Examples of using Predictor variables in English and their translations into Indonesian
{-}
-
Colloquial
-
Ecclesiastic
-
Computer
-
Ecclesiastic
Different predictor variables, that is, the Xs.
And x3 the independent or predictor variables.
No other predictor variables were selected.
Linear regression is an analysis that assesses whether one or more predictor variables explain the dependent(criterion) variable. .
Two predictor variables may be significantly correlated and still have low colinearity.
Predicting a complex phenomenon with only one factor(predictor variables) often only give less accurate results.
Predictor variables, based on group outcomes in rehabilitation, should be applied with caution to the individual case.
What we use to make predictions,the variables that are already known is called the predictor variable( predictor variables).
Being in predictive studies, the predictor variables should be measured over a period of time before the criterion variable occurs.
The linear regression model analyzes the relationship between the response or dependent variable anda set of independent or predictor variables.
The model has been appropriate and predictor variables entered into the model can explain the diversity of 32.6% with a classification accuracy of 74%.
It can be used for identifying relationships between predictor and criterion variables, whether the predictor variables are quantitative or qualitative in nature.
It is known that in this study the predictor variables are categorical and continuous with the response variable has two categories, then the appropriate method in this study is a binary logistic regression analysis.
Therefore, unlike relational research,both variables are measured in time sequence, the predictor variables were measured before going on criterion variables, and can not be otherwise.
Basically, correlation studies involving the calculation of the correlation between the complex variables(variable criteria)with other variables that are considered as bonafit relationship(predictor variables).
Under the condition that the errors are uncorrelated with the predictor variables, LLSQ yields unbiased estimates, but even under that condition NLLSQ estimates are generally biased.
Procedure generates a discriminant function(or, for more than two groups, a set of discriminant functions)based on linear combinations of the predictor variables that provide the best discrimination between the groups.
Like other regression models, QSAR regression models relate a set of"predictor" variables(X) to the potency of the response variable(Y),while classification QSAR models relate the predictor variables to a categorical value of the response variable. .
We illustrate this with an example where changing the working correlation from independence to equicorrelation qualitatively biases parameters of GEE models and show that this happens because within-and between-subject slopes for the outcomes regressed on the predictor variables differ.
Once the model has been estimated we would be interested to know if the predictor variables belong in the model-i. e. is the estimate of each variable's contribution reliable?
When involving more than two variables, for example, to determine whether two or more predictor variables can be used to predict the criterionvariable is better than when used individually, multiple regression analysis techniques, multiple regression or canonical analysis can be used.
SDM are empiricalmodels relating field observations to environmental predictor variables, based on statistically or theoretically derived response surfaces.
Neural networks are applicable in virtually every situation in which a relationship between the predictor variables(independents, inputs) and predicted variables(dependents, outputs) exists, even when that relationship is very complex and not easy to articulate in the usual terms of'correlations' or'differences between groups.'.
Logit analysis is usually employed if all of the predictors are categorical;and logistic regression is often chosen if the predictor variables are a mix of continuous and categorical variables and/or if they are not nicely distributed(logistic regression makes no assumptions about the distributions of the predictor variables).
The lab is used as the predictor variable.
