O ensino da estatística nos anos finais do ensino fundamental

Result of a professional master course of research work in Teaching Science and Technology of the Federal Technological University of Paraná (UTFPR), this work aims to provide the mathematics teacher of the final years of elementary school a teaching sequence (SE) which includes basic content of Statistics provided in the curriculum. In this book a text about the importance of the teaching of statistics is presented, as well as issues related to literacy skills, reasoning and statistical thinking. The development of the SE was designed considering the presuppositions of contextualization, being structured in six steps. We chose to develop a work with the basic contents of Statistics through real data collected with the participation of students, within a context for them significant. This option was due to be possible to develop with the students situations such as: raising hypotheses , communication situations experienced by different graphs and tables , results of discussion and understanding of the significance of the results obtained by means of statistical calculations. Thus, it is believed to be possible to contribute to the development of statistical skills by the students.

Estatística com projetos: uma alternativa de ensino e aprendizagem

This work presents the use of projects as an alternative for teaching statistics, for that it was elaborated a Project that involves the educational socioeconomic reality from the families of the students and built a link between the reality and the scholastic knowledge. This project was applied in Sesi School - Pato Branco between the months of August to September 2014 with 25 students from the 1o and 2o grades from High School. To work the statistics concepts a questionnaire was applied for the parents of the students of the Project´s, they answer it and through these answers the students made frequency tables and graphs, besides measure calculations on measures of central tendency and dispersion measure. All of the construction were realized manually and in the Excel spreadsheet and some of them were chosen to be in this work to with the purpose of showing the hits and the mistakes done. The students worked in groups of 5 students, except in the last class when it was done a test referring to the contents taught in the classroom and a questionnaire for them to evaluate the project´s application. The results show that the teaching of Statistics trough projects motivate the students interest, stimulating the statistical reasoning, in addition made the students know a Math that was different from the one they have already known, with a lot of calculation but with no final objective.

Estatística das aplicações de métodos multicritério nas áreas da engenharia de produção

Currently, the decision analysis in production processes involves a level of detail, in which the problem is subdivided to analyze it in terms of different and conflicting points of view. The multi-criteria analysis has been an important tool that helps assertive decisions related to the production process. This process of analysis has been incorporated into various areas of production engineering, by applying multi-criteria methods in solving the problems of the productive sector. This research presents a statistical study on the use of multi-criteria methods in the areas of Production Engineering, where 935 papers were filtered from 20.663 publications in scientific journals, considering a level of the publication quality based on the impact factor published by the JCR between 2010 and 2015. In this work, the descriptive statistics is used to represent some information and statistical analysis on the volume of applications methods. Relevant results were found with respect to the "amount of advanced methods that are being applied and in which areas related to Production Engineering." This information may provide support to researchers when preparing a multi-criteria application, whereupon it will be possible to check in which issues and how often the other authors have used multi-criteria methods.

Detecção de região saliente em imagens usando dissimilaridade de cor e amostragem por pixeis aleatórios

The purpose of this work is to demonstrate and to assess a simple algorithm for automatic estimation of the most salient region in an image, that have possible application in computer vision. The algorithm uses the connection between color dissimilarities in the image and the image’s most salient region. The algorithm also avoids using image priors. Pixel dissimilarity is an informal function of the distance of a specific pixel’s color to other pixels’ colors in an image. We examine the relation between pixel color dissimilarity and salient region detection on the MSRA1K image dataset. We propose a simple algorithm for salient region detection through random pixel color dissimilarity. We define dissimilarity by accumulating the distance between each pixel and a sample of n other random pixels, in the CIELAB color space. An important result is that random dissimilarity between each pixel and just another pixel (n = 1) is enough to create adequate saliency maps when combined with median filter, with competitive average performance if compared with other related methods in the saliency detection research field. The assessment was performed by means of precision-recall curves. This idea is inspired on the human attention mechanism that is able to choose few specific regions to focus on, a biological system that the computer vision community aims to emulate. We also review some of the history on this topic of selective attention.