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Tables

© The McGraw-HiliCompanies. Z001

I Appendix C: Tables

c

FactorialsThe BinomialDistribution

ThePoisson Distribution

RandomNumbersThe StandardNormal Distribution

The t DistributionThe Chi-SquareDistribution

TheF Distribution

CriticalValues for the PPMCCriticalValuesfor the SignTestCriticalValues for the Wilcoxon Signed­RankTestCriticalValuesfor the Rank CorrelationCoeffi­cientCriticalValues for the Numberof Runs

CriticalValuesfor the TukeyTest

668

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BackMatter Glossary ofSymbols © The McGraw-HiliCompanies, 2001

Q

Glossary of Symbols

a y intercept of a line MR Midrange

(¥ Probability of a type I error MSB Mean square between groups

b Slope of a line MSw Mean square within groups (error)

(3 Probability of a type IT error n Sample size

C Column:frequency N Population size

cf Cumulative frequency neE) Number of ways E can occur

.c, Number of combinations of n objects taking n(S) Number of outcomes in the sample spacerata time 0 Observed frequency

C.V. Critical value P Percentile; ProbabilityCVar Coefficient of variation p Probability; population proportionD Difference; decile p Sample proportion15 Mean of the differences p Weighted estimate of pdJ. Degrees of freedom P(BIA) Conditional probabilitydJ.N. Degrees of freedom, numerator peE) Probability of an event EdJ.D. Degrees of freedom, denominator peE) Probability of the complement ofEE Event; expected frequency; maximum error .r; Number of permutations of n objects taking

of estimate rat a timeE Complement of an event

'iT Pi.,., 3.14e Euler's constant s- 2.7183 Q QuartileE(X) Expected value q 1 - p; test value for Tukey test

f Frequency q I-pF F test value; failure q 1-pF' Critical value for the Scheffe test R Range; rank sumMD Median Fs Scheffe test value

GM Geometric mean

8 Kruskal-Wallis test value rs Spearman rank correlation coefficient

8 0 Null hypothesis S Sample space; success

HI Alternative hypothesis S Sample standard deviation

lIM: Harmonic mean s2 Sample variance

k Number of samples U Population standard deviation

"- Number of occurrences for the Poisson u2 Population variancedistribution

Ux Standard error of the meanSD Standard deviation of the differences

~ Summation notationSest Standard error of estimate Ws Smaller sum of signed ranks, WilcoxonSSB Sum of squares between groups signed-rank test

SSw Sum of squares within groups X Data value; number of successes for a

sj- Between-group variance binomial distribution

s* Within-group variance X Sample mean

t ttest value x Independent variable in regression

t0i/2 Two-tailed t critical value XOM Grand mean

JL Population mean Xm Midpoint of a class

JLD Mean of the population differences X2 Chi-square

J.Lx Mean of the sample means y Dependent variable in regression

w Class width; weights y' Predicted y value

r Sample correlation coefficient Z z test value or z score

.R Multiple correlation coefficient Za/2 Two-tailed critical z value

r2 Coefficient of determination ! Factorial

p Population correlation coefficient

Bluman:ElementaryStatistics: A Step byStepApproach.Fourth Edition

I BackMatter I Glossary of Symbols © The McGraw-HiliCompanies. 2001

Foundations ofEngineering Economy

I

© The McGrew-HiliCompenies. 2002

1.Foundations ofEngineering Economy

The need for engineering economy is primarily motivated by the work thatengineers do in performing analysis, synthesizinq, and coming to a conclu­sion as they work on projects of all sizes. In other words, engineering econ­omy is at the heart of making decisions. These decisions involve the funda­mental elements of cash flows of money, time, and interest rates. Thischapter introduces the basic concepts and terminology necessaryfor an en­gineer to combine these three essential elements in organized, mathemati­cally correct ways to solve problems that will lead to better decisions. Manyof the terms common to economic decision making are introduced here andused in later chapters of the text. Icons in the margins serve as back and for­ward cross-referencesto more fundamental and additional material through-out the book. .

The case study included after the end-of-chapter problems focuses onthe development of engineering economy alternatives.

