Preliminary Data Analysis and Data Preparation.doc

Preliminary Data Analysis and Data Preparation
Preliminary Data Analysis and Data Preparation
Session: January 22; 2010
Steps prior to data entry
Data editing: First ‘look’ at data to identify potential problems/correct them, in the field by interviewer and field supervisor
Errors, Inconsistencies, Ineligible Respondents, Systematic Missings -> early remedy?
Coding
Coding closed-ended questions involves specifying how the responses are to be entered
Open-ended questions are difficult to code
Set up Code Book with category labels and values?
Depends on type of MVA
In this session, we focus on steps after data entry…
Preliminary inspection
Identification of outliers
Missing data
Checking assumptions for MVA
Graphical inspection and simple
analyses
1 variable:
frequency table
simple statistics:
central tendency: mean, median, mode
dispersion: variance (stand1>.dev.), range
histogram
‘time series’ plot
2 variables:
scatterplot
correlation, cross-tab
Histogram
Histogram: Skewness of distribution?
Example: Shopping basket information (832 shoppers)
Bivariate analysis
Metric versus metric
Scatterplot, Pearson correlation
Non-metric versus non-metric
Cross-tab
Spearman correlation (Rho) or Kendall’s Tau

Pearson Correlation
Example: Shopper Data
Example: Simple Scatterplot
Cross-tab (1)
5
0
1
40
5
0
1
0
Ownership product A: 10% of respondents
Ownership product B: 90% of respondents
A
B
Cross-tabs (2):
Stockout Reactions per Brand Type
Rho and Tau
Useful to assess link between two ordinal variables
Examples:
Education (highest obtained)
Swimming certificate (highest obtained)
Categorically measured variables (. shopping frequency, e class, age category)
Example: e and Shopping Frequency (Categories)
Preliminary Data analysis: Summary
Obtain preliminary insights using univariate en bivariate analyses
First impression concerning missings, outliers and distributional properties ?? crucial before using