Outliers can be removed from a large dataset by using statistical methods such as the interquartile range or by using data visualization tools such as box plots. Additionally, using robust methods such as median or trimmed mean can help reduce the influence of outliers on the results. If the outliers are caused by data entry errors, they can be identified and corrected. If the outliers are caused by natural variability, it may be best to leave them in the dataset and use robust methods to analyze the data.