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J. \~Vildl. Manage. 63(.3):1999 <br />a very logical way to make decisions in the fare <br />of uncertainty It allows for incorporating be- <br />liefs, data, and the gains or losses expected from <br />possible consequences of decisions. See Wolf- <br />son et al. (1996) and Ellison (1996) for recent <br />overviews of Bayesian tnethads with an ecolog- <br />ical orientation. <br />STATISTICAL SIGNIFICANCE TESTING • Johnson 771 <br />BAt:,~N, D. 1966. The test of significance in psycholog- <br />ical research. Psychological B+dletin 66:4?3-117. <br />BARNAx~, G. 1998. Pooling probabilities. iVew Sci- <br />entist 157:47. <br />BAUERNFEIND, R. H. 1968. The need for replication • <br />in educational research. Phi Delta ~Kappan 50: <br />126-128. <br />BAYES, T. 1 ~ 6,i. An essay toward solving a problem in - <br />the doctrine of chances. Philosophical Transac- <br />tions of the Royal Society, London 13:370-418. <br />BERGER, J. O. 1985. Statistical decision theory and <br />Bayesian analysis. Springer-Verlag, Berlin, Ger- <br />man.. <br />, ~~xD D. A. BERRY. 1988. Statistical analysis <br />and illusion of objectivity. American Scientist~76: <br />159-165. <br />\D VL DEC.A~IPADI•. 1987. Testing precise <br />hypotheses. Statistical Science 3:317352. <br />• AxD T. SELLI:E. 1987. Testing a point null <br />hypothesis: the irreconcilabiliri• of P values and <br />ew~dence. Journal of the American Statistical As- <br />sociation 52:112-12_'. <br />BExt;50~. J~ 193S. Some ditficulties of interpretation <br />enciittntered in the app(ic;ttion of the chi-square <br />test. journal of the A+nerican Statistical rlssocia- <br />tiou :33:36-•54•'_. <br />Box. C. E. P. 19S0. Sampling and Baves~ inference in <br />:cieutific• modelling and rob+tstness. Journal of <br />the Rowal Statistic:u Socirh• 1-1:i::i8~>-430. <br />. ~xn (:. C. Tta(,. 193. Bayesian inference in <br />statistical :u,alwsis. Addison-\Vesle•:; Reading, <br />Massachusetts. USA. ~ - <br />Bt cla_\xn. S. T., 1:. P Bt~xxn:t». Axe \. H.:\t;- <br />CC~TI\. 199 ~locie( selection: au integrated part <br />o(intrrrncr. Bi+~n,rttic•s5:~:riU:i-(il•5. <br />Bt-r,~na~t. I:. P...~xo D. R.:\~nt:xsox. 1995. Model <br />selection ;uul inference: a prtctical intirrmation- <br />thet~retic ahprnac•h. Shnrr r-\~rrlag. Vrw Yorl:. <br />~irwr 1"rn'k. 1.~$iw. <br />t:.t>I~'htil.~.. \1. L9y^_. Cttuhdrncr intrr~als. Rowal 5ht- <br />tistical 5uc•ich' \rwws ;u,d \nh-s !S:~-•5. <br />(:.trr.r~. li. I'.. ~~r, T..\. L.ut~t~. 1996. Baces and ru+- <br />hirical H;n;•s me•tht+ds (nr datu ;urtlesis. (:hapm;ut <br />~\ I fall. London, l nitetl him~dont. <br />(:,\r;\"ha;, li. l'. 19 ti. Thr case a~aiust statistical sil~- <br />nilic;uicr U-stingy. Ilan:o'd tdnc:+tiunal Rrvirwc <br />t•ti:: i-~-: 1951. <br />(:I..~t:F. (:. .\. 19(1:1. Ilwixrthrsis tr_stiu>; in rrl;ttion to <br />statistical nu•thudnio~n. Rrw~irwv of F:ducatiun:d <br />(:uru<\. I. 14)ti~ti. St+tishctl ltuwcrr :uralcsis (nr the l+r- <br />haw inch x•icncrs. Src•ond edition. Ltwvrencr Erl- <br />h:uun .