (a) risk = 0.0 (b) risk = 0.

0 Understanding and Learning Statistics by Computer. (a) p-value = 0.0 (b) H 0 : p x = p =... = Pio = /0, /f : One of them is not /0. The risk probability can be found by simulation. It is 0.... (i) 0. (ii) Use Poisson 0. (iii) Use normal 0.00. (a) 0. (b) 0.00 (c) n =, c = by..0. on /0/. For personal use only. Exercise. (i = x,d =(n-\)s /n. (i) No. (ii) is not a good measure of the mean direction.. Yes.. Yes.. They can be reduced to two parameters. Exercise. p = 0.0. ±.. 0. ±0.0. None is significant at 0.0 level.. Mean interval is robust against non-normality, but the variance interval is not.. Q = 0., p < 0.00. Q =., p < 0.00. The breakdowns are not random..0 Q =., p< 0.00. y = -. +.JC, ft is significantly different from 0(p < 0.0).. Pi = 0., p = 0. both significant at 0.0 level.. p = 0.0. 0.. p= 0. Exercise. (i) \/N (ii) n/n. (n - l)/(n + ), Store the largest so far in the memory and replace the smaller one if x(n + ) is larger. Expected # of comparisons = W+n(V). n - l /n\ ~(e/n) n. No, the data may be partially ordered. The first one may be very far away from the median.. (i) 0.00 (ii) 0...