Exploratory Data Analysis is the first look at our data. It includes Missing Value Analysis to see if missing data has systematic patterns that need explanation or whether they are Missing At Random (MAR) or Missing Completely at random (PCAR) processes. For example, doe we have systematic bias in missing responses from one particular demographic?
Besides this, this is our first look at the variables of our study – often summarizing important information around means, variations and other distributional characteristics. This is also when we start looking at outliers in our data.
This also alerts us to potential problems in the data – for example, is the variation across scale questions too less for some respondents? Is there a potential scale use bias among different demographics?