scholarly journals التنبؤ بالتحصيل الدراسي لطلاب الجامعة من خلال بعض المتغيرات المعرفية و الديموجرافية باستخدام كل من الانحدار الخطي المتعدد و الانحدار اللوغاريتمي الثنائي = Prediction of Academic Achievement for Students of the University through Some Cognitive and Demographic Variables Using Both Multiple Linear Regression and Logistic Regression Binary

2013 ◽  
Vol 5 (4 P.2) ◽  
pp. 171-265
Author(s):  
سوسن إبراهيم أبو العلا شلبي
Keyword(s):  
Academic Achievement ◽  
Logistic Regression ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Demographic Variables ◽  
The University

scholarly journals Prediction of University Students' Academic Achievement by Linear and Logistic Models

2008 ◽  
Vol 11 (1) ◽  
pp. 275-288 ◽  
Author(s):  
Maria Noel Rodríguez Ayán ◽  
Maria Teresa Coello García
Keyword(s):  
Academic Achievement ◽  
Logistic Regression ◽  
Linear Regression ◽  
University Students ◽  
Goodness Of Fit ◽  
Predictive Power ◽  
Logistic Models ◽  
Demographic Factors ◽  
Academic Progress ◽  
Demographic Variables

University students' academic achievement measured by means of academic progress is modeled through linear and logistic regression, employing prior achievement and demographic factors as predictors. The main aim of the present paper is to compare results yielded by both statistical procedures, in order to identify the most suitable approach in terms of goodness of fit and predictive power. Grades awarded in basic scientific courses and demographic variables were entered into the models at the first step. Two hypotheses are proposed: (a) Grades in basic courses as well as demographic factors are directly related to academic progress, and (b) Logistic regression is more appropriate than linear regression due to its higher predictive power. Results partially confirm the first prediction, as grades are positively related to progress. However, not all demographic factors considered proved to be good predictors. With regard to the second hypothesis, logistic regression was shown to be a better approach than linear regression, yielding more stable estimates with regard to the presence of ill-fitting patterns.

scholarly journals PENGARUH LINGKUNGAN KERJA DAN MOTIVASI KERJA TERHADAP KINERJA KARYAWAN BAGIAN RUMAH TANGGA DAN PERBEKALAN UNIVERSITAS SARJANAWIYATA TAMANSISWA YOGYAKARTA

2020 ◽  
Vol 4 (2) ◽  
pp. 68-76
Author(s):  
Bambang Tri Pamungkas
Keyword(s):  
Linear Regression ◽  
Data Collection ◽  
Multiple Linear Regression ◽  
Work Environment ◽  
Work Motivation ◽  
Employee Performance ◽  
Collection Method ◽  
Significance Level ◽  
Analysis Technique ◽  
The University

 This study aims to determine whether there is a partial influence of work environment and motivation on the performance of Sarjanawiyata Tamansiswa Yogyakarta Household Employees. To find out the influence of work environment and work motivation simultaneously on the performance of Sarjanawiyata Tamansiswa Yogyakarta Household Employees.      The nature of this research is correlational. The variables of this study are the work environment and work motivation and employee performance. The population in this study were all Household Employees at the University of Sarjanawiyata Tamansiswa Yogyakarta with a population of 37, a population of less than 100, so that all populations were sampled by the census method. The data collection method uses a questionnaire. The analysis technique used is multiple linear regression with a significance level of 5%.       The results obtained by the work environment has a positive and significant effect on the performance of employees of the Household Section of the Sarjanawiyata Tamansiswa Yogyakarta University. Work motivation has a positive and significant effect on the performance of employees of the Household Section of the Sarjanawiyata Tamansiswa University in Yogyakarta. Employee performance is influenced by the work environment and work motivation by 29.3%, while the remaining 70.7% is influenced by other factors.

scholarly journals PENGARUH KECERDASAN EMOSIONAL DAN KETERAMPILAN KOMUNIKASI TERHADAP PRESTASI AKADEMIK MAHASISWA PENDIDIKAN BAHASA INGGRIS DI IKIP BUDI UTOMO MALANG

2018 ◽  
Vol 24 (1) ◽  
pp. 1-16
Author(s):  
Enis Fitriani
Keyword(s):  
Academic Achievement ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Communication Skill ◽  
T Test ◽  
Student Academic Achievement ◽  
Test Results ◽  
F Test ◽  
Independent Variable ◽  
Quota Sampling

This study aimed to determine the effect of emotional quotient (EQ) and communication skill(CS) on student academic achievement (AC). This quantitative studyis explanation type using quota sampling and the analysis used classical assumption test and multiple linear regression analysis.The result of t test showed that both independent variableX1 (EQ) and independent variable X2 (CS) had no effect on dependent variable Y (AC) as evidenced by significance value X1=0.185 (e”0.05) and value significance X2=0.398 (e”0.05). F test results showed that there was no effect between independent variable X1 and independent variable X2 to dependent variable Y simultaneously known from F significance value that is equal to 0.410 (e”0.05). The conclusions are: EQ has no effect on academic achievement; communication skill has no effect on academic achievement; and simultaneously EQ and communication skill have no effect on academic achievement.

