Chapter 15Frequency Distribution, Cross-Tabulation, and Hypothesis TestingTrue/False Questions1. In a frequency distribution, two variables are considered at a time.(False, moderate, page 4272. !"e valid percentage column in a frequencydistribution represents percentagescalculated by e#cluding t"e cases wit" missing values.(!rue, moderate, page 42$%. Frequency data may be used to construct a "istogram, or a vertical bar c"art.(!rue, easy, page 42$4. !"e most commonlyusedstatistics associatedwit"frequencies aremeasures oflocation, measures of variability, and measures of occasion. (False, moderate, page 4%&'. (ean, median, and mode are measures of variability.(False, moderate, page 4%&). If t"e entire sample is c"anged by adding a fi#ed constant to eac" observation, t"ent"e mean, variance, and median c"ange by t"e same fi#ed amount.(False, moderate, page 4%&7. (easures of location or central tendency include t"e mean, median, and mode.(!rue, easy, page 4%&*. !"e mode represents t"e "ig"est pea+ of t"e distribution. (!rue, difficult, page 4%1$. If a variable is measured on a nominal scale, t"e median s"ould be used.(False, moderate, page 4%11&. !"e mean is sensitive to e#tremely small or e#tremely large values (outliers.(!rue, moderate, page 4%111. If all t"e values in t"e data are multiplied by a constant, t"e range is multiplied by t"esame constant.(!rue, difficult, page 4%112. If all t"e data points are multiplied by a constant, t"e interquartile range is multipliedby t"e same constant.(!rue, difficult, page 4%11$$1%. !"e difference betweent"e meanandanobservedvalue is calledt"e standarddeviation from t"e mean.(!rue, difficult, page 4%114. !"e variance can never be negative.(!rue, easy, page 4%11'. ,"en t"e data points are scattered, variance is small.(False, difficult, pages 4%1-4%21). ,"en calculating t"e standard deviation, we divide by n because t"e sample is drawnfrom a population and we are trying to determine "ow muc" t"e responses vary fromt"e mean of t"e entire population.(False, difficult, page 4%217. In a symmetric distribution, t"e values on eit"er side of t"e center of t"e distributionare t"e same, and t"e mean mode, and median are equal.(!rue, easy, page 4%21*. !"e tendency of t"e deviations from t"e mean to be larger in one direction t"an in t"eot"er is called s+ewness. (!rue, difficult, page 4%2 1$. If t"e +urtosis is positive, t"e distribution is more pea+ed t"an a normal distribution.(!rue, moderate, page 4%22&. !"e first step in "ypot"esis testing is to select an appropriate statistical tec"nique andt"e corresponding test statistic.(False, moderate, page 4%%21. !"e null "ypot"esis is always t"e "ypot"esis t"at is tested.(!rue, easy, page 4%422. !"e alternative "ypot"esis is a statement t"at some difference or effect is e#pected.(!rue, easy, page 4%42%. !"enull "ypot"esisreferstoaspecifiedvalueoft"epopulationparameter,not asample statistic.(!rue, moderate, page 4%424. In commercial mar+eting researc", t"e two-tailed test is used more often t"an a one-tailed test. (False, moderate, page 4%'2'. !"e one-tailed test is more powerful t"an t"e two-tailed test. (!rue, easy, page 4%'2&&2). !"e test statistic measures "ow close t"e sample "as come to t"e null "ypot"esis andoften follows a well-+nown distribution, suc" as t"e normal,t, or c"i-squaredistribution.(!rue, moderate, page 4%'27. !ype II error occurs w"ent"e sample results lead tot"e re.ection of t"e null"ypot"esis w"en it is in fact true.(False, moderate, page 4%'2*. !"e probability of !ype I error ( is also called t"e level of significance.(!rue, moderate, page 4%'2$. For a given level of , increasing t"e sample si/e will decrease , t"ereby increasingt"e power of t"e test.(!rue, moderate, page 4%)%&. In determining t"e critical value of t"e test statistic, t"e area to t"e rig"t of t"e criticalvalue is eit"er or 02. It is for a one-tail test and 02 for a two-tail test.(!rue, moderate, page 4%7%1. If t"e probability associated wit" t"e calculated or observed value of t"e test statistic(!1 234 is less t"an t"e level of significance (, t"e null "ypot"esis is re.ected.(!rue, moderate, page 4%7%2. If t"e calculated value of t"e test statistic is greater t"an t"e critical value of t"e teststatistic (!1 25, t"e null "ypot"esis is re.ected.(!rue, moderate, page 4%7%%. In tests of associations, t"e null "ypot"esis is t"at t"ere is no association between t"evariables (6&78.is 9:! related to8..(!rue, difficult, page 4%*%4. Intests of differences, t"enull "ypot"esis is t"at t"ereis adifference(6&78.isdifferent t"an8..(False, difficult, page 4%* %'. 3cross-tabulationis t"e mergingof t"e frequencydistributionof twoor morevariables in a single table to "elp us to understand "ow one variable relates to anot"ervariable.(!rue, moderate, page 4%*%). !"eintroductionofat"irdvariableclarifiest"einitial association(orlac+ofitobserved between two variables and can result in four possibilities.(!rue, difficult, page 44&%7. 2ross-tabulation e#amines associations between variables, not causation.(!rue, moderate, page 44%2&1%*. !"e null "ypot"esis,6&, w"enusingt"ec"i-squarestatistic, is t"at t"ere is noassociation between t"e variables. (!rue, easy, page 444%$. ,"en using t"e c"i-square statistic in cross-tabulation, t"e null "ypot"esis (6& willbere.ectedonlyw"ent"ecalculatedvalueoft"etest statisticisgreatert"ant"ecritical value of t"e c"i-square distribution wit" t"e appropriate degrees of freedom.(!rue, difficult, page 444 4&. !"e c"i-square statistic can be estimated on counts of data or on percentages.(False, difficult, page 44'41. ,"en variables are perfectly associated, t"e p"i coefficient assumes t"e value of 1.(!rue, easy, page 44'42. ,"enmeasuringt"estrengt"ofassociationwit"t"econtingencycoefficient, t"ema#imum value of 1 is ac"ieved w"en t"e variables are perfectly associated.(False, difficult, page 44)4%. 4ambda assumes t"at t"e variables are measured on an ordinal scale.(False, difficult, page 44)44. 3nasymmetrical valueof1"appensw"eneac"independent variablecategoryisassociated wit" a single category of t"e dependent variable.(False, difficult, page 44)4'. ,"en conducting cross-tabulation analysis in practice, if 6& is re.ected, t"e pattern oft"e relations"ips"ouldbe interpretedbycomputinganappropriate statistic (p"icoefficient, contingency, 2ramer;s