This video discusses type of graphs and when it’s appropriate to use each one.

For more help, check out our Data and Graphs Lessons Page

Credit goes to MooMooMath and Science

## Different Types of Graphs and When To Use Them

Graphs are powerful tools for visually representing data, allowing for easier interpretation and analysis. There are several types of graphs, each with its own characteristics and best use cases. Below, I’ll explain in detail the most common types of graphs and when you should use each of them

### Line Graphs

- Line graphs are used to display data points over a continuous interval or time period.
- They are particularly useful for showing trends and changes over time.
- Use line graphs when you want to visualize the relationship between two continuous variables, such as temperature over time, stock prices, or population growth.

### Bar Graphs

- Bar graphs represent data using rectangular bars of different heights or lengths.
- They are effective for comparing discrete categories or groups.
- Use bar graphs when you want to compare the frequency, count, or magnitude of different categories, such as sales figures for different products, population of different cities, or scores in a survey.

### Histograms

- Histograms are similar to bar graphs but are used specifically for displaying the distribution of continuous data.
- They consist of contiguous bars with no gaps between them, representing intervals of values rather than distinct categories.
- Histograms are useful for visualizing the frequency or probability distribution of data, such as the distribution of ages in a population or the distribution of test scores.

### Pie Charts

- Pie charts represent data as a circular graph divided into slices, with each slice representing a proportion of the whole.
- They are ideal for showing the relative proportions of different categories within a dataset.
- Pie charts should be used when you want to illustrate the composition of a whole, such as market share percentages, budget allocation, or demographic distribution.

### Scatter Plots

- Scatter plots display individual data points as dots on a two-dimensional graph, with one variable on the x-axis and another on the y-axis.
- They are useful for visualizing the relationship between two continuous variables and identifying patterns or correlations.
- Scatter plots are particularly effective for detecting trends, clusters, or outliers in data, such as the relationship between height and weight, or between temperature and ice cream sales.

### Area Charts

- Area charts are similar to line graphs but with the area below the line filled in with color.
- They are used to represent cumulative totals or stacked values over time.
- Area charts are suitable for showing trends and changes over time while also emphasizing the magnitude of values, such as tracking the cumulative revenue of a company over several quarters.

### Box-and-Whisker Plots

- Box-and-whisker plots, also known as box plots, provide a visual summary of the distribution of a dataset.
- They display the median, quartiles, and potential outliers of the data.
- Box plots are helpful for comparing distributions, identifying central tendency and variability, and detecting outliers in a dataset, especially when dealing with large datasets or multiple groups.

### Heatmaps

- Heatmaps use color-coding to represent data values in a matrix format, with each cell color indicating the intensity of the value.
- They are effective for visualizing large datasets or matrices and identifying patterns or trends.
- Heatmaps are commonly used in fields such as data analysis, biology, and finance to display correlations, clustering, or spatial distributions of data.

### Radar Charts

- Radar charts, also known as spider charts or web charts, display multivariate data on a two-dimensional graph with multiple axes radiating from a central point.
- They are useful for comparing the performance or characteristics of multiple entities across several variables.
- Radar charts are commonly used in sports analytics, market research, and decision-making processes to visualize strengths and weaknesses across different criteria or attributes.

### Network Graphs

- Network graphs, or graphs, represent relationships between interconnected nodes or entities.
- They consist of nodes (representing entities) and edges (representing connections or relationships between nodes).
- Network graphs are ideal for visualizing complex relationships, such as social networks, transportation systems, or biological interactions.

Choosing the appropriate type of graph depends on the nature of the data you want to visualize and the insights you want to communicate. Consider factors such as the type of variables (continuous or categorical), the purpose of the visualization, the audience, and the context in which the data will be interpreted when selecting a graph type. Additionally, it’s important to ensure that the chosen graph accurately and effectively represents the underlying data without misleading or distorting the information.