QUESTION 1) Which of the following statements is correct? Group of answer choices: a) Logistic regression extends the idea of linear regression to the situation where the OUTCOME variable is categorical b) Logistic regression extends the idea of linear regression to the situation where a PREDICTOR variable is categorical c) Linear regression extends the idea of logistic regression to the situation where a PREDICTOR variable is categorical d) Linear regression extends the idea of logistic regression to the situation where the OUTCOME variable is categorical QUESTION 2) Which statement is correct with regard to describing the odds of belonging to class 1 in a binary classification model? Group of answer choices: a) The ratio of the probability of belonging to class 1 to the probability of belonging to class 0 b) The probability of belonging to class 1 c) The ratio of the probability of belonging to class 0 to the probability of belonging to class 1 d) The probability of belonging to class 0 QUESTION 3) What is the range for the value of Log Odds, or as it's called the logit? Group of answer choices: a) - to + b) 0 to + c) 0 to 1 d) -1 to +1 QUESTION 4) What is the interpretation of “log odds = 0” in a binary classification model? Group of answer choices: a) The probability of belonging to class 1 is zero b) The probability of belonging to class 1 is undeterminable c) The probability of belonging to class 1 is almost zero d) The probability of belonging to class 1 is 0.5 QUESTION 5) Which of the following statements is NOT a difference between Linear and Logistic Regression? Group of answer choices: a) Linear regression is more suitable for explanatory purpose, while logistic regression is more suitable for predictive purpose b) In linear regression, the relationship between Y and the beta coefficients is non-linear. Whereas in logistic regression, the relationship between Y and the beta coefficients is linear. c) Linear regression is more suitable for predictive purpose, while logistic regression is more suitable for explanatory purpose d) In linear regression, the relationship between Y and the beta coefficients is linear. Whereas in logistic regression, the relationship between Y and the beta coefficients is non-linear.
please answer all the questions
QUESTION 1)
Which of the following statements is correct?
Group of answer choices:
a) Logistic regression extends the idea of linear regression to the situation where the OUTCOME variable is categorical
b) Logistic regression extends the idea of linear regression to the situation where a PREDICTOR variable is categorical
c) Linear regression extends the idea of logistic regression to the situation where a PREDICTOR variable is categorical
d) Linear regression extends the idea of logistic regression to the situation where the OUTCOME variable is categorical
QUESTION 2)
Which statement is correct with regard to describing the odds of belonging to class 1 in a binary classification model?
Group of answer choices:
a) The ratio of the probability of belonging to class 1 to the probability of belonging to class 0
b) The probability of belonging to class 1
c) The ratio of the probability of belonging to class 0 to the probability of belonging to class 1
d) The probability of belonging to class 0
QUESTION 3)
What is the range for the value of Log Odds, or as it's called the logit?
Group of answer choices:
a) - to +
b) 0 to +
c) 0 to 1
d) -1 to +1
QUESTION 4)
What is the interpretation of “log odds = 0” in a binary classification model?
Group of answer choices:
a) The probability of belonging to class 1 is zero
b) The probability of belonging to class 1 is undeterminable
c) The probability of belonging to class 1 is almost zero
d) The probability of belonging to class 1 is 0.5
QUESTION 5)
Which of the following statements is NOT a difference between Linear and Logistic Regression?
Group of answer choices:
a) Linear regression is more suitable for explanatory purpose, while logistic regression is more suitable for predictive purpose
b) In linear regression, the relationship between Y and the beta coefficients is non-linear. Whereas in logistic regression, the relationship between Y and the beta coefficients is linear.
c) Linear regression is more suitable for predictive purpose, while logistic regression is more suitable for explanatory purpose
d) In linear regression, the relationship between Y and the beta coefficients is linear. Whereas in logistic regression, the relationship between Y and the beta coefficients is non-linear.
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