On association in regression: the coefficient of determination revisited

Universal coefficients of determination are investigated which quantify the strength of the relation between a vector of dependent variables Y and a vector of independent covariates X. They are defined as measures of dependence between Y and X through theta(x), with theta(x) parameterizing the conditional distribution of Y given X=x. If theta(x) involves unknown coefficients gamma the definition is conditional on gamma, and in practice gamma, respectively the coefficient of determination has to be estimated. The estimates of quantities we propose generalize R^2 in classical linear regression and are also related to other definitions previously suggested. Our definitions apply to generalized regression models with arbitrary link functions as well as multivariate and nonparametric regression. The definition and use of the proposed coefficients of determination is illustrated for several regression problems with simulated and real data sets

The Influence of Environment to Students’ Motivation and The Effect to Student Achievement Grade Audio Video Department SMK Muh. Kutowinangun Kebumen

This research aims to determine: 1) the influence of school environment to student achievement. 2) the influence of family environment to student achievement. 3) the influence of communities to student achievement. 4) the influence of industrial environments to student achievement. 5) the influences of students’ motivation to student achievement. (6) the influence of school environment, family environment, communities, industrial environments and students’ motivation to student achievement from student XII grade Audio Video department SMK Muh. Kutowinangun Kebumen. This research is an Ex-post facto with quantitative approach. The population is a class XII student of Audio Video department SMK Muh. Kutowinangun Kebumen school year 2011/2012 which amounts to 36 students. Methods of data collection using questionnaires Likert scale models for all variables. The validity of research instruments performed by analysis of the items calculated by the formula Product moment correlation. Reliability of the instrument calculated using Cronbach Alpha. Prior to the first data analysis conducted descriptive analysis and testing requirements analysis including tests of normality, linearity tests, and multicollinearity test. Data analysis techniques are used to test the hypothesis is a technical product moment regression analysis.. The results showed that: (1) there is a positive relationship between school environment (X1) with student achievement (Y) are indicated coefficient R = 0,335. The coefficient of determination (R2) = 0,112. (2) there is a positive relationship between family environment (X2) with student achievement (Y) are indicated coefficient R = 0,578. The coefficient of determination (R2) = 0,334. (3) there is a positive relationship between communities (X3) with student achievement (Y) are indicated coefficient R = 0,485. The coefficient of determination (R2) = 0,235. 4) there is a positive relationship between industrial environments (X4) with student achievement (Y) are indicated coefficient R = 0,367. coefficient of determination (R2) = 0,135. (5) there is a positive relationship between students’ motivation (X5) with student achievement (Y), are indicated coefficient R = 0,658. coefficient of determination (R2) = 0,434. (6) there is a positive relationship between school environment (X1), family environment (X2), between communities (X3), industrial environments (X4) and students’ motivation (X5) together in the readiness of student achievement (Y), are indicated coefficient R = 0,725. coefficient of determination (R2) = 0,526

Statistical Investigation of Connected Structures of Stock Networks in Financial Time Series

In this study, we have investigated factors of determination which can affect the connected structure of a stock network. The representative index for topological properties of a stock network is the number of links with other stocks. We used the multi-factor model, extensively acknowledged in financial literature. In the multi-factor model, common factors act as independent variables while returns of individual stocks act as dependent variables. We calculated the coefficient of determination, which represents the measurement value of the degree in which dependent variables are explained by independent variables. Therefore, we investigated the relationship between the number of links in the stock network and the coefficient of determination in the multi-factor model. We used individual stocks traded on the market indices of Korea, Japan, Canada, Italy and the UK. The results are as follows. We found that the mean coefficient of determination of stocks with a large number of links have higher values than those with a small number of links with other stocks. These results suggest that common factors are significantly deterministic factors to be taken into account when making a stock network. Furthermore, stocks with a large number of links to other stocks can be more affected by common factors.Comment: 11 pages, 2 figure

The Entrepreneurship Readiness of Student XII Grade Department of Audio Video SMK Piri 1 Yogyakarta School Year 2011/2012 Reviewed by Knowledge Entrepreneurship, Family Support, Soft Skills and Learning Achievment.

