A copula model to analyze minimum admission scores

Fernández, Manuel; González‐López, V. A.

doi:10.1063/1.4825799

Cited by 9 publications

(4 citation statements)

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“…More precisely, if we have observed high failure rates, we see how they affect the probability of high rates of students below the baseline and how those high failure rates impact in the mean value of rates of students below the baseline. The ACS family has already shown a good performance in applications in the area, see for example [2] and [3]. It is also compatible with our data which, as we shall see, shows very low correlation.…”

Section: Introductionsupporting

confidence: 91%

“…To understand the relation between (i) and (ii) we inspect the conditional dependence in different upper tail regions of [0,1] 2 of the marginal ranks of (i) and (ii) scaled to [0,1]. We can see the representation of the behavior of tail events given by equation (2) in Figure 5. We see that in 2013 the behavior of the conditional probability is the expected, since, the higher threshold in rate of fail, the higher the probability of classification under the basic level be superior to 90%.…”

Section: Resultsmentioning

confidence: 99%

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A copula-based consistency analysis of education indicators

Cunha

Fernández²,

Garćıa

et al. 2019

4open

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In this paper we investigate the consistency of quality indicators of the Brazilian public educational system. According to the newspaper Estado de São Paulo – Brazil, of January 18, 2017, only 7.3% of students in the third year of high school have an adequate level of mathematics, this shows the relevance of the evaluation and assessment of the Brazilian educational system. In this paper we explore the dependence between two indicators: (i) mean value between the proportions (in two subjects: Portuguese and Mathematics) of students under the basic level (SARESP classification) and (ii) rate of fails, during the years 2013, 2014 and 2015. (i) and (ii) are bases to define the educational quality of public schools for the population of young people, between 14 and 17 years old. This inspection is carried out through the Bayesian estimation of the parameters of the Asymmetric Cubic Sections (ACS) copula. We show that the dependence profile, year after year, behaves in a very unstable way, although during those years there were no substantial changes which justify such instability. Through the copula we compute conditional probabilities of tail events. We verify that an inversion occurred in the concordance/discordance between (i) and (ii). We compute the probability of (i) assuming high values, conditioned to a threshold in (ii). In 2013, as the threshold in (ii) increases the probability increases (concordance), in 2014 the threshold in (ii) is almost irrelevant to the probability and in 2015, as the threshold in (ii) increases the probability decreases (discordance). The inspection of the tail dependence allows to expose some kind of manipulation, in view of for instance, the maintenance of a global index índice de desenvolvimento da educação de São Paulo (IDESP) used to classify the educational institutions.

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Section: Introductionsupporting

confidence: 91%

Section: Resultsmentioning

confidence: 99%

A copula-based consistency analysis of education indicators

Cunha

Fernández²,

Garćıa

et al. 2019

4open

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show abstract

“…The copula density c ( u , v ∣ θ ) is obtained as usual from the distribution function. For information related to applications of those models, refer to and references therein for financial examples, for hydrological problems, for educational research, for classifying texts in different languages, and for application in tail dependence.…”

Section: Introductionmentioning

confidence: 99%

A note on conjugate distributions for copulas

Fernández

González‐López

Rifo

2014

Math Methods in App Sciences

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A family of conjugated distributions for a given type of copulas is defined in this paper. Those copulas can be written as a mixture of d-dimensional parameter exponential functions. The generalized Farlie-Gumbel-Morgenstern copula is an example of this representation. This family is used to illustrate the estimation technique with real data. Also, the applicability of Bayesian predictive approach is shown in an education policy issue by defining goals for the number of students per class that leads to improve their performance at school.

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“…As example of this matter can be listed the financial portfolio management and the minimum admission score establishment. This last case was explored in Fernández and González-López (2013) [2]. The goal of this paper is to find analytical expressions of boundary functions for the conditional expectations, because those findings can increase the information given to decision makers.…”

Section: Introductionmentioning

confidence: 97%