scholarly journals Islamic Retirement Planning Among Indonesian Bankers

2020 ◽  
Vol 8 (1) ◽  
pp. 25
Author(s):  
Yaser Taufik Syamlan ◽  
Reti Rahma Easti
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Employment Status ◽  
Retirement Planning ◽  
Demographic Variables ◽  
Potential Conflict ◽  
Level Of Education ◽  
Islamic Perspective ◽  
Islamic Bank ◽  
Conventional Bank

<p><em>This study aims to analyze differences in demographic factors towards retirement planning behavior according to Islamic perspective. This research wants to analyze the influence of clarity of purpose, retirement attitude and potential conflict towards retirement planning behavior according to among the Muslim who is working in a conventional bank and the Islamic Bank. The sample used in this study as many as 270 respondents of both conventional &amp; Islamic Banker in Indonesia.   There are two methods that are used in this research which are ANOVA and Multiple Linear Regression. The results identified several demographic variables that were significant such employment status (either working in the conventional bank or Islamic Bank) and income level. Furthermore, some demographic variables do not significant including age, number of dependents and level of education. This research also shows that non-demographic variables such as clarity of purpose, retirement attitudes and potential conflicts affect significantly to influence the behavior of bankers in retirement planning according to Islamic perspective.  In conclusion, the conventional Muslim bankers know that they should manage their retirement according to the Shariah value. However, some of them didn’t believe that the Shariah investment instrument can fulfill their desired retirement goals. </em></p>

scholarly journals Brand new norms for a good old test: Northern Italy normative study of MiniMental State Examination

2022 ◽  
Author(s):  
Giuseppe Foderaro ◽  
Valeria Isella ◽  
Andrea Mazzone ◽  
Elena Biglia ◽  
Marco Di Gangi ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Demographic Variables ◽  
Northern Italy ◽  
Normative Study ◽  
Cognitive Domains ◽  
Medical Disorders ◽  
A Value ◽  
State Examination ◽  
Interference Error

Abstract Aim Mini-Mental State Examination (MMSE) is one of the most used tests for the screening of global cognition in patients with neurological and medical disorders. Norms for the Italian version of the test were published in the 90 s; more recent norms were published in 2020 for Southern Italy only. In the present study, we computed novel adjustment coefficients, equivalent scores and cut-off value for Northern Italy (Lombardia and Veneto) and Italian speaking Switzerland. Methods We recruited 361 healthy young and old (range: 20–95 years) individuals of both sexes (men: 156, women: 205) and from different educational levels (range: 4–22 years). Neuropsychiatric disorders and severe medical conditions were excluded with a questionnaire and cognitive deficits and were ruled out with standardized neuropsychological tests assessing the main cognitive domains. We used a slightly modified version of MMSE: the word ‘fiore’ was replaced with ‘pane’ in verbal recalls to reduce the common interference error ‘casa, cane, gatto’. The effect of socio-demographic features on performance at MMSE was assessed via multiple linear regression, with test raw score as dependent variable and sex, logarithm of 101—age and square root of schooling as predictors. Results Mean raw MMSE score was 28.8 ± 1.7 (range: 23–30). Multiple linear regression showed a significant effect of all socio-demographic variables and reported a value of R2 = 0.26. The new cut off was ≥ 26 /30. Conclusion We provide here updated norms for a putatively more accurate version of Italian MMSE, produced in a Northern population but potentially valid all over Italy.

scholarly journals Using multiple linear regression to disaggregate electricity consumption for cluster-metered academic buildings

2021 ◽  
Author(s):  
Nicholas So
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Electricity Consumption ◽  
Average Error ◽  
University Of Toronto ◽  
Ideal Tool ◽  
Building Characteristics ◽  
Academic Buildings ◽  
The University ◽  
Selection Of

Ryerson University does not have a means to gauge electricity consumption for half of their campus buildings. The installation of utility meters is outside of the University’s budget, a situation that may be similar across other academic institutions. A multiple linear regression approach to estimating consumption for academic buildings is an ideal tool that balances performance and utility. Using 80 buildings from Ryerson University and the University of Toronto, significant building characteristics were identified (from a selection of 18 variables) that show a strong linear relationship with electricity consumption. Four equations were created to represent the diversity in size of academic buildings. Tested using cross-validation, the coefficient of variation of the RMSE for all models was 33%, with a range of error between 20% and 43%. The models were highly successful at modeling electricity consumption at Ryerson University with an average error of 14.8% for five building clusters. Using metered data from each cluster, raw estimates for individual buildings were adjusted to improve accuracy.

scholarly journals Factors Affecting Student Interest Of Al-Quran Wonosobo Science University To Saving In A Syariah Bank

2021 ◽  
Vol 3 (1) ◽  
pp. 47-62
Author(s):  
Mahgalena Mahgalena ◽  
Wahab Wahab ◽  
Choirul Huda
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Field Research ◽  
Primary Data ◽  
Student Interest ◽  
Islamic Banks ◽  
Factors Affecting ◽  
Analysis Technique ◽  
The University

