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 DEAR STUDENTS,

WELCOME TO THE TOPIC ESTABLISHING VALIDITY AND INTERPRETATION OF DATA

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LEARNING OUTCOMES

You will be able to interpret the outcomes of applying the techniques to the data. So that they answer the research questions that gave rise to them. This interpretation will include analysis of the validity of the answer to the research question in the light of the nature of the data and techniques used.  

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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

1.      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

2.      Face validity

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

3.      Concurrent Validity

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

4.      Predictive Validity

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

5.      Construct Validity

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

        

Interpretation of Data

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

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 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

 

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