This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Final Exam 5tuc_1 ﬁy'gg Beiow is e nontachaust'i're list of topics d1at will likely he tested in some form on the finEl Exam. Note that just homoso a topic does
not appear here does not: MEET! that it wifl not be on the ﬁnal. DEpite d1is. the topic below are among the most important ones
t". at have been ooliiercd. All necessary formulas and tables wilt be ptouidedl The "Statistics organiser" on p. Ell523 is an excellent overview of everything in the boolc. [Ine important thing to lrnow about the ﬁnal is that mamI of the qucaﬁons will beaten irons [acorns 1 through 3 [although their
might be slightly modiﬁed], so tool: o‘trer those exams and their answer Freys. In addition; the studf guides for Exams limough 3
will be useful for preparirrEtor the ﬁnal. Chapter 1 K." ow two at samples and populations are. and the relationship between sample statistics and population parameters I Ele familiar with the concept of sam pling error : Eta able to icenrtfy independent [or no assIndependent“; van ables and dependent variables i Know ".hE scales of measurement and be able to riasslﬁ.I a variable :noo one of U'tE sci les
Chapoer 2 e Be able to Ionic at a freqJ I:an dietriasuﬁnn table. histogram, bar graph, or freCuencg pollrgrsn and i..tt,rpr\q_vt what
information is contaioed therein
II incow the corn rIon shapes of diso'ibvtions I:st metric, pooi tivol'r or neg“Ilivnhl JamiNod] tjhapwr 3  tindersta ncl the purpose of ﬁnding a measure of central tendenc'g.r
II Be able to ﬁnd the mean, media n.a.'::l.11ocle.‘or a set of scores
II Know which measure of oertral tcncienor is preferred in diilexcrlt situations Chaptcrd  Understa nd the purpose of finding a measure of spread or variability
II Be able to find 55, standard deviation is. or]. and varia no: is} on] tore sampie or population Clippiﬂ 5 a nr: anle rn 1"nci a .WJIII'F based on a “air score anc the rreari anc so of a set o: scores  Kr.ow wcat “for113:0" Is conta ned n a zrscore — Be able to é"cud a raw score tITSIZC on o . sro'c and the Wear: and SCI rI" 'I so? of soorcs I BI; ahlc: tn :rarIj.'o:rrl some}. Irom one some. Lo nautiwr osing : toursn ﬂit. Know that recones that are close to zero {central} are c=ose the mean a4o twerefore are representative of a population inr
mmplcl. .1an that tro'tn that are in'threr from ten: tamerrel. are iar front E1: WEEi.“ and not reurestntutitr of :: rauncIntinn
lor samplel 5}: I ltnowwi'uat the moan and SDot a set oi : scores alwa'rs is Chapter is  Know how to ﬁnd the probability oF an event occurring based on frequencies  Knowwhatrandom sampling is I Uncierstand the relationship between probabi‘it'f'. trcquonn', and area in graphs 1 Be ahlptn ﬁnd the pmtlahili'q' of certain scones being sampled based on more: and LE:1’_ normal distribution [that is, knew
how to use the Unit N orma! Fable in the hat}: of the book] i understand that in a normal Elstn'htlﬁﬂr'l gscnres that: ans close tn Jern have higher freriuencf [and therefore higher
probabii told. and those that are fat From zero have lower Freq uonog' (and lhcrtlm r lﬂwur pink"bills? L'hapter'i‘ [Even though the list 5mm is shert, this chapter is the rnch'. important one to understanding how hypothesis 1151: mrki ' binaw what a sampling distribution ofnieens ie
i Know what the expectrd veiue dfthe mean is.
