Multiple measurement points during baseline control for statistical regression.

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Multiple measurement points during baseline control are important for statistical regression to help ensure that any observed changes are not simply due to random variation or measurement error. By collecting data over multiple time points, it becomes possible to identify patterns and trends that may indicate underlying causes of variation or changes in the dependent variable that are related to the intervention being tested. This can help to strengthen the validity of experimental findings and improve the accuracy of any conclusions drawn based on the data collected.

Multiple Measurement Points During Baseline Control for Statistical Regression