Quick start | First table | Delimiters and class limits | Objects of class fdt.multiple | Objects of class fdt_cat | Objects of class fdt_cat.multiple with subheadings | Quantiles estimated from grouped data | Custom numeric formatting | Table header in Portuguese | Takeaways

Overview | 1. Numerical data — fdt() | 1.1 Basic usage | 1.2 Choosing the number of classes | 1.3 Custom interval boundaries | 1.4 Formatting class limits | 1.5 Right-closed intervals | 1.6 Missing values | 2. Plots — plot.fdt.default() | 2.1 Absolute frequency histogram and polygon | 2.2 Relative frequency (proportion and percentage) | 2.3 Density | 2.4 Cumulative frequency | 2.5 Value labels on bars | 3. Summary statistics from grouped data | 4. Multiple numerical variables — fdt.data.frame() | 4.1 All numeric columns | 4.2 Grouped by a factor | 4.3 Plotting multiple tables | 4.4 Statistics on multiple tables | 5. Categorical data — fdt_cat() | 5.1 Basic usage | 5.2 Preserving natural order | 5.3 Formatting | 5.4 Plots for categorical data | 6. Reconstructing a table from frequencies | 7. LaTeX export | Session information

Overview | 1. Quick Start - Completely Randomized Design (CRD) | 2. Accepted Input Classes | 3. Unbalanced Data | 4. Randomized Complete Block Design (RCBD) | 5. Significance Level | 6. Factorial Experiment (FE) | 7. Split-Plot Experiment (SPE) | 8. Visualisation Options | 8.1 Dispersion bars | 8.2 Comparing all four options | 8.3 Boxplot | 9. Tabular Output | 10. Mixed Models with lme4 | References

Overview | Quick Start — Completely Randomized Design (CRD) | Accepted Input Classes | Unbalanced Data | Randomized Complete Block Design (RCBD) | Significance Level | Factorial Experiment (FE) | Split-Plot Experiment (SPE) | Visualisation Options | Tabular Output | Mixed Models with lme4 | References