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A Study of Agenda-Setting Theory in Presidential Debates in Mexico’s 2000 Presidential Campaign
Unformatted Document Text:  26 of this research. The panel study and the content analysis showed a considerable correspondence between issues important for the public and issues covered by television. For Hypothesis 3 inferential statistics show a weak positive relationship between the public’s issue agenda and the media issue agenda. Since the sample size is small for hypothesis 3 (N = 8), the use of inferential statistics alone will likely lead to a Type 2 error: concluding the null hypothesis is true when the null hypothesis is actually false. This could happen when the 0.05 alpha level commonly known as the 95 percent decision rule is used to accept or reject a hypothesis. Under the 95 percent decision rule this hypothesis is disconfirmed. However, inferential statistics show a weak linear positive relationship between those variables that is worthwhile to report. The Pearson correlation coefficient between news coverage on issues and the public’s interest on those issues was + .41 (P = .16) N=8 in February. The relationship between those variables was still positive in late April, although not statistically significant under the 95 percent rule: r = +.41 (P = .16) N=8. In June (third stage of the panel study) this relationship was still positive, but not statistically significant under the 95%: r = + .45 (P = .13) N=8. Figure 4 shows the relationship between news coverage on issues and the public interest on those issues (with values from February, April and June for the public’s agenda). This showed a positive, linear relationship whose alpha value was: r = .42 (P = .15) N=8. Small samples are prone to present Type 2 error. Lowering the decision rule to 90-percent in samples of less than 100 cases analyzed would lower also de possibility of Type 2 error (see Schneider & Darcy, 1984). In this case, the level of significance between issues coverage by the media, and issues regarded as important by the public was 89 percent using non- parametric statistical measures; and 84 percent using Pearson correlation coefficient.

Authors: Mercado, Antonieta., Hellweg, Susan., Dozier, David. and Hofstetter, C..
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26
of this research. The panel study and the content analysis
showed a considerable correspondence between issues important
for the public and issues covered by television. For
Hypothesis 3 inferential statistics show a weak positive
relationship between the public’s issue agenda and the media
issue agenda. Since the sample size is small for hypothesis 3
(N = 8), the use of inferential statistics alone will likely
lead to a Type 2 error: concluding the null hypothesis is true
when the null hypothesis is actually false. This could happen
when the 0.05 alpha level commonly known as the 95 percent
decision rule is used to accept or reject a hypothesis. Under
the 95 percent decision rule this hypothesis is disconfirmed.
However, inferential statistics show a weak linear positive
relationship between those variables that is worthwhile to
report. The Pearson correlation coefficient between news
coverage on issues and the public’s interest on those issues
was + .41 (P = .16) N=8 in February. The relationship between
those variables was still positive in late April, although not
statistically significant under the 95 percent rule: r = +.41
(P = .16) N=8. In June (third stage of the panel study) this
relationship was still positive, but not statistically
significant under the 95%: r = + .45 (P = .13) N=8. Figure 4
shows the relationship between news coverage on issues and the
public interest on those issues (with values from February,
April and June for the public’s agenda). This showed a
positive, linear relationship whose alpha value was: r = .42
(P = .15) N=8.
Small samples are prone to present Type 2 error. Lowering
the decision rule to 90-percent in samples of less than 100
cases analyzed would lower also de possibility of Type 2 error
(see Schneider & Darcy, 1984). In this case, the level of
significance between issues coverage by the media, and issues
regarded as important by the public was 89 percent using non-
parametric statistical measures; and 84 percent using Pearson
correlation coefficient.


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