The following are the conclusions of the analyses.

This report is an analysis from the data collected from my imported Mexican beer survey which asked respondents to answer various questions about three different brands of Mexican beer: Corona, Dos Equis, and Negra Modelo. The data includes the respondents' opinions and feelings about the brands before and after reviewing an ad for each beer. One of the main focuses in this report is measuring the Brand Index Score and the Advertisement Index Score for each beer.

 After viewing the ads 7 respondents opinion of Dos Equis was heightened while 3.1 respondents' opinions of Dos Equis was lowered. Table 2 shows the results of an Independent Two Tailed t-test was statistically significant between the Dos Equis Advertisement Index Score respondents who moved up and those who moved down. This means that in 85 samples out of 100 samples drawn from the population as this sample, it would be expected that the difference between the mean Advertising Index Score of the respondents who's opinion was raised and those who were lowered would appear about the same as it did in this test.

The Pearson Correlation would be expected that the correlation between the Brand Index Scores of Corona and Dos Equis would appear about the same as they do here. Which means that this could be projected onto the population.

Purchase intention for Dos equis was not related to being female.

This report is an analysis from the data collected from my imported Mexican beer survey which asked respondents to answer various questions about three different brands of Mexican beer: Corona, Dos Equis, and Negra Modelo. The data includes the respondents' opinions and feelings about the brands before and after reviewing an ad for each beer.

In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that the ten brand attitude Likert statements about Corona account for about 24.5% of the variance in the population's change scores for this brand. Because the F-Ratio is statistically significant, the results can be projected onto the population. There were, however, only two statements that had a statistically significant impact: “Corona has a bad aftertaste” & “Corona is a cool/trendy beer.” In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that these three coefficients would be about what they are here.

 In this sample, the ten brand attitude Likert statements about Dos Equis account for about 17.6% of the variance in the respondents' change scores for this brand. Because the F-Ratio is not statistically significant, the results can not be projected onto the population. There was only one statement that was statistically significant: “Dos Equis is for people who know a lot about beer.” In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that this coefficient would be about what it is here.

In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that the ten brand attitude Likert statements about Negra Modelo account for about 31.0% of the variance in the population's change scores for this brand. Because the F-Ratio is statistically significant, the results can be projected onto the population. There were, however, five statements that had a statistically significant impact: “Negra Modelo is a good beer.” “Negra Modelo tastes good” “Negra Modelo is a high end beer” “Negra Modelo has a bad aftertaste” & “Negra Modelo is a cool/trendy beer.” In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that these five coefficients would be about what they are here.

This report is an analysis from the data collected from my imported Mexican beer survey which asked respondents to answer various questions about three different brands of Mexican beer: Corona, Dos Equis, and Negra Modelo. The data includes the respondents' opinions and feelings about the brands before and after reviewing an ad for each beer. Multiple Discriminant Analysis was performed on the responses about Negra Modelo and whether the up movers and down movers were classified correctly.

The sample was drawn from a total of 27 respondents: 10 Up-movers and 17 Down-movers. “Negra Modelo is a good beer”, “Negra Modelo Tastes Good”, “Negra Modelo is a high-end beer” and “Negra Modelo has a bad aftertaste” seem to be the most important factors in determining the movement of the respondents' opinions.

Wilkes Lambda is not statistically significant. Therefore, we can not be certain if 85 samples out of 100 samples drawn from the same population as this sample, the difference in the group centroids of the Up-movers and the Down-movers would be what it is here. The group centroids can not be projected onto the population.

Twenty-three out of 27 respondents fell into the predicted membership groups, thus creating 85.2% of the original grouped cases being correctly classified. 85.2% is a pretty good classification accuracy. The original grouped cases are correctly classified and are statistically significant. In 85 out of 100 samples drawn from the same population as this sample, it would be expected that the percentage of cases correctly classified as Up-movers and Down-movers would be about what it is here.

This report is an analysis from the data collected from my imported Mexican beer survey which asked respondents to answer various questions about three different brands of Mexican beer: Corona, Dos Equis, and Negra Modelo. The data includes the respondents' opinions and feelings about the brands before and after reviewing an ad for each beer. Both the ANOVA and MANOVA analyses were performed on the Corona up-movers, down-movers and non-movers and the gender of the respondents.

In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that the difference in the mean Likert scores of “Corona Has a Bad Aftertaste” between the Up-Movers, Down-Movers, and Non-Movers groups would be about what it is here. The results of this analysis can be projected onto the population, unlike the comparison between genders or the comparison between the movers and gender.

In 85 samples out of 100 samples drawn from the same population as this sample, it would be expected that the results are what they are here for the multivariate tests run on the ten Likert questions for Corona along with the gender of the respondent and the gender of the respondent with the movers group. These two tests can be projected onto the population; unlike the multivariate test with the ten Likert questions for corona with the movers group alone. We would not necessarily expect the same result for this test.

This report is an analysis from the data collected from my imported Mexican beer survey which asked respondents to answer various questions about three different brands of Mexican beer: Corona, Dos Equis, and Negra Modelo. The data includes the respondents' answers to Likert Scaled questions about each brand. Factor analysis was performed all three brands of imported Mexican beer.

For Corona, there are 4 factors that can account for 75.5% of the variance. Dos Equis has three factors which account for 71.4% of the variance. Finally, Negra Modelo has two factors which account for 60.9% of the variance.

The results of this paired t-test demonstrated hat in 85 samples out of 100 samples taken from the same population as this sample, the mean attitude scores comparing Negra Modelo to both Corona and Dos Equis would be about what they are here and could be projected onto the population. The brand attitudes comparing Corona with Dos Equis, however, could not be projected onto the population.

This report is an analysis from the data collected from my imported Mexican beer survey which asked respondents to answer various questions about three different brands of Mexican beer: Corona, Dos Equis, and Negra Modelo. The data includes the respondents' answers to Likert Scaled questions about Corona. Cluster analysis was performed all three brands of imported Mexican beer to determine which brand was the best to examine further.

 There are two evenly distributed clusters in Corona determined by answers respondents gave to the Likert questions asked in the questionnaire. The only question that seems to have not been a factor in clustering the respondents is “Corona is too expensive for me.” In 85 samples out of 100 samples, drawn from the same population as this sample, the respondents answers for the Likert questions would appear in one of two clusters similar to what is shown here. This result can be projected onto the population.

In 85 samples out of 100 samples, drawn from the same population as this sample, the cross-tabulation for Corona would be about what it is here. This result can be projected onto the population.