How to analyze experimental data
Posted: Sat Jan 18, 2025 8:34 am
The graph shows how different versions of the site behaved on what dates. This is what the report will look like (its first part): Below are the detailed numbers for the metrics you chose to track. We are mainly interested in the first three columns - these are the metrics we chose to track. The larger indicators are highlighted in green.
In the experimental report, we see that the B-version wins list of honduras whatsapp phone numbers The report also has additional metrics. Here's what's written about them in the report help : Delta is the difference between the metric values in the experimental and control variants. Delta (%) - delta expressed as a percentage of the metric value in the control variant. Confidence interval - a plot of confidence intervals for the experimental and control variants on a number axis.
P-value is the main numerical characteristic of the result of a statistical criterion. It means the probability of obtaining the same or more extreme results under the assumption that the metric value has not actually changed. The hypothesis is accepted by comparing the P-value with the significance level: P-value <= alpha. The default threshold is alpha = 0.05. It is important to understand that alpha sets the probability of type I errors (false positives).
In the experimental report, we see that the B-version wins list of honduras whatsapp phone numbers The report also has additional metrics. Here's what's written about them in the report help : Delta is the difference between the metric values in the experimental and control variants. Delta (%) - delta expressed as a percentage of the metric value in the control variant. Confidence interval - a plot of confidence intervals for the experimental and control variants on a number axis.
P-value is the main numerical characteristic of the result of a statistical criterion. It means the probability of obtaining the same or more extreme results under the assumption that the metric value has not actually changed. The hypothesis is accepted by comparing the P-value with the significance level: P-value <= alpha. The default threshold is alpha = 0.05. It is important to understand that alpha sets the probability of type I errors (false positives).