by Data editing is defined as the process involving the review and adjustment of collected survey data. Data editing helps define guidelines that will reduce potential bias and ensure consistent estimates leading to a clear analysis of the data set by correct inconsistent data using the methods later in this article. The purpose is to control the quality of the collected data. Data editing can be performed manually, with the assistance of a computer or a combination of both.
Data analysis is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, while being used in different business, science, and social science domains. In today’s business, data analysis is playing a role in making decisions more scientific and helping the business achieve effective operation.
EDITING is the process of checking and adjusting responses in the completed questionnaires for omissions, legibility, and consistency and readying them for coding and storage.
Purpose of Editing
Purpose of Editing For consistency between and among responses. For completeness in responses– to reduce effects of item non-response. To better utilize questions answered out of order. To facilitate the coding process.
Basic Principles of Editing
- Checking of the no. of Schedules / Questionnaire)
- Completeness (Completed in filling of questions)
- Legibility.
- To avoid Inconstancies in answers.
- To Maintain Degree of Uniformity.
- To Eliminate Irrelevant Responses.
Types of Editing
- Field Editing
Preliminary editing by a field supervisor on the same day as the interview to catch technical omissions, check legibility of handwriting, and clarify responses that are logically or conceptually inconsistent.
Field editing is the preliminary editing of data by a field supervisor on the same day as the interview. Its purpose is to identify technical omissions, check legibility, and clarify responses that are logically or conceptually inconsistent.
When gaps are present from interviews, a call-back should be made rather than guessing what the respondent “would have probably said.”
A second important task of the supervisor is to re-interview a few respondents, at least on some pre-selected questions, as a validity check. In central or in-house editing, all the questionnaires undergo thorough editing. It is a rigorous job performed by central office staff.
- Office Editing
Editing performed by a central office staff; often done more rigorously than field editing.
Interactive editing
The term interactive editing is commonly used for modern computer-assisted manual editing. Most interactive data editing tools applied at National Statistical Institutes (NSIs) allow one to check the specified edits during or after data entry, and if necessary, to correct erroneous data immediately. Several approaches can be followed to correct erroneous data:
- Re-contact the respondent
- Compare the respondent’s data to his data from the previous year
- Compare the respondent’s data to data from similar respondents
- Use the subject matter knowledge of the human editor
Selective editing
Selective editing is an umbrella term for several methods to identify the influential errors, and outliers. Selective editing techniques aim to apply interactive editing to a well-chosen subset of the records, such that the limited time and resources available for interactive editing are allocated to those records where it has the most effect on the quality of the final estimates of published figures. In selective editing, data is split into two streams:
- The critical stream
- The non-critical stream
