1) every separate IV needs a separate F ratio a) true b) false 2) In a two-way ANOVA, which is broken up into separate parts a) between group variability b) within group variability c) both 3) Effects of multiple IVs together is produced by the combination of variables a) main effects (ME) b) interaction effects 4) the effects of each IV separately a) main effects (ME) b) interaction effects 5) Limitations of an ANOVA/ ANOVA requires that... a) subjects are randomly selected b) subjects are independent of each other c) ANOVAs are restricted to studies based on between group comparisons d) participants are randomly assigned e) Ns are exactly equal f) a-priori test is significant  6) why not just manipulate all IVS separately?  a) It does not account for potential interaction effects b) Time consuming c) It results in more type I errors d) It results in more type II errors 7) Each IV is manipulated at how many levels? a) 1 b) 2 c) 3 d) 4 8) What is a 2 way ANOVA a) a 2x2 design b) a 2 IV design c) a 2 DV design d) a design with 2 variables 9) C a) correction factor b) column c) rows d) number of cells/sample groups e) interaction f) Chi 10) col a) correction factor b) column c) rows d) number of cells/sample groups e) interaction f) Chi 11) K a) correction factor b) column c) rows d) number of cells/sample groups e) interaction f) Chi 12) row a) correction factor b) column c) rows d) number of cells/sample groups e) interaction f) Chi 13) rxc a) correction factor b) column c) rows d) number of cells/sample groups e) interaction f) Chi 14) squiggly X a) correction factor b) column c) rows d) number of cells/sample groups e) interaction f) Chi 15) does a 2 way ANOVA need a post-hoc a) yes b) no c) depends on if you did an a-priori test d) depends on of the f-test has significant findings 16) what do parallel graph lines mean? a) strong interaction effect b) no interaction effect 17) What is a factorial ANOVA a) a 2 way anova b) a 2x2 anova c) an anova that's more than 2x2 d) an anova with only one IV e) an anova with 2+ IVs 18) how do you find the homogeneity of variance  a) The mean of a Levene's test b) The standard deviation of a Levene's test c) The mean of an effect size d) The standard deviation of an effect size 19) What is the ideal range of significance for the homogeneity of variance a) 1 b) none c) .2 d) .5 e) .8 20) what are deviations from scores called a) moments b) deviations... duh c) products  d) correlations 21) Sum of cross products a) SSx b) SSy c) SP d) SCP e) SxP 22) what is the range for pearsons r a) 0-108 (if its Grace's math) b) 0-1 c) (-1) - (+1) d) 1-10 e) (-1)- (+10) f) 0-10 23) df for r a) n-1 b) n-2 c) k-1 d) k-2 24) does persons r prove causation a) yes! b) no! 25) why might there be a low pearson's r a) There is no relationship b) Low sample size c) Variables are curvilinear d) Low effect size e) It is a negative correlation f) the range is too restricted 26) Which sports equipment shape has the strongest pearson's r a) javelin b) soccer ball c) football d) hockey stick e) tap shoe 27) non-parametric tests a) ordinal b) interval c) assumes µ d) does not assume µ e) assumes normal distribution in the pop f) does not assume normal distribution in the pop 28) DF for non-parametric a) (r-1) (c-1) b) (r-1) + (c-1) c) (r-1) - (c-1) d) (c-1) - (r-1) e) r-2 f) c-2 29) What is M (when doing non-parametric test) a) Mean b) Manamana (do do dodo do) c) Marginal frequencies d) Margin of error 30) how to find Fo a) on the chart b) (Mr1xMc1)/N c) Mr1/ ((N)(Mc1)) d) I don't know!!! e) :( 31) What assumptions should you make on non-parametric tests a) Each observation or frequency is independent of all other observations b) Lack of independence will produce an inflated n c) Easily cause type I errors d) Easily cause type II errors 32) which is more powerful? a) Non-parametric tests are not as powerful as parametric tests b) Parametric tests are not as powerful as non-parametric tests c) they are equally powerful 33) which is true?  a) Non-parametric tests are safer b) Parametric tests are safer c) they are equally safe  34) What should you do if you have one ordinal score and one interval score a) do Chi and ANOVA b) make the ordinal score an interval score c) make the interval score an ordinal score d) cry. 35) how many tails does Chi have? a) 1 b) 2 c) 3 d) 4 e) 0 f) as many as your heart desires <3 36) Independent 2-group designs a) Mann-Whitney U b) Sign test c) Wilcoxon matched-paired signed rank test d) Kruskal-wallis test 37) Which is the most powerful non-parametric a) Mann-Whitney U b) Sign test c) Wilcoxon matched-paired signed rank test d) Kruskal-wallis test 38) Before-after/matched measures used, only focus on the direction of difference, ignores amount of difference between scores a) Mann-Whitney U b) Sign test c) Wilcoxon matched-paired signed rank test d) Kruskal-wallis test 39) Matched group design, Differences in scores are measured in an order of change ex: most to least or least to most a) Mann-Whitney U b) Sign test c) Wilcoxon matched-paired signed rank test d) Kruskal-wallis test 40) Non-parametric test as substitute for one-way ANOVA a) Mann-Whitney U b) Sign test c) Wilcoxon matched-paired signed rank test d) Kruskal-wallis test 41) What does a persons R of +1 mean? a) who knows? b) the relative position of a score is associated perfectly to the other variable c) there is a weak correlation d) there is a pretty strong correlation e) both variables are the same 42) Linear regression: score being predicted a) Ŷ or Y b) Y c) A d) By e) X 43) Linear regression: y value when X=0 a) Ŷ or Y b) Y c) A d) By e) X 44) Linear regression: intercept/constant, also known as the y intercept a) Ŷ or Y b) Y c) A d) By e) X 45) Linear regression: second intercept/ constant, also the slope of the line relating the value of y to x a) Ŷ or Y b) Y c) A d) By e) X 46) Linear regression: x value a) Ŷ or Y b) Y c) A d) By e) X 47) What are the differences between linear regression and correlation a) they are synonyms b) With regression you are able to make predictions about actual scores c) With correlation you are able to make predictions about actual scores 48) Can there be multiple Bys, if so what do you do with them? a) there can only be one b) add them c) multiply them d) do each equation separately then add them together e) do each equation separately then find the mean f) cry, give up, quit, anything other than more math 49) β a) type I error b) type II error 50) α a) type I error b) type II error 51) we reject H0 when it is true a) type I error b) type II error 52) fail to reject the null a) type I error b) type II error 53) how many effects are in a 2x2? a) 3 b) 1 c) 2 d) 4

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