Final answer:
In logistic regression, the independent variables are the predictors, the dependent variable is the probability of acceptance, and scatter plots are not used.
Step-by-step explanation:
a. In a logistic regression analysis, the independent variables are the predictors that are being evaluated, while the dependent variable is the probability of acceptance. The independent variables can be categorical or continuous.
b. Since logistic regression deals with categorical data, a scatter plot is not applicable. Scatter plots are used to visualize the relationships between two continuous variables.
c. In logistic regression, the line of best fit is represented by the logistic regression equation, which estimates the probability of an event (in this case, acceptance) based on the values of the predictors. The correlation coefficient is not typically used in logistic regression as it is in linear regression.
d. The correlation coefficient is not applicable in logistic regression, as it is used to measure the strength and direction of a linear relationship between two continuous variables. Instead, in logistic regression, we assess the significance of the predictors through statistical tests such as the Wald test or likelihood ratio test.
e. Logistic regression analyzes the relationship between the predictors and the probability of acceptance, not a linear relationship between the predictors themselves.