Some Glaring Mistakes made by Researchers in Education in Statistical Analysis
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Transcript of Some Glaring Mistakes made by Researchers in Education in Statistical Analysis
Some Glaring Mistakes Seen in Statistical Analysis by
Researchers in Education
Madhavi DharankarAsst Prof, School of Education,
Data Analysis
Quantitative
Triangulation
Qualitative
Intra Inter
Data Analysis: Some Observations
• Raw data and frequency tables are given in chapters
• Percentages, graphs, means taken as stats techniques
• Meaningless innumerable graphs
Conceptual Confusions Leading to Mistakes in Analysis
Doctoral Level Analysis based solely on Percentages
Findings based on Superficial Differences between the Groups
Comparison of Two Different Groups
Calculations NOT based on Gained Scores
Pre Post Gained Scores
Expt
Control
Observations
• Lack of Identifying Points of – qualitative analysis– Triangulation– Taking analysis to higher level - mixing data
• Lack of Reasoning on– Nature of data– Choice of appropriate stats technique– Strengths and limitations of a technique
Taking Analysis Further
• ‘Discussion of Results’ missing
• Difference between findings and conclusions not clear
• Predictions based on analysis
Arguments with the Researchers (and the Guides)
• “I have not done the calculations. Statistician has done it for me.”
• “He has used SPSS, computers as a statistical techniques.” – A guide
Does use of software and/ or help of a statistician mean saying goodbye to the basic understanding of analysis in research?
Crossing limits of findings
Questions Researchers Could Ask Themselves
• Why am I drawing a graph? How is it taking the understanding about the number ‘further’?
• What am I achieving through it, which otherwise cannot be achieved?
• What am I drawing attention to through this graph?
• What is the nature of data?• What does it demand?• Reading between the numbers
Measures at Institutional Level
• University– Rigor underlined– Evaluation of thesis by subject expert as well as
statistician (analysis expert)– Presentations completely focused on analysis– Formal inputs of stats to both students and
guides• Collaborations
– Periodical workshops for M Phil and Ph D research scholars with statisticians
– Analysis clinics (Dr Anil Gore)
Discussions!!!
Thank you