2.12
条形图
条形图也称为柱状图，是由相互分离的条形所组成的。它使用水平条形或垂直条形来比较不同类别。其中的条形也可以是矩形，也可以是矩形框（用于三维图）。图表中的一个轴能够用来表示被比较的具体类别，另一个坐标轴则用来表示离散值。在这种图表中中，每个类别的条形长度与每个类别中的个体数量或百分比是成正比的。一些条形…
请记住，定性数据代表非数值型变量，例如不同的发色、车辆类型，或大学提供的各类课程。
例如，考虑一个频率表，其中列出了每门课程的注册学生人数——统计学、生物学、物理学和化学。
此类定性数据可以通过条形图进行可视化展示。
定性数据的类别——即不同的课程——沿横轴表示，而频数或学生人数则沿纵轴给出。
然后，绘制宽度相等的条形，连接各个类别及其对应的学生人数。这些条形的高度表示不同类别的频数。
第一个条形表示有五名学生注册了统计学课程，第二个条形表示有三名学生注册了生物学课程，依此类推。这些条形可以相邻排列，也可以在它们之间留有间隙。
View the full transcript and gain access to JoVE Core videos
Q1: What type of data is best represented using a bar graph?
Bar graphs are ideal for displaying qualitative data, which represent non-numerical variables such as hair colors, vehicle types, or college courses. They effectively compare categorical information by showing frequencies or counts for each category along the vertical axis, with categories displayed horizontally. This makes bar graphs superior to line graphs for categorical rather than continuous data.
Q2: How are the axes organized in a bar graph?
In a bar graph, one axis represents the specific categories being compared, while the other axis shows discrete values or frequencies. Typically, categories are placed along the horizontal axis and frequencies along the vertical axis. The bar height is proportional to the number or percentage of individuals in each category, allowing easy visual comparison of relative sizes across groups.
Q3: What is the difference between a bar graph and a histogram?
A bar graph displays categorical data with bars separated by gaps, making it suitable for comparing distinct categories like course enrollments. A histogram, by contrast, represents continuous numerical data with adjacent bars showing frequency distributions across intervals. Bar graphs are the better choice when data is categorical rather than continuous, allowing clear comparison of category sizes.
Q4: Can bar graphs display multiple data series simultaneously?
Yes, bar graphs can display multiple data series through grouped bar graphs, where bars are clustered in groups of more than one to compare different variables across categories. Additionally, stacked bar graphs divide bars into subparts to show cumulative effects across categories. These variations allow complex comparisons while maintaining clarity in categorical data visualization.
Q5: What are Pareto charts and how do they relate to bar graphs?
Pareto charts are bar graphs organized from highest to lowest frequency values, prioritizing the most significant categories first. This arrangement helps identify which categories have the greatest impact or frequency. Pareto charts maintain the standard bar graph structure with categories on one axis and frequencies on the other, but emphasize relative importance through ordering.
Q6: How do you construct a bar graph from frequency data?
To construct a bar graph, place categories along the horizontal axis and frequencies along the vertical axis. Draw bars of equal width for each category, with bar height corresponding to the frequency count. Bars can be positioned with or without gaps between them. This visual representation makes it easy to compare enrollment numbers or other categorical frequencies at a glance.
Q7: Why might you choose a bar graph over other visualization methods?
Bar graphs are preferred for categorical data because they clearly show comparisons among distinct categories and effectively display the relative size of each group. Unlike line graphs, which suggest continuity, or histograms, which show continuous distributions, bar graphs isolate and emphasize differences between separate categories, making them ideal for qualitative data analysis.