Science & Research
Research Methods & Data Analysis skills assessment
Researchers turn questions into evidence. This scorecard covers study design, statistical analysis, programming, reproducibility and interpretation.
- 12 skills to score
- 1–10 scale on every skill
- 6 starting levels
The 12 Research Methods & Data Analysis skills you can score
These are the default Research Methods & Data Analysis skills in SkillScorer. Each one is scored from 1 to 10 for every researcher, and you can edit, remove or add skills at any time.
Research Question and Hypothesis
Develops clear, testable research questions and hypotheses.
Experimental and Study Design
Designs studies with appropriate controls, sample sizes and methods.
Statistical Analysis
Chooses and applies appropriate tests.
Programming for Analysis
Uses programming languages such as R or Python to analyse data.
Data Management and Reproducibility
Organises and documents data and code so analyses can be repeated.
Critical Appraisal of Literature
Evaluates published research for quality, bias and relevance.
Interpreting Results
Interprets results carefully and avoids overstating conclusions.
Visualisation
Presents data in clear, honest charts and figures.
Research Ethics and Integrity
Follows research ethics and integrity rules and reports honestly.
Collaboration
Works with co-researchers and shares data and credit fairly.
Scientific Writing
Writes papers and reports clearly and concisely.
Peer Review Skills
Reviews colleagues' work fairly and constructively.
Levels included with Research Methods & Data Analysis
Research Methods & Data Analysis starts with 6 levels, which SkillScorer calls “Seniority Level” for science & research, so researchers can be grouped and compared fairly. Rename, reorder or replace them at any time.
- Student
- Research Assistant
- Scientist
- Senior Scientist
- Group Leader
- Director
How Research Methods & Data Analysis works in SkillScorer
Score
Each researcher in a lab is scored on the Research Methods & Data Analysis skills in the Skills Matrix: tap a cell, type a score, and it saves itself.
Compare
Rank researchers, compare two side by side, or compare your labs against each other to see exactly where the strengths and gaps are.
Track
Scores are kept year after year, so you can see who is improving and which Research Methods & Data Analysis skills need attention. Reports also follow each group leader's lab.
Research Methods & Data Analysis scorecard: common questions
What skills does the Research Methods & Data Analysis scorecard include?
SkillScorer's Research Methods & Data Analysis scorecard covers 12 skills: Research Question and Hypothesis, Experimental and Study Design, Statistical Analysis, Programming for Analysis, Data Management and Reproducibility, Critical Appraisal of Literature, Interpreting Results, Visualisation, Research Ethics and Integrity, Collaboration, Scientific Writing and Peer Review Skills. Each one comes with a written description of what it measures, and you can edit, rename, remove or add skills to suit your organisation.
How are researchers scored in Research Methods & Data Analysis?
Every researcher is scored from 1 to 10 on each skill (1 = Poor, 5 = Average, 10 = Elite), one lab and year at a time. Scores autosave in the Skills Matrix, and the 18 built-in reports turn them into rankings, radar charts, skill gaps and year-on-year trends.
Which levels come with Research Methods & Data Analysis?
Research Methods & Data Analysis starts with these levels (called “Seniority Level” in the app): Student, Research Assistant, Scientist, Senior Scientist, Group Leader and Director. They are just a starting point, so you can rename, reorder or replace them.
Can I change the Research Methods & Data Analysis skills and wording?
Yes. The skills, levels and labels are all editable per organisation. In science & research the app talks about researchers, labs and group leaders, and you can change any of those words too.
Score Research Methods & Data Analysis with SkillScorer
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