Pandas 解释OLS回归的结果

Pandas 解释OLS回归的结果,pandas,statistics,Pandas,Statistics,我试图找到一些关于如何正确解释OLS回归结果的信息: model = ols("rating ~ gender_F + gender_M + genre + gender_F*genre + gender_M*genre", data = data).fit() model_summary = model.summary() print(model_summary) 我得到以下输出: OLS Regression Results

我试图找到一些关于如何正确解释OLS回归结果的信息:

model = ols("rating ~ gender_F + gender_M + genre + gender_F*genre + gender_M*genre", data = data).fit()
model_summary = model.summary()
print(model_summary)
我得到以下输出:

OLS Regression Results                            
==============================================================================
Dep. Variable:                 rating   R-squared:                       0.000
Model:                            OLS   Adj. R-squared:                 -0.000
Method:                 Least Squares   F-statistic:                    0.3757
Date:                Tue, 15 Sep 2020   Prob (F-statistic):               1.00
Time:                        17:48:10   Log-Likelihood:            -1.5372e+05
No. Observations:              100000   AIC:                         3.075e+05
Df Residuals:                   99963   BIC:                         3.079e+05
Df Model:                          36                                         
Covariance Type:            nonrobust                                         
=================================================================================================
                                    coef    std err          t      P>|t|      [0.025      0.975]
-------------------------------------------------------------------------------------------------
Intercept                      -8.39e+11   1.26e+12     -0.663      0.507   -3.32e+12    1.64e+12
genre[T.Adventure]             -1.94e+11   1.31e+11     -1.481      0.139   -4.51e+11    6.28e+10
genre[T.Animation]            -2.204e+11   3.09e+11     -0.714      0.475   -8.25e+11    3.85e+11
genre[T.Childrens]             1.299e+11   3.06e+11      0.424      0.671    -4.7e+11     7.3e+11
genre[T.Comedy]                -1.17e+11   2.24e+11     -0.523      0.601   -5.55e+11    3.21e+11
genre[T.Crime]                 1.739e+11   3.52e+11      0.493      0.622   -5.17e+11    8.65e+11
genre[T.Documentary]            9.41e+11   7.97e+11      1.181      0.238    -6.2e+11     2.5e+12
genre[T.Drama]                 1.276e+11   7.25e+11      0.176      0.860   -1.29e+12    1.55e+12
........
gender_F                        8.39e+11   1.26e+12      0.663      0.507   -1.64e+12    3.32e+12
gender_F:genre[T.Adventure]     1.94e+11   1.31e+11      1.481      0.139   -6.28e+10    4.51e+11
gender_F:genre[T.Animation]    2.204e+11   3.09e+11      0.714      0.475   -3.85e+11    8.25e+11
gender_F:genre[T.Childrens]   -1.299e+11   3.06e+11     -0.424      0.671    -7.3e+11     4.7e+11
gender_F:genre[T.Comedy]        1.17e+11   2.24e+11      0.523      0.601   -3.21e+11    5.55e+11
gender_F:genre[T.Crime]       -1.739e+11   3.52e+11     -0.493      0.622   -8.65e+11    5.17e+11
gender_F:genre[T.Documentary]  -9.41e+11   7.97e+11     -1.181      0.238    -2.5e+12     6.2e+11
gender_F:genre[T.Drama]       -1.276e+11   7.25e+11     -0.176      0.860   -1.55e+12    1.29e+12
gender_F:genre[T.Fantasy]     -2.866e+10   6.69e+10     -0.429      0.668    -1.6e+11    1.02e+11
gender_F:genre[T.Film-Noir]   -6.506e+11   1.02e+12     -0.636      0.525   -2.66e+12    1.36e+12

我想知道如何解释coef?我们确定该系数被认为是重要的截止点是什么?在分析中还可以包括哪些内容?解释P>| t |,P值(在我的例子中,没有显著的关系)