Examples of using Multiple regression analysis in English and their translations into Indonesian
{-}
-
Colloquial
-
Ecclesiastic
-
Computer
-
Ecclesiastic
Multiple regression analysis in Minitab.
Results of analysis by using multiple regression analysis showed that: 1.
Multiple regression analysis was used to ascertain whether.
Results of analysis by using multiple regression analysis showed that: 1.
Multiple regression analysis of the results revealed that.
The main mathematical approach used in these studies is multiple regression analysis.
Multiple regression analysis was performed to control for age.
The method used in this study are multiple regression analysis using Eviews 9.
Use multiple regression analysis with various frequencies to increase the scope of testing and improve accuracy.
Having mastered simple regression, students will also learn the basics of multiple regression analysis. .
This research uses multiple regression analysis as a testing tool.
So the researchers sought to control for other factors like gender, race, age, education, political leaningand even personal feelings about Clinton and Trump using multiple regression analysis.
Use of multiple regression analysis of the frequency and increase the scope of testing to enhance accuracy.
This is true even foradvanced correlation-based statistical techniques such as multiple regression analysis, which control for competing effects of several variables on one main dependent variable.
Multiple regression analysis may permit predictions about changes in communication variables that can be expected when the communication situation changes.
Mathematically, factor analysis is somewhat similar to multiple regression analysis, in that each variable is expressed as a linear combination of underlying factors.
In multiple regression analysis these were linked to HbA1c, duration of diabetes and systolic blood pressure, and fasting plasma glucose, folate and C-reactive protein, respectively.
Examples of the curriculum include human factors, research methods,industrial and organizational psychology, multiple regression, analysis of variance, patient handling, physical health at work, and sports medicine.
Path analysis is an extension of multiple regression analysis, used to test the fit of the correlation matrix against two or more causal models which are being compared by the researchers.
So the researchers sought to control for other factors such as gender, race, age, education, political leaning and even personal feelings about Clinton andTrump using multiple regression analysis, a method to measure the relative impact of multiple independent variables.
Multiple regression analysis was used to investigate whether those variables that differentiate between occupations also contribute to job satisfaction based on satisfaction data collected at the same time as the Career Direct normative data.
So the researchers sought to control for other factors such as gender, race, age, education, political leaningand even personal feelings about Clinton and Trump using multiple regression analysis, a method to measure the relative impact of multiple independent variables.
In a multiple regression analysis, the effect of each independent variable(i.e., each predictor) on the dependent variable(the log of NT-proBNP increase) is calculated controlling for the effects of all the other independent variables on the dependent variable.
In Linear Regression analysis, we can involve one independent variable and one dependent variable, which is commonly called a simple regression analysis. We can also involve more than one independent variables with thedependent variable which is commonly called multiple regression analysis.
Among the variables adjusted in the multiple regression analysis, the VAS score(measurement of perception of labour pain), the husband accompanying the wife to the antenatal clinic, and availability of a support person at home were also observed to be significantly associated with the women's feeling of being in control during labour.
When involving more than two variables, for example, to determine whether two or more predictor variables can be used to predict the criterion variableis better than when used individually, multiple regression analysis techniques, multiple regression or canonical analysis can be used.
It is clear that many of the methods used by social psychologists are not unique to them but are also used by sociologists, political scientists, economists, or members of other social science disciplines(for instance, this is true of survey research, of evaluation research,and of many statistical techniques such as multiple regression analysis).
Data from the normative sample of working adults(N= 1002), 1995,were entered into multiple regression analyses to predict Strong individual occupational scales(105 scales, males and female) using Career Direct General Interest factor scores(21), Personality factors(compassion and extroversion) and personality subfactors(10) from the remaining four factors.
Using multiple regression data analysis and binomial logistic regression methods, Dr. Daru Asih, S.E., M. Sc.
Data analysis technique used are factor analysis, multiple linear regression analysis and classical assumption were processed using SPSS version 15.00.