Data editing involves checking data for errors or inconsistencies. It occurs at different stages of data collection and processing. There are several techniques used for data editing including checking for valid and complete data, duplicate entries, outliers, and logical inconsistencies. Editing ensures data accuracy and coherence, and provides the best possible data for analysis. It is an important part of cleaning data and enhancing quality for statistical analysis. The editing process involves transforming raw data into a comprehensible form by first editing the data, then coding it to draw inferences. Editing improves data quality for effective coding and statistical analysis. However, data editing has limitations based on the resources and scope of each study.

1. EDITING

2. • Data editing is the application of checks to detect missing,
invalid or inconsistent entries or to point to data records that
are potentially in error.
• No matter what type of data you are working with, certain
edits are performed at different stages or phases of data
collection and processing.

3. TECHNIQUES OF DATA EDITING
• Validity and Completeness of Data
• Duplicate data entry.
• Outliers
• Logical inconsistencies

4. BENEFITS OF EDITING
• To ensure the accuracy of data
• To ensure the coherence of aggregated data
• To obtain the best possible data available
• To determine whether the data are complete

5. IMPORTANCE OF EDITING
• Cleaning up data is an imperative aspect of enhancing data
quality for statistical analysis purposes.
• The process of cleaning up data to ensure and verify its
accuracy is called data editing. Currently, data editing is an
under-described, albeit immensely important, component of
the data collection process.

6. STEPS IN EDITING
• When the researcher collects the data it is in raw form and it
needs to be edited, organized and analyzed. The raw data
needs to be transformed into a comprehensible form of data.

7. • The first steps in this process are to edit the data.
• The edited data is then coded and inferences are drawn

8. EDITING METHODS
• Editing is the process of selecting and preparing written,
photographic, visual, audible, or cinematic material used by a
person or an entity to convey a message or information

9. Interrelation of Editing and Coding
• A researcher should classify the raw data into some purposeful
and usable categories.
• Coding operation is usually done at this stage through which
the categories of data are transformed into symbols that may
be tabulated and counted
• . Editing is the procedure that improves the quality of the data
for coding.

10. Example of Editing in Reasearch
• Modifying your short story, cutting out some lines and adding
others, is one example of editing.

11. Purpose Of Editing
• Editing removes errors
• Improves your work flow
• Enhances your language and style

12. LIMITATIONS OF EDITING
• Data editing has its limitations with the capacity and resources
of any given study. These determinants can have a positive or
negative impact on the post-analysis of the data set. Below are
several determinants of data editing