DA0-002 Data Analysis Practice Question
Exhibit
Refer to the exhibit.
Call:
lm(formula = price ~ sqft_living + bedrooms + bathrooms, data = housing)
Residuals:
Min 1Q Median 3Q Max
-1.2345 -0.3456 -0.0123 0.3456 2.3456
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.123456 0.012345 10.000 <2e-16 ***
sqft_living 0.001234 0.000123 10.000 <2e-16 ***
bedrooms -0.056789 0.012345 -4.600 4.23e-06 ***
bathrooms 0.234567 0.045678 5.135 3.45e-07 ***
--
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4567 on 496 degrees of freedom
Multiple R-squared: 0.789, Adjusted R-squared: 0.787
F-statistic: 617.8 on 3 and 496 DF, p-value: < 2.2e-16Given the linear regression output, which independent variable has the strongest effect on price, based on standardized coefficients?
⚠ Common exam trap
The trap here is that candidates mistakenly compare unstandardized coefficients or p-values instead of standardized coefficients, leading them to choose a variable like bathrooms or bedrooms that appears significant but has a weaker standardized effect.
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
✓
sqft_living
Standardized coefficients (beta weights) allow comparison of the relative strength of independent variables by measuring the number of standard deviations the dependent variable changes per one standard deviation change in the predictor. In the regression output, sqft_living has the highest absolute standardized coefficient, indicating it has the strongest effect on price. The intercept is not an independent variable and its coefficient is not standardized for comparison.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
bathrooms
Why it's wrong here
bathrooms has a lower t-value (5.135) than sqft_living.
- ✓
sqft_living
Why this is correct
sqft_living has the highest absolute t-value (10.0) indicating strong effect.
- ✗
Intercept
Why it's wrong here
The intercept is not an independent variable; it's the baseline.
- ✗
bedrooms
Why it's wrong here
bedrooms has a negative coefficient and lower t-value magnitude (4.6).
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