DA0-002 Data Analysis Practice Question
A data scientist builds a simple linear regression model to predict house prices based on square footage. The model yields an R-squared value of 0.85. Which statement accurately interprets this result?
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 model explains 85% of the variability in house prices
R-squared of 0.85 means 85% of the variance in house prices is explained by square footage.
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 slope of the regression line is 0.85
Why it's wrong here
R-squared is not the slope.
- ✗
85% of the data points lie exactly on the regression line
Why it's wrong here
R-squared does not indicate percentage of points on the line.
- ✓
The model explains 85% of the variability in house prices
Why this is correct
Correct interpretation of R-squared.
- ✗
There is a 85% chance that square footage causes higher prices
Why it's wrong here
R-squared does not imply causation or probability.
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