Integrating R and Hadoop for Big Data Analysis

Analyzing and working with big data could be very diffi cult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with hundreds or even thousands of computing nodes. Offi cial statistics is increasingly considering big data for deriving new statistics because big data sources could produce more relevant and timely statistics than traditional sources. One of the software tools successfully and wide spread used for storage and processing of big data sets on clusters of commodity hardware is Hadoop. Hadoop framework contains libraries, a distributed fi le-system (HDFS), a resource-management platform and implements a version of the MapReduce programming model for large scale data processing. In this paper we investigate the possibilities of integrating Hadoop with R which is a popular software used for statistical computing and data visualization. We present three ways of integrating them: R with Streaming, Rhipe and RHadoop and we emphasize the advantages and disadvantages of each solution.Comment: Romanian Statistical Review no. 2 / 201

A logit model for the estimation of the educational level influence on unemployment in Romania

Education is one of the main determinants of the unemployment level in all EU countries. In this paper we used a logit model to estimate the effect of the educational level on the unemployment in Romania using data recorded at the Population and Housing Census 2011. Besides the educational level we also used other socio-demographic variables recorded at the Census like gender, marital status, residential area. Data processing was achieved using R software system and since the data set used for model estimation was very large we used special techniques suited for big data processing. The results showed that the lowest odds ratio to be unemployed was recorded for population with tertiary education which is consistent with other studies at international level and with the official statistics data, but our study indicates that tertiary education has a greater impact on unemployment in Romania than in other EU countries

Predicting students’ results in higher education using a neural network

A significant problem in higher education is the poor results of students after admission. Many students leave universities from a variety of reasons: poor background knowledge in the field of study, very low grades and the incapacity of passing an examination, lack of financial resources. Predicting students’ results is an important problem for the management of the universities who want to avoid the phenomenon of early school leaving. We used a neural network to predict the students’ results measured by the grade point average in the first year of study. For this purpose we used a sample of 1000 students from “Nicolae Titulescu” University of Bucharest from the last three graduates’ generations, 800 being used for training the network and 200 for testing the network. The neural network was a multilayer perceptron (MLP) with one input layer, two hidden layers and one output layer and it was trained using a version of the resilient backpropagation algorithm. The input data were the students profile at the time of enrolling at the university including information about the student age, the GPA at high school graduation, the gap between high school graduation and higher education enrolling. After training the network we obtained MSE of about 1.7%. The ability to predict students’ results is of great help for the university management in order to take early action to avoid the phenomenon of leaving education

A logit model for the estimation of the educational level influence on unemployment in Romania

Education is one of the main determinants of the unemployment level in all EU countries. In this paper we used a logit model to estimate the effect of the educational level on the unemployment in Romania using data recorded at the Population and Housing Census 2011. Besides the educational level we also used other socio-demographic variables recorded at the Census like gender, marital status, residential area. Data processing was achieved using R software system and since the data set used for model estimation was very large we used special techniques suited for big data processing. The results showed that the lowest odds ratio to be unemployed was recorded for population with tertiary education which is consistent with other studies at international level and with the official statistics data, but our study indicates that tertiary education has a greater impact on unemployment in Romania than in other EU countries

The return to higher education: evidence from Romania

Education is one of the most important components of the human capital, and an important determinant of the personal income. Estimating the rate of return to education is a main topic of economic research. In this paper we analyzed the rate of return to higher education in Romania using the well-known Mincer equation. Besides the educational level and the number of years of experience on the labor market we also used a series of socio-demographic variables such as gender, civil status, the area of residence. We were interested mainly in calculating the rate of return to higher education, therefore we computed this rate for bachelor, master and doctoral degrees separately. We also investigated the rate of return to higher education on technical, science, economics, law, medicine, and arts fields. Our results showed that the rate of return to higher education has a greater value than most of the developed countries of EU and the field of higher education that brings the highest rate of return is medicin

Internationalization of the higher education in Romania and EU countries

Internationalization of higher education has become a part of the globalization process. In this paper we analyze the internationalization of the higher education in Romania and EU countries, identifying the forms of the internationalization, the main statistical indicators available to measure the process of internationalization. The figures presented in this article show that although Romania took some measures to support the internationalization and the number of foreign students started to increase especially after 2007, it has one of the lowest rates of student mobility among EU countries. The asymmetry ratio of students’ mobility shows that Romania is not currently an attractive country for tertiary education. Only medicine seems to attract foreign students mainly because the tuition fee is much lower than in other European countries. The determinants of the student mobility were investigated through some simple regression models which showed that the GDP per capita and the ratio between the number of students and professors influence the decision to study abroad

Internationalization of the higher education in Romania and EU countries

Internationalization of higher education has become a part of the globalization process. In this paper we analyze the internationalization of the higher education in Romania and EU countries, identifying the forms of the internationalization, the main statistical indicators available to measure the process of internationalization. The figures presented in this article show that although Romania took some measures to support the internationalization and the number of foreign students started to increase especially after 2007, it has one of the lowest rates of student mobility among EU countries. The asymmetry ratio of students’ mobility shows that Romania is not currently an attractive country for tertiary education. Only medicine seems to attract foreign students mainly because the tuition fee is much lower than in other European countries. The determinants of the student mobility were investigated through some simple regression models which showed that the GDP per capita and the ratio between the number of students and professors influence the decision to study abroad