DA0-002 Data Analysis Practice Question

In a multiple regression model, one predictor has a high p-value (0.45). What should the analyst consider doing?

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

✓

Remove the predictor from the model

High p-value indicates the predictor is not statistically significant; it may be removed to simplify the model.

Answer analysis

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

✗
Transform the predictor
Why it's wrong here
A high p-value of 0.45 indicates the predictor’s coefficient is not statistically significant, meaning it fails to reject the null hypothesis that the true coefficient is zero. Transforming the predictor would alter its functional form but does not address the underlying lack of a linear relationship with the response. This option is tempting because transformation is correctly used to linearise non-linear relationships or stabilise variance, scenarios where the predictor’s p-value would typically be low due to a genuine but mis-specified association.
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Keep the predictor regardless
Why it's wrong here
Keeping insignificant predictors adds noise.
✓
Remove the predictor from the model
Why this is correct
The variable is not significant.
✗
Increase the sample size
Why it's wrong here
Increasing sample size might reduce p-value but not necessarily; removing is more direct.

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