Establishing Validity and Interpretation of Data deepa ict product.docx

Establishing Validity and Interpretation of Data

The data, collected for research, has to be processed, analyzed and interpreted to develop a solution to the research question.

Validity

Validity refers to how accurately a method measures what it is intended to measure. If research has high validity that means it produces results that correspond to real properties, characteristics, and variations in physical or social world.

High reliability is one indicator that a measurement is valid. If a method is not reliable, it probably isn’t valid

Types of Validity

The followings are the types of validity

Content Validity

A qualitative type of validity where the domain of the concept is made clear and the analyst judge whether the measures fully represent the domain (Bollen, 1989, p.185)

The empirical indicators should be proven to be logically and theoretically related to the construct

Face validity

Subjective judgment on a construct operationalization (eg; choosing to measure an employee work efficiency based on punctuality only)

Concurrent Validity

The ability of a test to predict time event/outcome; the measure and the criterion co-exist at the same time.

Predictive Validity

Ability of a test to measure a future time event/outcome (eg; student GMAT score and MBA program GPA/completion)

Construct Validity

The empirical assessment of the degree to which empirical indicators adequately measure the construct

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Interpretation of Data

Data interpretation refers to the process of using diverse analytical methods to review dat and arrive at relevant conclusions.

Meaning of data interpretation

Establish inter connection between and among data
Check for indicators whether hypothesis are supported or not by findings
Link the present findings with the previous literature

Following are the Interpretation of data given below

Figures 1

Graphs

Figures 2

Diagrams Figures

Figures 3

Charts

Figures 4

Table

Sl no	Class divisions	Total Students Number of girls number of boys number
1	10A	40 12 28

2	10B	32 10 12

Method of data interpretation

Direct visual observations of raw data
After organizing the data in tables
After making Graphical representations
After using numerical/statistical methods
After mathematical modeling

Conclusion

Validity and Interpretation of data closely related. Validity is proving data status and interpretation is analyzing data in various methods. it’s two methods provides quality of data

Reference

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