Examples of 'explanatory variables' in a sentence
Meaning of "explanatory variables"
explanatory variables: Explanatory variables are independent variables in statistical analysis that are used to explain or predict the outcome of a dependent variable. These variables are manipulated or controlled by researchers to understand the relationship or impact they have on the dependent variable. They are often used in regression analysis or experimental design to explore cause-and-effect relationships
How to use "explanatory variables" in a sentence
Basic
Advanced
explanatory variables
Explanatory variables are typically measured on different scales.
Interactions between explanatory variables were not observed.
Explanatory variables after removing the effect of covariables.
Three groups of explanatory variables were included.
Explanatory variables used to explain the source lines of.
Forecasting of the explanatory variables up to the same horizon.
Relationship between outcome variable and explanatory variables.
All explanatory variables are lagged by one period.
Selection and definition of explanatory variables.
The explanatory variables were grouped into three areas.
Collinearity is a linear association between two explanatory variables.
The following explanatory variables were selected.
These extended models include additional explanatory variables.
All the explanatory variables were divided into categories.
The dependent variable and the explanatory variables.
See also
The explanatory variables were divided into two groups.
The variability of the explanatory variables.
All the explanatory variables were used.
Demographic and socioeconomic explanatory variables.
The following explanatory variables were analyzed.
Personal disposable income as explanatory variables.
All reported explanatory variables are lagged one year.
Correlations between the explanatory variables.
All explanatory variables are assumed to be predetermined.
Correlation with the explanatory variables.
The explanatory variables are temperature and day length.
The implication is that the explanatory variables have to be exogenous.
Explanatory variables explained above.
Event and explanatory variables.
Mean number of deaths was estimated as a function of the explanatory variables.
The following list of explanatory variables are the main.
It makes it possible to select the most relevant explanatory variables.
Was a vector of explanatory variables and.
Each equation to be estimated contains the same explanatory variables.
The magnitude of key explanatory variables is determined by the marginal effect gX.
Forward stepwise procedure was used in the selection of the explanatory variables.
The explanatory variables and their respective metrics are described below.
There are several explanatory variables.
The other explanatory variables did not carry significant explanatory power.
Physiographic parameters were used as explanatory variables in the regression analysis.
Catchability is modeled using both continuous and categorical explanatory variables.
Testing whether a subset of explanatory variables is exogenous is an important challenge in econometrics.
Effects on the probabilities evaluated at the mean of the explanatory variables.
Independent explanatory variables.
The form of the relationship between response and explanatory variables.
X is the explanatory variables.
The random effects model was chosen for the three explanatory variables.
Other explanatory variables.
The distribution of scores with other explanatory variables was similar.
Note that the explanatory variables can be either qualitative or quantitative.
You'll also be interested in:
Examples of using Variables
Show more
Variables are introduced in order to track such bequests
The plan of the variables is the following
Variables to be probed as part of the study include
Examples of using Explanatory
Show more
Explanatory comments appear in parentheses in this format
Annex draft explanatory note and comment
Explanatory note and key to the table
