Final answer:
An outlier is a data point that significantly deviates from other data points in a set, often due to experimental errors or other issues. It is crucial to assess the causes of an outlier to decide if it should be included or excluded from the analysis.
Step-by-step explanation:
The part of the data that is not valid because of mistakes in designing or carrying out the experiment is likely referring to an outlier. Outliers are data points that deviate significantly from other observations in a data set. These aberrations can be the result of experimental error, recording mistakes, or could indicate a rare event. It's important to closely examine outliers to determine whether they are the result of nonsampling errors such as poor study design, biased sampling methods, data entry errors, or are genuine values that represent important variations in the data. In a statistical analysis, if an outlier is deemed to result from an error, it may be excluded from the data set to avoid skewing the results. However, if the outlier is a true representation of the population, it should be retained as it can provide valuable insights.