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DA0-002 Data Analysis Practice Question

A logistic regression model is used to predict the probability of customer churn. The model's coefficient for the feature 'customer support calls' is 0.8 with a p-value of 0.001. Which interpretation is 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

For each additional support call, the log-odds of churn increase by 0.8, and this effect is statistically significant.

In logistic regression, a positive coefficient indicates that as the predictor increases, the log-odds of the outcome increase. The p-value being less than 0.05 indicates the effect is statistically significant.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • For each additional support call, the log-odds of churn increase by 0.8, and this effect is statistically significant.

    Why this is correct

    Correct interpretation of logistic regression coefficient.

  • The odds of churn are multiplied by 0.8 for each additional call.

    Why it's wrong here

    The exponentiated coefficient gives odds ratio, not the coefficient itself.

  • Support calls have no significant effect on churn.

    Why it's wrong here

    p-value is 0.001, so significant.

  • For each additional support call, the probability of churn increases by 80%.

    Why it's wrong here

    Coefficient is in log-odds, not probability.

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