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Related Concept Videos

Multiple Bar Graph01:07

Multiple Bar Graph

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As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
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Bar Graph01:07

Bar Graph

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A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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Interpreting R Charts01:22

Interpreting R Charts

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
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Interpreting Run Charts01:25

Interpreting Run Charts

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Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
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Framing Effects03:26

Framing Effects

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Information is everywhere and its presentation—such as how and when items are presented—can impact our perceptions and decisions surrounding the info. This broad concept umbrellas framing effects—influences that occur due to the way information is framed in its appearance, whether it’s purely the order or the specific wording of a message. Let’s take a look at numerous ways in which two versions of something can objectively say the same thing, yet we respond in...
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Time-Series Graph00:54

Time-Series Graph

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Related Experiment Video

Updated: Sep 8, 2025

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
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Misleading graphs in context: Less misleading than expected.

Jannetje E P Driessen1, Daniël A C Vos2, Ionica Smeets1

  • 1Science Communication and Society, Leiden University, Leiden, Netherlands.

Plos One
|June 15, 2022
PubMed
Summary
This summary is machine-generated.

Context, not misleading graphs, significantly shapes opinions. This study found that graph literacy and a manipulated y-axis had no impact on how people perceived data trends.

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Area of Science:

  • Data Visualization
  • Cognitive Psychology
  • Information Design

Background:

  • Misleading graphs, particularly those with truncated y-axes, are a concern for data interpretation.
  • Limited understanding exists on how individuals interpret deceptive visualizations and their influence on opinions.
  • Graph literacy is hypothesized to affect susceptibility to misleading graphical information.

Purpose of the Study:

  • To investigate the impact of a misleading y-axis in line charts on public opinion.
  • To examine the role of context and individual graph literacy in the interpretation of data visualizations.
  • To determine how manipulated graphs influence estimations of data trends.

Main Methods:

  • A randomized controlled trial was conducted to compare interpretations of normal versus misleading line charts.
  • Participants were exposed to graphs within different contextual settings.
  • Data collected included opinions on trends, estimations of increase, and individual graph literacy assessments.

Main Results:

  • Contextual factors were the sole significant determinant of opinion formation regarding data trends.
  • Neither the presence of a misleading graph nor individual graph literacy levels affected participants' opinions.
  • No significant impact of graph type, context, or literacy was observed on estimations of data increase.

Conclusions:

  • Individuals may be less vulnerable to misleading graphs than previously assumed.
  • The surrounding context of a graph exerts a greater influence on opinion than a manipulated y-axis.
  • Further research is needed to fully understand the nuances of data visualization interpretation.