sed=sqrt(se1**2.0+se2**2.0)# calculate the t statistic t_stat=(mean1-mean2)/sed # degreesoffreedom df=len(data1)+len(data2)-2# calculate the critical value cv=t.ppf(1.0-alpha,df)# calculate the p-value p=(1.0-t.cdf(abs(t_stat),df))*2.0#returneverythingreturnt_stat,df,cv,...
t_stat, p_val = stats.ttest_ind(group1, group2)print(f"t-statistic: {t_stat}, p-value: {p_val}") Python深度学习-意力机制、Transformer模型、生成式模型、目标检测算法、图神经网络、强化学习与可视化方法 Python数据分析实用技巧重新命名列 i...
t_value=stats.t(df).isf(a/2) print"t value:",t_value lsd=t_value*math.sqrt(mse*(1.0/len(sample1)+1.0/len(sample2))) print "LSD:",lsd if distance<lsd: print"no significant difference between:",sample1,sample2 else: print"there is significant difference between:",sample1,sample2 ...
1,1,1,1])model=LogisticRegression(C=1e30).fit(x,y)print(logit_pvalue(model,x))# compare ...
To set up the bootstrap hypothesis test, you will take the mean as our test statistic. Remember, your goal is to calculate the probability of getting a mean impact force less than or equal to what was observed for Frog B if the hypothesis that the true mean of Frog B's impact forces...
To set up the bootstrap hypothesis test, you will take the mean as our test statistic. Remember, your goal is to calculate the probability of getting a mean impact force less than or equal to what was observed for Frog Bif the hypothesis that the true mean of Frog B's impact forces is...
Jason Brownlee：时间序列预测法是一个过程，而获得良好预测结果的唯一途径是实践这个过程。在本教程中，您将了解如何利用Python语言来预测波士顿每月持械抢劫案发生的数量。本教程所述为您提供了一套处理时间序列预测问题的框架，包括方法步骤和工具，通过实践，可以用它来解决自己遇到的相关问题。本教程结束之后，您将...
df=2*N-2#p-value after comparisonwiththe t p=1-stats.t.cdf(t,df=df)print("t = "+str(t))print("p = "+str(2*p))#Note that we multiply the p value by2because its a twp tail t-test ### You can see that after comparing the t statisticwiththe critical tvalue(computed interna...
In [ ]:fromstatsmodels.tsa.stattoolsimportadfuller result = adfuller(df_log_diff)print('ADF statistic:', result[0])print('p-value: %.5f'% result[1]) critical_values = result[4]forkey, valueincritical_values.items():print('Critical value (%s): %.3f'% (key, value)) ...
print(f'T-statistic: {t_stat}, p-value: {p_value}') 6、Scikit-learn Scikit-learn 是一个 Python 机器学习库,提供简单高效的数据分析和建模工具,包括各种分类、回归、聚类和降维算法。 from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split ...