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A state is considering legislation to establish a fifteen day waiting period for the purchase of hand guns.A sample of 392 citizens has been questioned regarding their opinions.Is there a relationship between sex and support for this law? Calculate percentages for the table below and write a sentence or two assessing the strength and pattern or direction of the relationship.  Sex  Male  Female  Support  For 113145258 Against 7856134191201392\begin{array}{|l|l|l|l|l|}\hline & & \text { Sex } & & \\\hline & & \text { Male } & \text { Female } & \\\hline \text { Support } & \text { For } & 113 & 145 & 258 \\\hline & \text { Against } & 78 & 56 & 134 \\\hline & & 191 & 201 & 392 \\\hline & & & & \\\end{array}

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In a bivariate table,the categories of the dependent variable are placed in the


A) rows.
B) columns.
C) marginals.
D) far right-hand column.

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If the conditional distributions of Y change,the variables are


A) independent.
B) not associated.
C) significantly related.
D) associateD.

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If the conditional distributions of Y do not change across the categories of X,any measure of association and the maximum difference would be


A) 1.00.
B) 0.00.
C) 0.10.
D) 100.

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In the case of a perfect association,predictions from one variable to another can be made


A) only if variables are measured at the nominal level.
B) when at least one variable is ordinal.
C) without error.
D) only if the relationship is positive.

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If there is a perfect association between sexual attraction and accelerated heartbeat,then


A) sex is unhealthy.
B) there is strong evidence that sexual attraction and accelerated heartbeat are causally related.
C) if there is no sexual attraction,the heartbeat never accelerates.
D) whenever the heartbeat accelerates,people become sexually attractive.

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A researcher tested the relationship between education and support for assisted suicide ("death with dignity") and found that support increased as education increased and that the maximum difference was 45.This relationship is


A) strong negative.
B) weak positive.
C) strong positive.
D) significant but not important.

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C

To prove that one variable causes another,we use


A) measures of association.
B) tests of significance.
C) ANOVA.
D) none of the above: neither measures of association or tests of significance can prove causal relationships

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With the independent variable in the columns,the "maximum difference" is the largest difference


A) in column percents in any row.
B) in row percents in any column.
C) between the marginals.
D) between any two cell frequencies.

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If the distribution of the scores of one variable changes across the categories of another variable,the variables


A) are associated to some extent.
B) are related in a way that is statistically significant.
C) have a cause and effect relationship.
D) are perfectly associateD.

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Is there an association between support for the legalization of marijuana and age? Calculate percentages for the table below and write a sentence or two assessing the strength and pattern or direction of the relationship.  Age  Less than 35355050 andOlder  Suppat  In Favor: 36231776 Neutral 20171653 Opposed 10183664665869193\begin{array}{|l|l|l|l|l|l|}\hline &&\text { Age }\\\hline && \text { Less than } 35 & 35-50 & 50 \text { andOlder } & \\\hline \text { Suppat }& \text { In Favor: } & 36 & 23 & 17 & 76 \\\hline& \text { Neutral } & 20 & 17 & 16 & 53 \\\hline &\text { Opposed } & 10 & 18 & 36 & 64 \\\hline && 66 & 58 & 69 & 193 \\\hline\end{array}

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One way to detect an association between variables is the chi square statistic.Variables are associated if obtained chi square is


A) greater than zero.
B) less than zero.
C) greater than 10.
D) greater than 100.

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A researcher finds that males are much more supportive of cohabitation than females.The maximum difference is 25.This is a ____ relationship.


A) moderate
B) negative
C) positive
D) strong

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Tests of significance tell us if our results are non-random.To investigate the strength and direction of relationships,we must use


A) Chi square tests.
B) ANOVA.
C) percentages.
D) measures of association.

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The table below displays the effects of hair color on political ideology for a sample.How should this relationship be characterized?  Hair Color  Blonde  Not Blonde  Libera 60%60% Conservative 40%40%100%100%\begin{array}{|l|l|l|}\hline & \text { Hair Color } & \\\hline & \text { Blonde } & \text { Not Blonde } \\\hline \text { Libera } & 60 \% & 60 \% \\\hline \text { Conservative } & 40 \% & 40 \% \\\hline & 100 \% & 100 \% \\\hline & & \\\hline\end{array}


A) This is a strong,positive relationship.
B) This is a strong,negative relationship.
C) There is no relationship between these variables.
D) This is a perfect relationship.

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Measures of association provide the researcher with information that


A) indicates the strength of a relationship between variables.
B) assists him or her in making predictions from one variable to another.
C) facilitates his or her understanding of causal relationships between variables.
D) all of the above

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A maximum difference greater than 30 would usually be accompanied by a ____ measure of association.


A) weak
B) moderate
C) negative
D) strong

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The distribution of scores on the dependent variable for a specific category of the independent variable is called


A) associated categories.
B) the distribution correlation.
C) the conditional distribution of Y.
D) the marginal response category.

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C

If there is an association between two variables,


A) the scores of the cases are approximately equal.
B) the distributions of the scores approach normality.
C) all of the scores are in the same row in the bivariate table.
D) the conditional distributions of Y change.

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The closer the value of a measure of association is to one,


A) the stronger the relationship.
B) the more evenly the scores are distributed.
C) the weaker the relationship.
D) the more certain we are that the samples are representative.

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A

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