Blank-TBrquin: Level One:ThisIs HowhEngineering Economy, Fihh AllStartsEdition

Blank-Tarquin: Level One: ThisIs How ItEngineering Economy, Fifth AllStartsEdition

1.Foundations ofEngineering Economy

© The McGraw-HiliCompanies, 2002

8. Identify the Excel© spreadsheet functions commonly used tosolve engineering economy problems.

4. Perform calculations about interest rates and rate of return.

7. Identify and use engineering economy terminology andsymbols.

6. Calculate simple interest and compound interest for one ormore interest periods.

5. Understand what equivalence means in economic terms.

3. Identify what is needed to successfullyperform anengineering economy study.

2. Determine the role of engineering economy in the decision­making process.

9. Understand the meaning and use of Minirnum AttractiveRate of Return (MARR).

1. Understand the types of questions engineering economycan answer.

10. Understand cash flows, their estimation, and how tographically represent them.

11. Usethe rule of 72 to estimate a compound interest rate ornumber of years for a present worth amount to double.

12. Develop a spreadsheet that involves simple and compoundinterest, incorporating sensitivity analysis.

This chapter will help you:

LEARNING OBJECTIVES

8luman: ElementaryStatistics:AStepbyStepApproach. Fourth Edition

BackMatter Appendix C:Tables © The McGraw-HiliCompanies, 2001

Appendix Tables 669

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Appendix Tables

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Appendix Tables 673

Note: Allvaluesof 0.0005 or less are omitted.

Source: JohnE.Freund, Modem Elementary Statistics, 8th ed., © 1992.Reprintedby permissionof Prentice Hall, Inc., Upper SaddleRiver,NewJersey.

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Reprinted with permission from W.H. Beyer, Handbook ofTables for Probability and Statistics, 2nd ed. Copyright CRC Press, Boca Raton,Florida, 1986.

Reprinted with permission frOID W. H. Beyer, Handbook ofTables for Probability and Statistics, 2nd ed. Copyright CRC Press, Boca Raton,

Florida, 1986.

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o z

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Source: FrederickMostellerand RobertE. K. Rourke,SturdyStatistics, TableA-I (Reading,Mass.: Addison-Wesley, 1973). Reprinted with'permission of the copyrightowners. . Area given

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684 Appendix Tables

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!>This valuehas been rounded to 1.65 in the textbook.

'This valuehas been rounded to 2.33 in the textbook.

dJ1ris valuehas been rounded to 2.58 in the textbook.

Source:AdaptedfromW. H. Beyer, Handbook ofTables for Probabil­ity and Statistics. 2nded., CRCPress, BocaRaton, Florida, 1986.Reprintedwith permission.

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Note:TableJ is for one-tailed or two-tailedtests.The termn repre­sentsthe totalnumberof + and - signs.The test valueis the num­ber of less frequent signs.

Source:FromJournal ofAmericanStatistical Association Vol. 41(1946)pp. 557-66.W. J. Dixon andA. M. Mood.

Appendix C:Tables

Source: FromBiometrika Tables for Statisticians Vol. 1 (1962)p. 138.Reprinted withpermission.

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I AppendixG:Tables© The McGraw-HiliCompanies, 2001

Source: From SomeRapid Approximate StatisticalProcedures,Copyright1949,1964LerderleLaboratories,AmericanCyanamidCo.,Wayne, N.J.Reprinted withpermission.

692 Appendix Tables

Source:From N. L. Johnsonand F. C. Leone,Statisticaland Ex­perimentalDesign, Vol. I (1964),p. 412. Reprintedwith permis­sion from the Instituteof MathematicalStatistics.

Source:Adaptedfrom C. Eisenhardtand F. Swed, 'Tables for TestingRandomness of Groupingin a Sequenceof Alternatives," The Annals ofStatistics 14 (1943), pp. 83-86. Reprintedwith permissionof the Institute of Mathematical Statisticsand of the Benjamin/Cummings Publish­ing Company, in whose publication,Elementary Statistics, 3rd ed. (1989), by MarioF.Triola,this table appears.

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