The Pre-Analysis Data Cleaning & Preparation Steps

Before actually analyzing data to answer questions such as the CEO’s queries above, you will need to assess the data for integrity, clean any obvious errors and mistakes, and prepare the data for final analysis. These checks may include:
  1. Initial data assessment and cleaning. Notice the following in Figure 6.1 First lines of initial dataset:
    1. Size of the fifth respondent is captured as “Bigg,” obviously a typographical error.
    2. The “Satisfaction03” score for Respondent 2 is captured as a “55”, but this is supposed to be a 1-7 scale.
    3. These are data entry mistakes. While easy to spot in such a small with the eye, you’ll not see this in a bigger table easily. Mis-entered data can seriously impact any analysis.
  2. Missing data: There is missing data; we need to assess and possibly deal with this as discussed in Chapter 4.
  3. Multi-item scales assessing trust and satisfaction: We need to assess and aggregate these into single measures of the variables if possible.
We need to pre-assess and clean our data. We usually do these sorts of assessments through basic descriptive statistics and variable associations. Therefore, the next four chapters will sequentially discuss the following:
  • Chapter 6 discusses how to create, change and manipulate data, as well as give an overview of some other topics. To do things like create aggregated variables from multi-item scales, we’ll need these skills.
  • Chapter 7 discusses the essential descriptive statistics we use for single variables.
  • Chapter 8 discusses basic measures of variable association.
  • Chapter 9 discusses using these analyses in an initial set of steps for the purposes of data checking, cleaning, and preparation.
Last updated: April 18, 2017
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