DA0-002 Data Analysis Practice Question
A data analyst is building a logistic regression model to predict whether a customer will churn (yes/no). Which TWO statements about logistic regression are correct?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The output is a probability between 0 and 1.
Logistic regression outputs probabilities between 0 and 1, and can use a sigmoid function. It is a classification algorithm, and coefficients represent log-odds changes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
It is used only for time series forecasting.
Why it's wrong here
It is used for classification.
- ✗
The dependent variable is continuous.
Why it's wrong here
Logistic regression deals with categorical outcomes.
- ✓
The output is a probability between 0 and 1.
Why this is correct
Logistic regression predicts probabilities.
- ✗
It requires normally distributed errors.
Why it's wrong here
Logistic regression does not assume normality.
- ✓
It assumes a linear relationship between predictors and the log-odds of the outcome.
Why this is correct
This is the underlying assumption.
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