SW: The W statistic of a Shapiro-Wilk test ranges from 0 to 1, where 1 indicates perfect normality. The p-value reflects the probability of observing such a W value under the hypothesis of normality.
Skew: Measures asymmetry of the data distribution (positive = right-tailed, negative = left-tailed).
Kurtosis: Tail heaviness compared to normal distribution (high = heavy tails, low = light tails).
Median: Middle value when data is sorted.
Mean: Average value of all data points.
Std: Standard deviation (spread of data around the mean).
CV: Coefficient of variation (std/mean, relative variability independent of scale).
Q-Q Plot:
Compares your data against a theoretical distribution. Points following the diagonal reference line indicate a good match. Deviations show where your data differs from the theoretical model.
Histogram:
Shows the frequency distribution of your data as bars, with a theoretical distribution overlaid as a gray line. The height of bars represents how many data points fall in each bin range. Compare bar heights to the theoretical line to see how well your data matches the expected distribution.
Distributions:
Select different theoretical distributions from the list to overlay them for comparison with your data. This helps identify which distribution type best fits your data.
Navigation:
↑↓ / j/k: Scroll through distributions to compare different overlays
s: Toggle histogram scale (Linear ↔ Log)
Esc: Return to distribution table
Settings:
Scale: Toggle between Linear and Log scale for histogram
(Log scale requires positive values only)
Warning color indicates scale fallback (e.g., Log selected but Linear used due to negative values)