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Showing 1 to 6 of 6 for “"SECS-S/02 Statistica per la ricerca sperimentale e tecnologica"”.

  1. Clustering of variables around latent components: an application in consumer science

    … a method based on CLV (Clustering around Latent Variables) for identifying groups of consumers in L-shape data. This kind of datastructure is very common in consumer studies where a panel of consumers is asked to assess the global liking of a certain number of products and then, preference …

    bologna Repository record for Clustering of variables around latent components: an application in consumer science (opens in a new tab)

  2. Knowledge discovery for stochastic models of biological systems

    … by the deployment of several automated experimental frameworks, this discipline has seen a tremendous growth during the last decades. Recently, the focus towards studying biological systems holistically, has lead to biology converging with other disciplines. In particular, computer science …

    trento Repository record for Knowledge discovery for stochastic models of biological systems (opens in a new tab)

  3. Multi-Country Event Study Methods

    … specification or power. Applying the tests that perform best in simulation to merger announcements produces reasonable results.

    bologna Repository record for Multi-Country Event Study Methods (opens in a new tab)

  4. An eye tracking exploration of cognitive reflection in consumer decision-making

    … presented in this thesis are the result of the experiments conducted in the Cognitive and Experimental Economics Laboratory (CEEL) and in the Consumer Neuroscience Laboratory (NCLab) of the Economics and Management Department at the University of Trento. The aim of this research is to study the …

    trento Repository record for An eye tracking exploration of cognitive reflection in consumer decision-making (opens in a new tab)

  5. Novel data-driven analysis methods for real-time fMRI and simultaneous EEG-fMRI neuroimaging

    … Due to the intrinsic difficulties of real-time experiments, in order to fully exploit their potentialities, advanced signal processing algorithms are needed. In particular, since brain activations are free to evolve in an unpredictable way, data-driven algorithms have the potentials of being more …

    trento Repository record for Novel data-driven analysis methods for real-time fMRI and simultaneous EEG-fMRI neuroimaging (opens in a new tab)