Statistics and plotting

Is my treatment different from my control?

Which of my conditions differ from each other?

Does one measurement predict the other?

Do these categories occur at different rates?

What n do I need for this experiment?

I ran thousands of tests — which results are real?

How should I show this data instead of a bar chart?

How do I plot fold change against significance?

How do I visualise an expression matrix?

How do I make a diagram of my model?

Compare two groups and get the effect size and interval, not just a p-value.

Adjust a list of p-values by Benjamini–Hochberg or Bonferroni.

Compare three or more groups, with variance explained and every pair tested.

Pearson or Spearman with a confidence interval on r, plus a fitted line.

Compare counts across categories, with the odds ratio and its interval.

How many replicates you need — worked out before the experiment, not after.

Free statistics software with both classical and Bayesian tests.

The default statistics and graphing package in experimental biology.

Free point-and-click statistics built on R, with a spreadsheet front end.

Estimation plots: effect size with confidence interval, not just a p-value.

The statistical environment nearly all biological methods are written for.

Power analysis and sample size calculation for the standard tests.

Plots every replicate and every experiment, instead of hiding both in a bar.

Volcano plots from a results table, with labelling and thresholds you control.

Interactive heatmaps with clustering, in the browser.

Scientific diagrams and schematics from a large library of biological icons.

Long-established commercial statistics package, common in clinical research.

Commercial statistics package strong in epidemiology and survival analysis.

Free web platform covering a very wide range of biological plot types.

Free vector editor for assembling and labelling multi-panel figures.