Describe the difference between the predictor variable for l

Solution

Linear Regression is used to establish a relationship between Dependent and Indipendent variables, which is useful in estimating the resultant dependent variable in case indipendent variable change where logistic regression on the other hand is used to ascertain the probability of an event and this event is captured in binary format, i.e. 0 or 1.

The predictive varibles can be categorical or continuous. Logistic regression is similar to linear regression in that it is used to determine which predictor variables are statistically significant, diagnostics are used to check that the assumptions are valid, a test-statistic is calculated that indicates if the overall model is statistically significant, and a coefficient and standard error for each of the predictor variables is calculated.

When we have to predict the value of a categorical outcome, we use logistic regression where use of linear regression to predict the value of an outcome given the input values.