PPT: Data Interpretation | Quantitative Techniques for CLAT PDF Download

 Page 1


Data 
Iterpretatio
Page 2


Data 
Iterpretatio
Data Iterpretatio
Data interpretation assigns meaning to analyzed information and 
determines its significance and implications.
It involves processes to review data for arriving at informed 
conclusions.
Data mapping should be done properly due to multiple sources.
Analysis is usually s u b j e c t i v e with varying goals.
Two main types: quantitative and qualitative.
Page 3


Data 
Iterpretatio
Data Iterpretatio
Data interpretation assigns meaning to analyzed information and 
determines its significance and implications.
It involves processes to review data for arriving at informed 
conclusions.
Data mapping should be done properly due to multiple sources.
Analysis is usually s u b j e c t i v e with varying goals.
Two main types: quantitative and qualitative.
Type of Scale of Meaureet
Noial Scale
Consists of non-numeric categories that cannot be ranked or compared 
quantitatively. Variables are exclusive and exhaustive.
Ordial Scale
Includes categories that are exclusive and exhaustive but with a logical order. 
Examples: quality ratings and agreement ratings.
Iterval Scale
Groups data into categories with orderly and equal distances. Always has an 
arbitrary zero point.
Ratio Scale
Combines features of all three types.
Page 4


Data 
Iterpretatio
Data Iterpretatio
Data interpretation assigns meaning to analyzed information and 
determines its significance and implications.
It involves processes to review data for arriving at informed 
conclusions.
Data mapping should be done properly due to multiple sources.
Analysis is usually s u b j e c t i v e with varying goals.
Two main types: quantitative and qualitative.
Type of Scale of Meaureet
Noial Scale
Consists of non-numeric categories that cannot be ranked or compared 
quantitatively. Variables are exclusive and exhaustive.
Ordial Scale
Includes categories that are exclusive and exhaustive but with a logical order. 
Examples: quality ratings and agreement ratings.
Iterval Scale
Groups data into categories with orderly and equal distances. Always has an 
arbitrary zero point.
Ratio Scale
Combines features of all three types.
Iterpretig Data
Aalyi Coideratio
Analysts must differentiate between correlation, 
causation, and coincidences.
Two main methods: qualitative and quantitative analysis.
Qualitative Data Iterpretatio
Narrative data collected through person-to-person 
techniques.
Described as 'categorical' with descriptive context 
rather than numerical values.
Page 5


Data 
Iterpretatio
Data Iterpretatio
Data interpretation assigns meaning to analyzed information and 
determines its significance and implications.
It involves processes to review data for arriving at informed 
conclusions.
Data mapping should be done properly due to multiple sources.
Analysis is usually s u b j e c t i v e with varying goals.
Two main types: quantitative and qualitative.
Type of Scale of Meaureet
Noial Scale
Consists of non-numeric categories that cannot be ranked or compared 
quantitatively. Variables are exclusive and exhaustive.
Ordial Scale
Includes categories that are exclusive and exhaustive but with a logical order. 
Examples: quality ratings and agreement ratings.
Iterval Scale
Groups data into categories with orderly and equal distances. Always has an 
arbitrary zero point.
Ratio Scale
Combines features of all three types.
Iterpretig Data
Aalyi Coideratio
Analysts must differentiate between correlation, 
causation, and coincidences.
Two main methods: qualitative and quantitative analysis.
Qualitative Data Iterpretatio
Narrative data collected through person-to-person 
techniques.
Described as 'categorical' with descriptive context 
rather than numerical values.
Tecique for Data 
Collectio
Obervatio
Analyzing behavior patterns, such as time spent on 
activities and communication used.
Docuet
Documentation resources classified based on the material 
they contain.
Iterview
Most effective for collecting narrative data, allowing 
grouping by themes for focused data segmentation.