Over 1100 students over four semesters were given the option of taking an introductory undergraduate statistics class either by in-person attendance in lectures or by taking exactly the same class (same instructor, recorded lectures, homework, blind grading, website, etc.) without the in-person lectures. Roughly equal numbers of students chose each option. The online lectures were available to all. Attendance by online students was rare. The online students did slightly better on computer-graded exams. The causal effect of choosing only online lectures was estimated by adjusting for measured confounders, of which the incoming ACT math scores turned out to be most important, using four standard methods. The four nearly identical point estimates remained positive but were small and not statistically significant at the 95% confidence level. Sensitivity analysis indicated that unmeasured confounding was unlikely to be large but might plausibly reduce the point estimate to zero. No statistically significant differences were found in preliminary comparisons of effects on females/males, U.S./non-U.S. citizens, freshmen/non-freshman, and lower-scoring/higher-scoring math ACT groups.

翻译：在四个学期中，超过1100名学生可以选择通过线下出席讲座或通过完全相同的课程（相同教师、录制讲座、作业、盲评、网站等）但不参加线下讲座的方式，修读一门本科统计学入门课程。选择每种选项的学生数量大致相等。所有学生均可获得在线讲座资源。在线学生的出勤率极低。在线学生在计算机评分考试中表现略优。通过调整已测量的混杂因素（其中入学ACT数学成绩最为关键），并采用四种标准方法估计仅选择在线讲座的因果效应，得到的四个近乎相同的点估计值均为正值但较小，且在95%置信水平下不具备统计显著性。敏感性分析表明，未测量的混杂因素影响不太可能很大，但可能会合理地将点估计值降低至零。在针对女性/男性、美国/非美国公民、新生/非新生以及ACT数学低分/高分群体的初步效果比较中，未发现具有统计显著性的差异。