Purpose - This study aims to examine the effect of knowledge, location and religiosity on the interest of students at the University of Sains Al-Quran Wonosobo to save in Islamic bank.Method - This research uses a type of field research with a quantitative approach. Sources of data in this study are primary data obtained from the results of a questionnaire by scoring using a likert scale. The population o this research is 100 students. In data analysis, the data analysis technique used is multiple linear regression analysis.Result - The result showed that knowledge had a significant effect on interest in saving in Islamic bank, while location and religiosity did not significantly influence the interest in saving at Islamic banks. Then knowledge, location and religiosity simultaneously affect the interest in saving at Islamic banks.Implication - This research can be used as input in getting customers with a high amount of savings in Islamic banks.Originality - This study looked at the factors that influence the interest of students at the University of Sains Al-Quran Wonosobo to save in Islamic banks This research can be used as input in getting customers with a high amount of savings in Islamic banks.. In this study focused on 3 variables, namely variables of knowledge, location and religiosity.

scholarly journals Using multiple linear regression to disaggregate electricity consumption for cluster-metered academic buildings

2021 ◽  
Author(s):  
Nicholas So
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Electricity Consumption ◽  
Average Error ◽  
University Of Toronto ◽  
Ideal Tool ◽  
Building Characteristics ◽  
Academic Buildings ◽  
The University ◽  
Selection Of

Ryerson University does not have a means to gauge electricity consumption for half of their campus buildings. The installation of utility meters is outside of the University’s budget, a situation that may be similar across other academic institutions. A multiple linear regression approach to estimating consumption for academic buildings is an ideal tool that balances performance and utility. Using 80 buildings from Ryerson University and the University of Toronto, significant building characteristics were identified (from a selection of 18 variables) that show a strong linear relationship with electricity consumption. Four equations were created to represent the diversity in size of academic buildings. Tested using cross-validation, the coefficient of variation of the RMSE for all models was 33%, with a range of error between 20% and 43%. The models were highly successful at modeling electricity consumption at Ryerson University with an average error of 14.8% for five building clusters. Using metered data from each cluster, raw estimates for individual buildings were adjusted to improve accuracy.

scholarly journals COMPARAÇÃO DE TÉCNICAS ESTATÍSTICAS PARA ANALISAR A RELAÇÃO ENTRE DOENÇAS RESPIRATÓRIAS E CONCENTRAÇÕES DE POLUENTES ATMOSFÉRICOS

2013 ◽  
Vol 35 (1) ◽  
pp. 98
Author(s):  
Angela Radünz Lazzari
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Generalized Linear Models ◽  
Respiratory Diseases ◽  
Linear Models ◽  
Ordinal Logistic Regression ◽  
Atmospheric Pollutants ◽  
Meteorological Variables ◽  
Data Set

Air pollution is a risk factor for the population health. Its harmful effects on the population are observed even when the atmospheric pollutants are within the parameters set out in specific legislation, and they develop mainly through respiratory diseases. The aim of this study was to analyze the relationship between the concentrations of air pollutants and the incidence of respiratory diseases in the city of Porto Alegre, in 2005 and 2006. Applied multiple linear regression analysis, ordinal logistic regression and generalized linear models were used in the work. The results show good adjustment by the three techniques. The ordinal logistic regression detected only positive influence of air temperature and relative humidity in hospitalizations for respiratory diseases. Multiple linear regression related negatively hospitalizations with meteorological variables and positively with the particulate matter (PM10). The generalized linear model detected negative influence of meteorological variables and positive of pollutants, tropospheric ozone (O3) and PM10 in hospitalizations. Comparing the three statistical techniques to analyze the same data set, it can be concluded that all of them had a model with good fit to the data, but the technique of generalized linear models showed higher sensitivity in capturing the influence of pollutants, except in ordinal logistic regression and multiple linear regression.

scholarly journals ANALISIS PENGARUH DIMENSI FRAUD DIAMOND TERHADAP PERILAKU KECURANGAN AKADEMIK MAHASISWA FAKULTAS EKONOMI (Studi Empiris Mahasiswa Fakultas Ekonomi dan Bisnis Universitas Trisakti)

2017 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Anastasya Putri Yudiana ◽  
Hexana Sri Lastanti
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Statistical Method ◽  
Sampling Method ◽  
Purposive Sampling ◽  
Independent Variables ◽  
Academic Fraud ◽  
Convenience Sampling ◽  
The University ◽  
Selection Of

<span class="fontstyle0">This study aims to examine the factors that influence the behavior of academic fraud by students in the faculty of economics by using diamond fraud dimensions consisting of pressure, opportunity, rationalization and capabilities at the University of Trisakti environment. This study is using purposive sampling method and convenience sampling, purposive sampling is the selection of the sample taken not random, so that later on only samples that are necessary are to be tested, while convenience sampling means is easy with a qualititative approach that ultimately result in quantitative. The independent variables in this study is Fraud Diamond and the dependent variable is academic fraud by students in faculty of economics. Data was obtained through questionnaires with Likert scale. Statistical method in use is multiple linear regression with the help of SPSS 20 software. The results of this study indicate that students academic fraud behavior is influenced by the dimensions of the economic faculty of diamond fraud.</span>

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