Examples of using Dependent variables in English and their translations into Indonesian
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Ecclesiastic
Describe the design and clearly spell out the independent and dependent variables.
When any of the dependent variables change, the‘DB Library' will run your binding expressions(and thus updates views).
The answer to this question is a definite yes, but the effect depends on what dependent variables you look at.
In the first design, the effects on dependent variables are measured several times before and after the independent variables are subjected.
You can directly apply and evaluate R Squared when comparing twoequations with different explanatory variables and identical dependent variables.
In the most general case there may be one or more independent variables and one ormore dependent variables at each data point.
From its initial research(like the Erie County Study),the field of political communication focused on such individual-level dependent variables as voting choices.
Homogeneity of Variances:- Homogeneity of variances assumes that the dependent variables exhibit equal levels of variance across the range of predictor variables. .
Or in other words, the moderator variable has asignificant contribution against the ability of the independent variable in the dependent variables affect.
We can derive the probability distribution of any linear combination of the dependent variables if the probability distribution of experimental errors is known or assumed.
In any experimental design, a researcher will be manipulating one variable, the independent variable, and studying how that affects the dependent variables.
The probability distribution of any linear combination of the dependent variables can be derived if the probability distribution of experimental errors is known or assumed.
This is also common in experimental design where factors such as thequality of the user's performance are used as dependent variables, and measured on a quantitative scale.
For dependent variables, the data are a random sample of vectors from a multivariate normal population; in the population, the variance-covariance matrices for all cells are the same.
In explorative research methodology, e.g. in some qualitative research,the independent and the dependent variables might not be identified beforehand.
The change in one or more independent variables is generally hypothesized to result in a change inone or more dependent variables, also referred to as“output variables” or“response variables.”.
To verify the statistical significance of this pattern,three orthogonal comparisons were conducted on both dependent variables(the frequency and total amount of donations).
In the charity solicitation experiment, the dependent variables were objective behavioral measures(donation of money and amount donated), so the authors did not have to be concerned with the problems of selfreport measures, or the reliability and validity issues of rating scales.
The multinomial logit model is the appropriate technique in these cases,especially when the dependent variables are not ordered(for example colors like red, blue, green).
A research hypothesis is quite often a predictive statement, which is capable of being testedusing scientific methods that involve an independent and some dependent variables.
This can be done using linear regressions,which correlate independent variables(or questions) with dependent variables(or comprehensive‘big picture' questions).
This situation can be viewed as a within-subject independent variable with as many levels as occasions,or it can be viewed as separate dependent variables for each occasion.
While mathematically it is feasible toapply multiple regression to discrete ordered dependent variables, some of the assumptions behind the theory of multiple linear regression no longer hold, and there are other techniques such as discrete choice models which are better suited for this type of analysis.
These models may contain multiple independent,dependent and mediating variables(interactions and categorical dependent variables can be problematic depending on the software used).
Failing to take a confounding variable intoaccount can lead to a false conclusion that the dependent variables are in a causal relationship with the independent variable. .
The qualitative nature of most of the information,the representativity of the samples used and the censoring issues associated to the dependent variables are, among others, some of the aspects that distinguish these techniques from an econometric perspective…[-].
The dependent variable: Stress.
Dependent variable: Performance of Employee.
An experiment has an independent and dependent variable.