some glaring mistakes made by researchers in education in statistical analysis

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Some Glaring Mistakes Seen in Statistical Analysis by Researchers in Education Madhavi Dharankar Asst Prof, School of Education, YCMOU [email protected]

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The presentation discusses a few examples of the commonly made mistakes by researchers in education in statistical analysis.

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Page 1: 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,

[email protected]

Page 2: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Data Analysis

Quantitative

Triangulation

Qualitative

Intra Inter

Page 3: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Data Analysis: Some Observations

• Raw data and frequency tables are given in chapters

• Percentages, graphs, means taken as stats techniques

• Meaningless innumerable graphs

Page 4: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Conceptual Confusions Leading to Mistakes in Analysis

Page 5: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis
Page 6: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Doctoral Level Analysis based solely on Percentages

Page 7: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Findings based on Superficial Differences between the Groups

Page 8: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Comparison of Two Different Groups

Page 9: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Calculations NOT based on Gained Scores

Pre Post Gained Scores

Expt

Control

Page 10: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

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

Page 11: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Taking Analysis Further

• ‘Discussion of Results’ missing

• Difference between findings and conclusions not clear

• Predictions based on analysis

Page 12: Some Glaring Mistakes made by Researchers in Education in Statistical 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?

Page 13: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Crossing limits of findings

Page 14: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

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

Page 15: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

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)

Page 16: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Discussions!!!

Page 17: Some Glaring Mistakes made by Researchers in Education in Statistical Analysis

Thank you