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Goodness of Fit Testing for the Log-logistic Distribution Based on Type I Censored Data
No full textA goodness of fit test procedure is proposed for the log-logistic distribution when the available data are subject to Type I censoring. The proposed test is based on transforming type 1 censored data into complete data from a suitably truncated distribution. A Monte Carlo power study is conducted to evaluate and compare the performance of the proposed method with the existing classical methods. An application based on a real dataset is considered for illustrative purpose
Rice crop growth analysis using Auto Regressive Models
No full textTime series play a vital role in predicting and forecasting different types of agricultural applications with respect to different types of problems among successive units of observations. Time series forecasting techniques are applied in all areas of statistics, and one of the most important applications includes backscatter generating time-series data using advanced forecasting techniques. Agriculture is a major food sector in the world, and it is also a major income source for low-income people. In this paper, we present two aspects of the rice crop growing time series process. The first one is to identify different types of rice crop growing stages for backscatter datasets, and the second is to make a mathematical time series model for the generation of different data sets. The different operator techniques (DOT) method was introduced to identify different types of rice crop growing stages in a season. We proposed the DOT method for identification of different phenological stages for a short-term crop and adopted first and second-order auto-regressive models for prediction and forecasting of the generating backscatter time series observations. The measures of the quality fit are mean absolute percent error (MAPE), mean percent error (MPE), and mean absolute error (MAE)
Recurrence Relations for Moment Generating Function Based on Progressive First Failure Censoring from Generalized Pareto Distribution and Characterization
No full textIn this article, we establish recurrence relations (RR) for single and product moment generating function (MGF) based on based on progressive first failure censoring (PFFC) for generalized Pareto distribution (GPD). Characterization for GPD using RR of single and product MGF of PFFC are also obtained. Further, the results are specialized to the progressively type-II right censored (PTIIRCOS).
Confronting Partial Knowledge Through a Pedagogy of Discomfort: Notes on Anti-Oppressive Teaching
No full textWrestling with issues of racism and colonization in the classroom requires significant nuance from dominantly positioned educators. In this article, we weave together a narrative unpacking of an uncomfortable experience in a graduate level class with an exploration of relevant theoretical literature. Our reflection on practice takes up the possibilities for anti-oppressive education to engage with the partial knowledge of educators and students. Ultimately, engaging in a pedagogy of discomfort is necessary to unsettle dominantly positioned educators and students and enable a move towards bearing witness to the unequal realities of Canadian society. In order to begin to enter more deeply into relationships of accountability between non-Indigenous and Indigenous peoples, teaching moments such as these are inevitable, if not required.
Keywords: anti-oppressive education, discomfort, colonialism, partial knowledge, Indigenous futurit
A Review of Relationships With Families in Early Childhood Education and Care: Beyond Instrumentalization in International Contexts of Diversity and Social Inequality
No full textA Review of Relationships with Families in Early Childhood Education and Care: Beyond Instrumentalization in International Contexts of Diversity and Social Inequality edited by Joanne Lehrer, Fay Hadley, Katrien Van Laere, & Elizabeth Rous
A new modified Bayesian method for measurement uncertainty analysis and the unification of frequentist and Bayesian inference
No full textThis paper proposes a new modification of the traditional Bayesian method for measurement uncertainty analysis. The new modified Bayesian method is derived from the law of aggregation of information (LAI) and the rule of transformation between the frequentist view and Bayesian view. It can also be derived from the original Bayes Theorem in continuous form. We focus on a problem that is often encountered in measurement science: a measurement gives a series of observations. We consider two cases: (1) there is no genuine prior information about the measurand, so the uncertainty evaluation is purely Type A, and (2) prior information is available and is represented by a normal distribution. The traditional Bayesian method (also known as the reformulated Bayes Theorem) fails to provide a valid estimate of standard uncertainty in either case. The new modified Bayesian method provides the same solutions to these two cases as its frequentist counterparts. The differences between the new modified Bayesian method and the traditional Bayesian method are discussed. This paper reveals that the traditional Bayesian method is not a self-consistent operation, so it may lead to incorrect inferences in some cases, such as the two cases considered. In the light of the frequentist-Bayesian transformation rule and the law of aggregation of information (LAI), the frequentist and Bayesian inference are virtually equivalent, so they can be unified, at least in measurement uncertainty analysis. The unification is of considerable interest because it may resolve the long-standing debate between frequentists and Bayesians. The unification may also lead to an indisputable, uniform revision of the GUM (Evaluation of measurement data - Guide to the expression of uncertainty in measurement (JCGM 2008))
A Review of Tools for Teaching in an Educationally Mobile World by Jude Carroll
No full textA Review of Tools for Teaching in an Educationally Mobile World by Jude Carrol
Counter-Storytelling: A Form of Resistance and Tool to Reimagine More Inclusive Early Childhood Education Spaces
No full textIn this essay, I reflect on my lived experiences as a girl child growing up in my home country of Botswana, and also as a mother in a foreign country, Canada. I am experimenting with my personal essay and making connections with academic articles that will help me understand my behaviors, attitudes, and responses to challenging situations that seemed unfair and unjust. I believe sharing my experiences not only gives me a platform to reflect, but also renders an opportunity to unearth hidden ideologies that perpetuate dominant discourses that continue to undesirably affect early childhood education. Sharing the unfortunate events for me brings healing and comfort. My essay is guided by critical race theory that provokes and challenges the normalized practices in education that continue to marginalize the minority community. Also, my inspiration for this piece was drawn from Wallace and Lewis’s (2020) book, which described humans as narrative creatures who need stories/narratives to make sense of the world around them. The essay unpacks and discusses four critical questions, at the same time, offering acts of resistance and refusal by applying counter-storytelling methodology.
Keywords: counter-storytelling, critical race theory, lived experiences, racialized minorities, early childhood education, acts of resistance and refusa
