During the post-intervention period, the response variable had an average value of approx. 3.the absence of an intervention, we would have expected an average response of 3. The 95% interval of this counterfactual prediction is [3, 3]. Subtracting this prediction from the observed response yields an estimate of the causal effect the intervention had on the response variable. This effect is 0 with a 95% interval of [0, 0]. For a discussion of the significance of this effect, see below.Summing up the individual data points during the post-intervention period (which can only sometimes be meaningfully interpreted), the response variable had an overall value of 7.the intervention not taken place, we would have expected a sum of 7. The 95% interval of this prediction is [7, 7]The above results are given in terms of absolute numbers. In relative terms, the response variable showed-2.8%. The 95% interval of this percentage is [0.0%, -11.1%]This means that the negative effect observed during the intervention period is statistically significant. If the experimenter had expected a positive effect, it is recommended to double-check whether anomalies in the control variables may have caused an overly optimistic expectation of what should have happened in the response variable in the absence of the intervention.
