Visualizations are a powerful tool for sharing insights gained from data analysis. In our previous article, we discussed box plots and histograms. In this article, we will continue our exploration of data visualizations by examining line and scatter plots. Both line plots and scatter plots are graphs used to display the relationship between data.
Line Plots
Line plots are good for visualizing changes in numeric variables over time; they are particularly useful for showing how a variable (most of the time a continuous variable) changes over a given period of time.
Where line plots are used
- Temperature changes (average change) over a period of time.
- The sales trends of a product over time.
- Stock market trends over time (performance of different companies).
- Population change over a period of time.
In order to present data clearly and succinctly, line plots are used in many disciplines, including statistics, economics, finance, and science.
Scatter Plots
Scatter plots, on the other hand, are great for visualizing relationships between two numeric variables. The scatter plot can be used to identify patterns in the data and to investigate the strength of the relationship between the two numeric variables.
A pair of values for each of the two variables is represented by a point on the plot. It is simpler to determine whether there is a relationship between the two variables and what kind of relationship it is by looking at the distribution of points on the plot (e.g., positive correlation, negative correlation, or no correlation).
Where scatter plots are used
Scatter plots are useful in many fields, including statistics, data analysis, and scientific research, to identify patterns and relationships in the data.
Some examples are
- Age vs Income
- Weight vs Height
- Study Hours vs Grade/Scores
- Acceleration vs Time
- Birth Rate vs Life Expectancy
In conclusion, both line plots and scatter plots are useful tools for investigating and discussing conclusions drawn from data analysis. It is simpler to spot trends, patterns, and linkages in the data by utilizing these representations than it could be by simply looking at a table of numbers.