Getting Started Data Studio Statistical Analysis Auto Modeling SEM Lab Network Analysis Surveys Security & Privacy Developers Reference

01 Get started

Getting started with statistical analysis

Statistical analysis overview Start an analysis Find an analysis for your research question Run several analyses with Analysis Recipes

02 Prepare your data

Preparing the data to analyse

Upload data Understand variable types and roles Check missing values and outliers Review your data before analysis

03 Run an analysis

The six steps of an analysis

Step 1 · Variables Step 2 · Settings Step 3 · Validation Step 4 · Summary Step 5 · Interpretation Step 6 · Statistical Details

04 Understand your results

Checking and using the result

Read assumption tests and diagnostics Read tables and charts Review AI interpretations Report results in a paper Change settings and rerun an analysis

05 Save and manage your work

Reports and exporting results

Save tables and charts Download an analysis report View the R and Python code Save and manage analysis results

Analysis reference

Analysis methods

Explore Compare Relationships and prediction Survival analysis Econometrics Structural analysis Clustering Time Series

Statistical Analysis›Check missing values and outliers

Check missing values and outliers

What breaks quietly, and what to do about it before the run.