3 resultados para Estatística na análise sensorial

em Repositorio Institucional da UFLA (RIUFLA)


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The consumption of snack bars is based especially on the demand for practical and nutritious food. Coffee is highlighted for being appreciated and consumed worldwide, presenting elevated antioxidant activity, in addition to peculiar sensorial attributes. Therefore, it has great potential for use in many formulations. However, the success in the acceptance of a new product also derives from adequate marketing strategies. In this context, the present study aimed at evaluating the feasibility of introducing to the market a snack bar added with coffee, by means of sensorial acceptance and purchase intent of the consumers, in addition to identifying the best concept and the possible market segments. This work was a qualitative, by means of a focus group (content analysis), and quantitative research, by means of sensorial analysis and structures questionnaires (descriptive – frequency distribution, arithmetic mean, crosstabs and t test – and multivariate – cluster and discriminate analysis - statistical techniques). With the results, we showed that the main aspects considered by the consumers regarding the snack bar added with coffee. According to the qualitative evaluation, the consumer prefers packaging with matte colors ranging in the tones related to the coffee grain. The analysis of the quantitative data allows us to infer that the evaluations of the product regarding overall impression, purchase intent, preference and expectation before and after consuming the product are better for packaging containing the information “special coffee flavor – 100% arabic”. Regarding market segment, it was possible to conclude that, of the three extracted groups, the group of “healthy and conscious consumers” was the segment with higher potential for exploitation regarding purchase and consumption of the snack bar added with coffee.

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The multivariate t models are symmetric and with heavier tail than the normal distribution, important feature in financial data. In this theses is presented the Bayesian estimation of a dynamic factor model, where the factors follow a multivariate autoregressive model, using multivariate t distribution. Since the multivariate t distribution is complex, it was represented in this work as a mix between a multivariate normal distribution and a square root of a chi-square distribution. This method allowed to define the posteriors. The inference on the parameters was made taking a sample of the posterior distribution, through the Gibbs Sampler. The convergence was verified through graphical analysis and the convergence tests Geweke (1992) and Raftery & Lewis (1992a). The method was applied in simulated data and in the indexes of the major stock exchanges in the world.

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Experiments using factorial arrangement of treatments are rather common and useful in agricultural research. The main advantage is the possibility of testing many hypotheses, allowing broader conclusions over different factors, studied simultaneously. Factorial arrangements are used to compare levels of each factor (main effects), and also to verify if the differences among levels of a given factor are dependent on the levels of the other factors (interacions). In the analysis of data from factorial experiments, difficulty is increased when additional treatments are included. Inclusion of one or more additional treatments is a quite common practice, since such treatments are usually taken as reference or standard for evaluation and comparasion of the remaimng treatments, or aiming complementary information. This increase of difficulty is however low, compared to the advantages. As in literature there are few references about the statistical analysis of factorial experiments with additonal treatments, and given straightforward use in experimentation, the objective of this work was the presentation of approach for the use of factorial experiments with additonal treatments trough the analysis of some examples using the SAS® software, with the corresponding theoretical development, obtaining the system of normal equations, estimators of the parameters and variance of contrasts among two treatment means. It is suggested that additional treatments should be used with caution. The analysis of variance of such kind of experiment was presented using matrix notation.