DA0-002 Data Analysis Practice Question
A data scientist is building a model to predict customer churn (yes/no). After training a logistic regression model, the coefficient for 'monthly charges' is 0.05 with a p-value of 0.03. Which interpretation is correct at α=0.05?
⚠ Common exam trap
The trap is misinterpreting the coefficient as a direct probability change or confusing it with R-squared; candidates may also ignore the p-value and incorrectly claim no significance.
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 every unit increase in monthly charges, the odds of churn increase by about 5%.
In logistic regression, coefficients are in log-odds units. A coefficient of 0.05 means that for a one-unit increase in monthly charges, the log-odds of churn increase by 0.05. Exponentiating gives e^0.05 ≈ 1.051, so the odds increase by about 5.1%. The p-value of 0.03 is less than α=0.05, so 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.
- ✗
The model's R-squared is 0.05.
Why it's wrong here
R-squared measures the proportion of variance explained in linear regression, whereas logistic regression coefficients describe log-odds change per unit. It is tempting because 0.05 appears in both, but the coefficient is not a goodness-of-fit statistic; pseudo-R-squared measures would be reported separately.
- ✓
For every unit increase in monthly charges, the odds of churn increase by about 5%.
Why this is correct
A one-unit rise in monthly charges multiplies the odds of churn by e^0.05 ≈ 1.051, an increase of roughly 5%. The p-value of 0.03 falls below α=0.05, so the coefficient is statistically significant and the predictor's effect on churn odds is supported.
- ✗
Monthly charges decrease the probability of churn.
Why it's wrong here
A positive coefficient of 0.05 means monthly charges increase the log-odds of churn, so the direction stated is reversed. It is tempting because the p-value of 0.03 confirms significance, but significance says nothing about the sign; the sign comes from the coefficient itself.
- ✗
Monthly charges have no significant effect on churn.
Why it's wrong here
With p=0.03 below α=0.05, the null hypothesis of no effect is rejected, so monthly charges do have a statistically significant association with churn. It is tempting because 0.05 is small in magnitude, but significance depends on the p-value, not the coefficient size.
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Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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