In the early stages of working with a dataset, you gain data understanding by at least selectively performing outlier analysis and missing value analysis. IBM SPSS Statistics offers many useful facilities for outlier analysis. In this chapter, we looked at ways of generating histograms, percentiles, z-scores, and boxplots to gain an understanding of outliers. In addition, most procedures in IBM SPSS Statistics produce a simple summary table of valid and missing cases. We also saw how to look at missing value patterns and perform mean substitution. In the next chapter, we turn to visually exploring the data through charts.
