10회 기출 작업형3 문제 2-1 질문

안녕하세요. 해당 문제를 아래와 같이 풀었는데 저는 계속 0.253이 나오는데 정답이 0.254여서 제가 어떤 부분에서 틀렸는지 알고 싶습니다. 감사합니다.

[출력결과]

                            OLS Regression Results                            
==============================================================================
Dep. Variable:           heating_load   R-squared:                       0.754
Model:                            OLS   Adj. R-squared:                  0.752
Method:                 Least Squares   F-statistic:                     417.8
Date:                Tue, 16 Jun 2026   Prob (F-statistic):          2.02e-164
Time:                        12:24:27   Log-Likelihood:                -1772.0
No. Observations:                 550   AIC:                             3554.
Df Residuals:                     545   BIC:                             3576.
Df Model:                           4                                         
Covariance Type:            nonrobust                                         
==============================================================================
                 coef    std err          t      P>|t|      [0.025      0.975]
------------------------------------------------------------------------------
Intercept     38.3821      1.504     25.517      0.000      35.427      41.337
wall           0.0304      0.030      1.012      0.312      -0.029       0.090
roof           0.2483      0.006     39.564      0.000       0.236       0.261
glazing        0.2217      0.023      9.693      0.000       0.177       0.267
height        -0.2469      0.077     -3.212      0.001      -0.398      -0.096
==============================================================================
Omnibus:                        0.698   Durbin-Watson:                   1.896
Prob(Omnibus):                  0.705   Jarque-Bera (JB):                0.785
Skew:                          -0.077   Prob(JB):                        0.675
Kurtosis:                       2.899   Cond. No.                         805.
==============================================================================

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
0.25349999999999995

[코드]

# 1) 데이터 불러오기
df = pd.read_csv("https://raw.githubusercontent.com/lovedlim/inf/refs/heads/main/p4/10_3/heating.csv")

# 모든 독립변수를 포함한 회귀모형을 적합하시오. 다중 선형 회귀 분석
from statsmodels.formula.api import ols 
model = ols("heating_load ~ wall + roof + glazing + height", data = df).fit()
print(model.summary())

# 이때 절편을 제외한 회귀계수의 합을 구하시오.


print(0.0304+ 0.2483+ 0.2217+ ( -0.2469) )

# 0.253