ds@mcpanalytics.aiA data scientist you can email your data and question to, and get a reliable response. Not AI slop.A data scientist you can email. Not AI slop.
Upload a CSV, pick the outcome you care about and the factors that might move it, and get a full regression report — coefficients, confidence intervals, driver ranking, and diagnostics. Free.
Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size, so sign up to analyze your full dataset.
Fitting the regression model...
Sent to . Inside: coefficient estimates with confidence intervals, driver ranking, interactive charts, R code, and AI insights.
Analyze another fileThe practical guide behind this tool: when it applies, how to read the output, and the traps that make it say the wrong thing.
Linear regression finds the straight-line relationship that best explains your outcome from the drivers you pick. Each driver gets a coefficient — the expected change in the outcome per one-unit increase in that driver, holding the others constant — plus a confidence interval and a significance test that separates real signal from noise. The report also ranks drivers by influence and checks the model's assumptions with residual diagnostics.
Use it when you have a numeric outcome (sales, cost, score, time) and want to know which factors move it and by how much.
Not ideal for yes/no outcomes (use logistic regression) or heavily non-linear relationships (tree-based models capture those better).
Built for: Analysts, marketers, and operators who need to know which levers move a number
Typical data source: Any spreadsheet or CSV export with a numeric outcome column and candidate driver columns
Any table where one numeric column is the outcome you care about and other columns might explain it. For example, weekly sales vs marketing spend:
Minimum 20 rows · Best with 100-10,000 rows and 1-8 drivers
Explains any numeric outcome from the driver columns you choose, using ordinary least squares regression. Coefficient estimates with 95% confidence intervals and significance, driver ranking by statistical influence, and full model diagnostics.
See the shape and range of your outcome before reading any effects.
Each driver's effect size with a 95% confidence interval and significance stars — the heart of the analysis.
All drivers ranked by statistical influence, so you know what matters most.
The strongest driver plotted against your outcome, showing the relationship the model found.
How closely the model's predictions track reality.
Prediction errors across the range — the honesty check on the linear model.
Plain-English interpretation of what the numbers mean, what's significant, and what to do next.
Which of our spend channels actually moves revenue — and by how much per dollar?
Map revenue as the outcome and each channel's spend as drivers. The coefficient table tells you the incremental effect of each channel, with confidence intervals that show which effects are statistically real.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
Run any analysis on your own data: R analyses, interactive reports, AI insights, and PDF export.
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Bring your own data and the question you actually need answered.
CympleData Scientist Send me your data and question, I’ll send you the analytics. ds@mcpanalytics.ai
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