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Young People, Media Use, and Voter Turnout: An Analysis of the 2000 National Election Study
Unformatted Document Text:  Young Voters and Media Use 14 watched television news were less likely to cast a ballot and those who paid more attention to campaign news were more likely to vote. Table 2 shows how correctly this model, as a whole, classified those young people who voted and those who did not. Canonical correlation value (.618) shows that this model, as a whole, can explain 38 percent of variance in young voter turnout, same as the R 2 value in the final regression (regression 4). Wilks’ Lambda also shows that this whole set is discriminating (classifying) those who do vote from those who do not with a strong statistical significance (p<.0001). Among all the predictors, political efficacy (function coefficient = -.47) was the strongest predictor and campaign interest (function coefficient = .37) was the second strongest predictor. Among those predictors found to be significant in regression analysis, television news exposure (function coefficient = .25) was the weakest predictor. Overall classification results show that this whole set correctly classified 79.3 percent of original grouped cases. This model correctly classified 87 percent of those who did vote and 66 percent of those who did not vote. Considering fairly even division between those who voted and those who did not 20 , this model appears to be successful in discriminating both groups. Based on what was found in discriminant analysis, it can be argued that young people who feel less cynical and less unconfident about politics, are more interested in politics, do not identify themselves as strong republicans, do not watch television news frequently, and pay good attention to campaign-related news on television are more likely to vote on Election Day. 20 Among 493 young voters interviewed in the 2000 National Election Study, 256 people reported that they voted (52%) and 237 people reported that they did not vote (48%).

Authors: Kim, Eunsong.
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Young Voters and Media Use
14
watched television news were less likely to cast a ballot and those who paid more
attention to campaign news were more likely to vote.
Table 2 shows how correctly this model, as a whole, classified those young
people who voted and those who did not. Canonical correlation value (.618) shows that
this model, as a whole, can explain 38 percent of variance in young voter turnout, same
as the R
2
value in the
final regression (regression 4). Wilks’ Lambda also shows that this
whole set is discriminating (classifying) those who do vote from those who do not with
a strong statistical significance (p<.0001). Among all the predictors, political efficacy
(function coefficient = -.47) was the strongest predictor and campaign interest (function
coefficient = .37) was the second strongest predictor. Among those predictors found to
be significant in regression analysis, television news exposure (function coefficient
= .25) was the weakest predictor. Overall classification results show that this whole set
correctly classified 79.3 percent of original grouped cases. This model correctly
classified 87 percent of those who did vote and 66 percent of those who did not vote.
Considering fairly even division between those who voted and those who did not
20
, this
model appears to be successful in discriminating both groups. Based on what was found
in discriminant analysis, it can be argued that young people who feel less cynical and
less unconfident about politics, are more interested in politics, do not identify
themselves as strong republicans, do not watch television news frequently, and pay
good attention to campaign-related news on television are more likely to vote on
Election Day.
20
Among 493 young voters interviewed in the 2000 National Election Study, 256 people
reported that they voted (52%) and 237 people reported that they did not vote (48%).


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