In this app, we explore salary distributions through a histogram (manually computed), boxplots, scatter plots, quantile plots, and a Q-Q plot. We also compare two salary datasets.
Interpretation:
The histogram shows a concentration of salaries at the lower end with a long tail towards the
higher salaries. This suggests that while most salaries are modest, a few high values (possibly
outliers) create a heavy tail.
Discussion:
Removing the outliers reduces the spread of the data and provides a clearer view of the
central tendency. The updated boxplot shows a more compact distribution with adjusted
quartiles.
Comparison Interpretation:
The scatter plot and boxplots show that while both datasets cover a similar range, their
distributions differ slightly. These differences are visible in their central tendencies and
spread.
Observations on the Quantile Plots:
The quantile plots display how the salary values progress across percentiles for each dataset.
- Vertical markers (default) are drawn at the 25th, 50th, and 75th percentiles.
- Horizontal markers show the salary values corresponding to these percentiles.
The interactive marker allows you to select any percentile to further explore the data.
Observation from the Q-Q Plot:
If the plotted points lie close to the 45-degree line, it indicates that the two datasets have
similar distributional characteristics. Deviations from this line suggest differences such as
heavier tails or shifts in the central location.