Assertion: regression's variable | /r/HasProperty | binary
Facets:
value: in nature
type: LOCATION
value: in logistic regression
type: OTHER
Source sentences:
text: Even though logistic (logit) regression is frequently used for binary variables (2 classes), it can be used for categorical dependent variables with more than 2 classes.
text: Logistic regression is generally used where the dependent variable is Binary or Dichotomous.
text: We should use logistic regression when the dependent variable is binary (0/ 1, True/
text: Binary logistic regression is the statistical technique used to predict the relationship between the dependent variable (Y) and the independent variable (X), where the dependent variable is binary in nature.
text: x} is a Bernoulli distribution rather than a Gaussian distribution, because the dependent variable is binary.
text: Here the dependent factor or variable is binary in nature.
text: The independent variables can be continuous or binary.
text: Where the dependent variable is dichotomous or binary in nature, we cannot use simple linear regression.
text: Logistic regression is the statistical technique used to predict the relationship between predictors (our independent variables) and a predicted variable (the dependent variable) where the dependent variable is binary (e.g., sex [male vs. female], response [yes vs. no], score [high vs. low], etc…).
text: outcome (response) variable is binary (0/1); win or lose.
text: outcome (response) variable is binary (0/1); win or lose.
text: For this chapter only, we are going to deal with a dependent variable that is binary (a categorical variable that has two values such as "yes" and "no") rather than continuous.
text: Logistic regression and probit models are used when the dependent variable is binary.
text: The outcome (response) variable is binary (0/1); win or lose.
text: In logistic regression, the dependent variable is binary or dichotomous, i.e. it only contains data coded as 1 (TRUE, success, pregnant, etc.) or 0 (FALSE, failure, non-pregnant, etc.).
text: The dependent variable must be binary or dichotomous, and should only contain data coded as 0 or 1.
text: The outcome (response) variable is binary (0/1); win or lose.