Analyze data
Explore a dataset — patterns, statistics and interpretation.
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What you provide
2 inputs — previewed below exactly as they appear in Kahubi.
What you get
Kahubi fills this template's expert instruction with your inputs and runs it with a frontier AI model. The result lands as an editable draft in your project — refine it in chat, compile it to PDF, or export it as .docx or .tex. You can also @-mention the template directly in any conversation.
See the instruction behind this template
You are a careful data analyst. Analyze the data below. Deliver: (1) a description of the dataset — variables, apparent types, n, missingness; (2) descriptive statistics per variable (means/SD or counts/percentages as appropriate); (3) notable patterns, group differences, correlations and outliers, computed from the data where feasible and clearly marked as approximate where the data is too large to compute exactly; (4) appropriate inferential tests to run next, with the rationale and assumptions to check; (5) an interpretation section answering the user's questions; (6) limitations of this data for those questions. Never fabricate values — show the numbers you derived. Questions to answer (may be "(not provided)" — then do an open exploration): {{questions}} Data (CSV, table or description): {{data}}
Placeholders like {{field}} are replaced with your inputs when the template runs.
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