 mm»... whatthe emeerd error efthe mean is. and what it leltt you  Knuwwha: mu ices. suncard error bigger and smaller
 Undergiand 1.2 Law of Lrenji: Mambars and haw it"s. relade to sampling error and standard isl'rﬁl'
an, uhleto ﬁred :5: peobahiiibr o.‘ certain temple means etulrr‘fr'e batted art zsmnzs timi' the normal dittﬁbuﬁen [That is, lmow how to use the Uni: Ndrmai Tattle in the Didi i3me bunk: Cha pters  UI'IIIIEFEE"E witg h'fFIGti'lﬁis tests are done
a Undcrudtuﬁ :ne purpcse and FII'L‘ICEd ore at etch of the fee stem of hypothesis tEEtii'LE 1. Starve the null E.'.'_'i alternative l'rypﬂthcoi:
F. :::i the crime! talueei the Libat slalirst'ii:
3. F=.d the observed value ofthe test slenst
i:_ Decide wt: ha: 3:0 reiecl. :Jie iiuli hypdthbsis ur nn:
5. Drawa cancusiﬂﬂ based on your decision in step ‘1 and The SHITDIE means
 Understanc whata :rit'ical value tells Wu
o Lindersteed what facldr‘t mate the observed vaiue of the test statistic :12 in this chapter] get baggerbr srnbiler « Know tila: aim I and Type II ems: oontepteal hr and hi: thiefuser tontrﬂrlr what M EITDFS “ﬂuid he in a Speciﬁc tesuzfth design
 Knowwhat permer it. and what makes pmh'ergtr up and dawn Itihagzl‘ter'iiI . underweer what a sinele sample design is, and what klnd ofnuil t't'euu’leiit is tested in that: tituETittnt
 Be able to d .etinguisr. between when a rtm't sheuid be :II:r"l'I‘I'I'Iei'—i and When a l 105': SHGUid he PEI'i'Orl'I‘Iliii  Be able to peeform :i singlesample t—tett. ind udine el‘. five ereps
: Unde'stend wth l'atbsrs make the observed value 6i ﬂ'ietEst Sﬁlti'sﬁc lE in this IIi'IEFIIEF] act WEE?!" 0F Email” Cha enter 13] o Undersea1d what. or. inéependent 'ttll'l1piES design is. end what ltlnd df null hypothesis is tested in these titeadttea in Be able toI per form an independentsamples ttt‘tir inductee 3" iitE tit“Pt
. unnereena what rem. . make :‘ne abscrvcd eelue of the test stulihtiLif in this chapter] eat HitterDr Sinai“Er Ci’..!'.:'.L:i ‘ ‘ . 'Jrﬁcrgjanvj whdl’. .1. related garnplm. design is_ arm whu'. kiwi 01' ".L: i'rlrpntt'rsi". is ﬂawed in these 'tillit‘It'tﬂr'lﬁ I ee :'_r.i:: 'tu Wrenm a relarea HdrltpiES t test. ineluore all ‘Ne stern
I. Unﬂfirrltafld wha‘l [rtmm :r. maﬁa mi {Ibslllr'eFI‘i '4'2':IJE Elf the 1133!. 'eldiiﬁi'ili if in This theotwl Hat bigger UFSF'UllL‘r
a Understand were this. kind err tlzst it: rndte pmvel'll'. than u: iridede edentserrpleet lLest Chapter 1.2  '.J ndorstené IJe purpose ot‘ trialtine estimates
0 Be able 1.; generabea pdirll etdrnate  Be able to generati an interval estimate iusinga formula]
 Know what testers make inhequ eed matﬁ narrower and wider Cha pter 15l understned what: kinds etdme'gns are appwrtﬁate for an anel'r‘tikﬁi M'ﬁt'ial'lCE WNWQ]; Mid What kind Uiﬂu" i'l'iI'3"3'ii"li'5iTL i"
tatted in Lime :terabions Understand why an runow. ls peit'ormed insbead ofmultiple t—tests Understand that the .Fratio is a traction with a uariante in the nu memosr and another Ira dance in the denominator
Know what tattors nsalce the :1 umelator and denominator of me F—Iatio get bigger or smaller Be able to perform an snow, including all Five steps Be able to putthe results of an ANU'JA in a sermon nr tabII: understand why pun5'. lie3:1; are needed after rejecting the nulE hrlpothsisusing F  Be. able to penEm Tukelr's HSEI posttart and be abie to draw conclusions based on I: Chapter 1! : H am: a gonorai sons: of NIH“ is Factorial design it.
 Knuwwhat a main effect it and we. at i': tests  Know what an interaction is i be able to perform a factorial ATIEI'IJ'P. El'erote.r 15 e Understand what kind; ni reenanch queetinnr. it. re .1 pprnpriate For conupon up; a correlation
 Be able to create a Iscatterplot and Interore: die Information In a starterpmr  Be able to compute Pearson'sr i Know what Pearson'sr tells you. and what uses :here are for torreSations en El: atllc tEI ca I11, aura l'nf'pnthotil; test using Manson's r General thirgs to know  be able to disongulsh bameer tee general goals of destriptive and Inferanbal statistical bechniques i Know witIr hypothesis tests are done: Because sampling error can make is look li ice something systematic Is happening when
there is nothing happening, I: Be able to diawa correct conclusion based on a hypothesis test. This means that you should know. whether the test tells
you iFone group is different from another, whether there is a relationship betwee’r m variables. etc. I have or! eruen.I
answer keg.r tr:ed ED moo el what proper tontlusions look like. In add room. when you draw: :oncluson, make itcni’orrnatlve!
That is. say which ﬁloup socII: higher on lower, or if the relationship is positive or negative. etc.  Be able to pic's: this right. test statistic for a particular research design: (.I I3 i”: lf you are oarrpari nil, one sample's moon to some known population mesa, use a singiesarrple z— or t—test: use I
only if the population SDI's knawn lf'p'ou are comparing two independent samp! es' means to one anoier, use an independentsampler. t—test
rf'lrou are oompari ngtwo related samplE' means to one anoth er. use a relatedsamples t—te_r.t II'_.ou are eompari mg the means from th ree or more groe ps Lo one Lanethee. use a one meter snow. il's'uu ullllllxilﬁ1piﬂ:i‘§ll‘llll :‘Ieurl in .I lent.1rl:h:Er".i5n w'll'l LIIm Factor5. LIE: u lnﬂqriu' ANOVA i.‘ LuzI ' e examining the ionshi5: be'. two au an .'e variables. use the correlaten roe ...
View
Full Document
 Spring '08
 McDonald
 Psychology

Click to edit the document details