This research aims to determine:1) the influence of knowledge entrepreneurship to the readiness entrepreneurship. 2) the influence of family support to the readiness entrepreneurship 3) The infulence soft skill to the readiness entrepreneurship 4) the influence of student achievment to the readiness entrepreneurship 5) the influences of knowledge entrepreneurship, family support, soft skills dan student achievment to the readiness entrepreneurship together from student XII grade Audio Video department SMK Piri 1 Yogyakarta school year 2011/2012. This research is an Ex-post facto with quantitative approach. The population is a class XII student of Audio Video department SMK Piri 1 Yogyakarta school year 2011/2012 which amounts to 24 students. Methods of data collection using questionnaires Likert scale models for all variables. The validity of research instruments performed by analysis of the items calculated by the formula Product moment correlation. Reliability of the instrument calculated using Cronbach Alpha. Prior to the first data analysis conducted descriptive analysis and testing requirements analysis including tests of normality, linearity tests, and multicollinearity test. Data analysis techniques are used to test the hypothesis is a technical product moment correlation analysis and multiple regression analysis techniques. The results showed that: (1) there is a positive relationship between entrepreneurial knowledge (X1) with the readiness of student entrepreneurship indicated coefficient R = 0.639. The coefficient of determination (R2) = 0.408 and is shown by the equation Y = 27.099 + 0.877 X1. (2) there is a positive relationship between family support (X2) with the readiness of entrepreneurship students (Y) are indicated coefficient R = 0.644. The coefficient of determination (R2) = 0.415 and is shown by the equation Y = 42.00 + 0.777 X2 . (3) there is a positive relationship between soft skills (X3) with the readiness of entrepreneurship students (Y) are indicated coefficient R = 0.344. The coefficient of determination (R2) = 0.118 and is shown by the equation Y = 20.217 + 0.160 X3. (4) there is a positive relationship between learning achievement (X4) with entrepreneurship student readiness (Y) are indicated coefficient R = 0.237. coefficient of determination (R2) = 0.056 and is shown by the equation Y = 18.889 + 0.188 X4. (5) there is a positive relationship between entrepreneurial knowledge (X1), family support (X2), soft skills (X3) and learning achievement (X4) together on the readiness of entrepreneurship students (Y), which indicated multiple regression coefficient Rx(1,2,3,4) y of 0.921. coefficient of determination (r2) = 0.848 and is shown by the equation Y = 13.402 + 0.746 X1 + 0.471 X2 + 0.122 X3 - 0483X

On the link between the coefficient of determination and polarization

In this paper, taking as starting point the link between polarization and dispersion, we reformulate the measure of polarization of Zhang and Kanbur (2001) using the decomposition of the variance instead of the decomposition of the Theil index. The proposed measure is equivalent to the coefficient of determination of an ANOVA Linear Model, that explains the income of the households as a function of any population characteristic e.g. education, gender, occupation etc. This result provides an alternative way to analyze polarization by household characteristics and at the same time allows us to compare sub-populations via the estimated coefficients of the ANOVA model.Polarization, coefficient of determination, ANOVA model.

Non-invasive estimation of left atrial dominant frequency in atrial fibrillation from different electrode sites: Insight from body surface potential mapping

© 2014, CardioFront LLC. All rights reserved. The dominant driving sources of atrial fibrillation are often found in the left atrium, but the expression of left atrial activation on the body surface is poorly understood. Using body surface potential mapping and simultaneous invasive measurements of left atrial activation our aim was to describe the expression of the left atrial dominant fibrillation frequency across the body surface. 20 patients in atrial fibrillation were studied. The spatial distributions of the dominant atrial fibrillation frequency across anterior and posterior sites on the body surface were quantified. Their relationship with invasive left atrial dominant fibrillation frequency was assessed by linear regression analysis, and the coefficient of determination was calculated for each body surface site. The correlation between intracardiac and body surface dominant frequency was significantly higher with posterior compared with anterior sites (coefficient of determination 67±8% vs 48±2%,

Ambiguities in fit-evaluation for selector models

Abstract: The use of the direct evaluation of the Gaussian Process, using the square exponential function kernel prediction at the given data points is often misleading towards evaluation of the fit, given by the coefficient of determination. The predicted value at the data points when using the Gaussian Process, is almost at all cases equal to the original value. As such, interpretation problems arise when coefficient of determination suggest the model to be a good fit, but visual representations suggest otherwise. We illustrate the difficulties in presenting the coefficient of determination for the Gaussian Process and recommend the use of alternative methods for the evaluation of the predicted value, thus realizing the true function of the coefficient of determination

PENTINGNYA SOSIAL MEDIAL DALAM MENINGKATKAN MINAT BELI DAN KEPUTUSAN PEMBELIAN DI ELYADA CAKE

This study aimed to analyze the influence of social media Instagram and product quality on purchasing decisions through consumer buying interest at Elyada Cake Jakarta. This study uses primary data obtained from questionnaires with purposive sampling method with a sample of 200 respondents consisting of consumers who have purchased Elyada Cake products at least once. The data analysis method used in this research is validity test, reliability test, classical assumption test. While the hypothesis testing includes path analysis, MSI transformation, Sobel test, direct and indirect effect, path coefficient and coefficient of determination (R2). The author uses a quantitative descriptive method, namely by analyzing data using IBM SPSS Statistics 20. The results of the calculation of the coefficient of determination, social media Instagram and product quality on consumer buying interest, the coefficient of determination or R2 produced is 36.8%. Instagram social media, product quality and consumer buying interest in purchasing decisions obtained a coefficient of determination or R2 of 42.2%