Data Analysis

Data Analysis

1. To reduce info for explanations and patters

   • Framework for analysis
     • Assembling data (collect data)
     • Coding data (make it specific)
     • Comparing data (compare categories)
       • LISA SANCHEZ
     • Building meanings and interpretations
     • Reporting the outcome
       • Trustworthy conclusions
         • Keep pedagogical focus
         • Different sources of info
         • Immerse yourself in the data
         • Maintain objectivity and perspective
         • Focus on practical theory

2. Qualitative data

   • Analysis without numbers
     • Categorizing
       • Inductive coding
       • Deductive coding
     • Analyzing talk
       • General characterization
       • Identify apparent features
       • Focus on structural elements
       • Developing a description

3. Quantitative data

   • Numerical form
     • Numerical scales
       • Nominal (categorizing numbers by groups)
       • Ordinal (ordering data across a continuum of numbers)
       • Interval (ranking numbers but describing the interval or distance between them)
     • Descriptive statistics
       • Measures of central tendency (data around a central point)
         • Mean (average)
         • Medium (middle)
         • Mode (most frequent number)
       • Measures of dispersion (concise description of the distribution)
         • Range (the spread across all the numbers)
         • Standard deviation