| In survey research, data cleaning is a crucial step to ensure
the accuracy and reliability of the results. This involves identifying and correcting
errors, inconsistencies, and missing data in the survey responses. However, the goal of
data cleaning is not to remove non-matching or doubtful answers to improve the analyst's
conclusions. Instead, it aims to ensure that the data accurately reflects the respondents'
attitudes and behaviors, and that the analysis is based on a valid and representative
sample, see example. Regarding
the examples we provided, analyzing Internet surfing behavior in a company may involve
collecting data through surveys or other means, and then using statistical techniques to
identify patterns and factors that distinguish "spiders" from non-surfing
colleagues. This may involve analyzing demographic and job-related variables, as well as
examining the frequency and duration of website visits. However, it is important to ensure
that the data collection and analysis methods are valid and reliable, and that the
conclusions drawn are based on sound statistical principles. To find the answer,... |
![[IMAGE]](salgsn.gif)
