Assertion: regression's variable | /r/HasProperty | equal
Facets:
value: to a value
type: OTHER
value: to 0
type: OTHER
value: to zero
type: OTHER
value: to the square of x.
type: OTHER
Source sentences:
text: To do that , we create a new variable which is equal to the square of X.
text: a is the Y-intercept, which is the expected mean value of y when all x variables are equal to 0.
text: To accomplish this, we transform the original, ordinal, dependent variable into a new, binary, dependent variable which is equal to zero if the original, ordinal dependent variable (here apply ) is less than some value a, and 1 if the ordinal variable is greater than or equal to a (note, this is what the ordinal regression model coefficients represent as well).
text: , u, lower.tail = TRUE) is an R function that gives the probability that a random variable will be lower than or equal to a value.