The data collected was analysed in reference to five major variables: age, income level, employment status, education and gender. By separating the survey results into these categories researchers determined how different demographics differed in their labelling perception and in their expectations. Because of the simple form of the questions put to survey-takers, the analysis of results was made fundamentally simple to understand and given the results of the data collection, it would have been easy for most individuals to form their own fact-based conclusions. The analysis is very forthright in its categorisation and it is easy to understand why the researchers chose to divide their information up in this way.
References made to the 7-point Likert scale, ANOVA and Levene’ s homogeneity assumption are not properly explained, however, so it is difficult for the reader to grasp certain details of the analysis. ResultsDespite a basic differentiation between the scientific methods of analysis utilized in this study and the capabilities of the average reader, the published results are simple and easy to grasp. Findings are published both in paragraph form and in graphs.
Based on the five categorisations of the data it was found that age makes little relative difference to the percentage of consumers who are satisfied or dissatisfied with environmental labelling; no differences were marked in terms of gender; income level, employment status and education levels all had a varying effect on the perception of environmental labels and the attitudes concerning any sort of product labelling. While the results published in paragraph form were very simple and to the point, the graphs provided as support for the researchers’ conclusions were created using complex mathematics which an average person would not be able to interpret.
Where the graphs might have been modified to encompass simple percentages for each category and piece of information, they instead rely on a high mathematics comprehension in their readers.
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