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Found 50 Skills
Expert-level research methodology, academic writing, statistical analysis, and scientific investigation
SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.
Expert in statistical analysis, predictive modeling, machine learning, and data storytelling to drive business insights.
Implements comprehensive backtesting capabilities for Pine Script indicators and strategies. Use when adding performance metrics, trade analysis, equity curves, win rates, drawdown tracking, or statistical validation. Triggers on "backtest", "performance", "metrics", "win rate", "drawdown", or testing requests.
Kpi Definition Helper - Auto-activating skill for Data Analytics. Triggers on: kpi definition helper, kpi definition helper Part of the Data Analytics skill category.
Data analysis, SQL queries, BigQuery operations, and data insights. Use for data analysis tasks and queries.
Comprehensive CSV data analysis and visualization tool. Use this skill when analyzing CSV files, generating data summaries, creating visualizations from data, detecting outliers, finding correlations, assessing data quality, or creating data reports. Triggers on CSV analysis, data exploration, data visualization, data profiling, statistical analysis, or data quality assessment requests.
Use when optimizing multi-factor systems with limited experimental budget, screening many variables to find the vital few, discovering interactions between parameters, mapping response surfaces for peak performance, validating robustness to noise factors, or when users mention factorial designs, A/B/n testing, parameter tuning, process optimization, or experimental efficiency.
Conduct statistical hypothesis testing including null/alternative hypothesis formulation, p-values, Type I/II errors, and test statistic selection. Use this skill when the user needs to determine whether a result is statistically significant, choose the right statistical test, interpret p-values correctly, or evaluate research findings — even if they say 'is this result significant', 'which statistical test should I use', or 'what does this p-value mean'.
Design and execute marketing A/B tests for landing pages, email campaigns, ad creatives, and pricing with proper test design and result analysis. Use this skill when the user needs to test marketing variations, improve conversion rates through experimentation, or decide between two campaign approaches — even if they say 'which version performs better', 'test this landing page', 'A/B test our email subject line', or 'should we change our CTA'.
Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Triggers on tasks involving: Bayesian inference, posterior sampling, hierarchical/multilevel models, GLMs, time series, Gaussian processes, BART, mixture models, prior/posterior predictive checks, MCMC diagnostics, LOO-CV, WAIC, model comparison, or causal inference with do/observe.
Data journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics or building data-driven stories. Essential for reporters, newsrooms and researchers working with quantitative information.