\sstK•iatcs. Ilillsd;tlr, \r•.v jersey. U5;\. <br />IS)si-{. I'hr e:u'th is round . )~ < .0.~1. Amrrir;u+ <br />Pswch++ltn~ist "5):5)9 -11111:3. <br />D-UTU~. l'. ti. L95)ti. Reversal of the burden uf• prooF <br />in fi.aLcrirs n+:ucn~rn+rnt. Scienc•r_'79:521 S2-'_. <br />DICGR(>tPr. \I. I[. l9~(1. Optincd statistical decisions. <br />MrCrawc-Fill, ~'rwc York. ~iewv York, USA. <br />Dr;>n~c, \1'. E. 195. (h, prohahility :a a basis li,r <br />action. Anucric:u+ Shttistician 39:1[6-1.52. <br />Et.l.rsci~. :\. ~1. 199fi. An introduction to B;n'esi:u+ <br />inl~errnc•e lire ecolr>,gical research and environ- <br />mental decision-makim~. Ea,lo;~ical Applications <br />fi:10:i[i- LO-tfi. <br />Cr:xAxr~. P. ll.. U. R. 5>IITH, :\~D C. WEER:\6liODY. <br />~ CONCLUSIONS <br />Editors of scientific journals, along with the <br />referees they rely on, are really the arbiters of <br />scientific practice. They need to understand <br />how statistical methods can be used to reach <br />sound conclusions from data that have been <br />gathered. It is not sufficient to insist that au- <br />• thors use statistical methods-the methods <br />must be appropriate to the application. The <br />' most common and flagrant misuse of statistics, <br />in my view, is the testing of hypotheses, espe- <br />cially the vast majorih~ of them known before- <br />hand to be false. <br />With the hundreds of articles already pub- <br />lished that derv- the use of statistical hypothesis <br />testing, I w•as somewhat hesitant about writing <br />another. It ront:uns nothing ne~v. Blit still, read- <br />ing The ~r»irnal of [Vilc~life Vla»a~erne~nt makes <br />me realize that the message has not really <br />reached the at.ulieuce of wildlife bioiogists. Our <br />work is important. su we should use the best <br />tools we have available. Rareh, how'rver. is that <br />tool statistical ii~puthesis testing. <br />ACKiVOWLEDGME~ITS <br />\V. L. Thompson and C. :~. Rihic deserve <br />thanks Coe or~ranizin~r the svmposimn that <br />prompted this article. I appreciate the enconr- <br />a,rment and cr»nments un the mamiscript pn>- <br />~idrd bt~ D. R. Audrnon. J. O. Brrgrr. D. L. <br />Larson: til. R. ~iester. \V. 1/. Nrv~~ton. T. L. Shaf- <br />fer, S. L. Sberil(•. B. Tbuntpson. curl C. G \Vltite, <br />who nrntetlteless reut:tin hlauteless fin- any mis- <br />iutrrpretaticnts er+ntainrcl herein. B. R. Ltrliss as- <br />sistr..d with the prr~par.ttion of the, manuscript. <br />LITERATURE CITED <br />:\BFl.ut~, ti. P 199. _~ rrtrus(trc•tiwr on the signi6- <br />c;u+ce test h:u+ ou 1999 IIf there wvrrr no signif- <br />ic•:utcr tests. thrw~ would he invrntrdl. Pages 11~- <br />l-t l in L. L. [ [:u-low, S. A. ~Inlaik, and J. 11. <br />Stri,~er, editors. 4\'Itat if there weer nu si~nifi- <br />c;u+cr tests:' Lawvrrnc•r Erlb;unu Associates. ~luh- <br />wvah, \rw Ic•ncw'. USr\. <br />\~scr,~,ntr:. F. J. 195(1. Discussion on Dr. Dawid•s and <br />Ur. luhnsons Paper. lourn:tl +,F the Royal Statis- <br />tical Sucieh lS:°_~-'_i. <br />