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This graph is misleading because it did not start at 0 on the Y axis.

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This graph is misleading because it starts at 24 not 0, making Willy B's Coffee look better than the others

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This graph is misleading because it has no title.

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Already explained

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This graph is misleading by wanting you to think that Michael has got way more by doubling the size as well.

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This graph is misleading. Firstly it has no title and secondly there is no scale at all, so we don't know how big the gap actually is

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This is misleading because the horses are bigger than the res

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This graph is misleading because you can see the McDonalds is like 8 times bigger than BurgerKing

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This graph is about how much candy two people collected. It is misleading because the candy isn't the same size so it looks like Michael collected way more than Shayna.

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A article says that Apple's iPad in these advertising photos are untrue, the sizes are different.
Apparently they got sued for this to.

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This graph is misleading because the y axis doesn't start at zero

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It is misleading by not having a title or lables

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This is a misleading graph because there is no title and no numbers to explain how much

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this graph is misleading because it dose not start with 0 and it starts at 75 not 0 to 5 then it should be less spaced

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This graph talks about the amount of people in each political party that agrees with court.
This graph is misleading because it doesn't start with 0 and because it doesn't have percentages that add up to 100% (the maximum amount is only supposed to be 100%). It also doesn't tell you what they are agreeing or disagreeing about (what topic it is).

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this graph is misleading because the candy is bigger than the other one

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This graph is misleading because they have left out the title and they have also not put the number of percent of on the pie chart. The graph is made on an angle in 3D form making item D look way larger than it should be in truth Item B is almost the same size as item D.

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this display is misleading because they d\show you the graph and make you think the par is high but it really isn't

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This graph is misleading because it starts at 249000 along the y axis instead of starting at

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This graph misleads by not starting at zero on the y axis

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I assume this graph is about how someone divides their 24 hour day.
It is misleading because it has no title.

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In statistics, a misleading graph, also known as a distorted graph, is a graph that misrepresents data, constituting a misuse of statistics and with the result that an incorrect conclusion may be derived from it.

Graphs may be misleading by being excessively complex or poorly constructed. Even when constructed to display the characteristics of their data accurately, graphs can be subject to different interpretations, or unintended kinds of data can seemingly and ultimately erroneously be derived.

Misleading graphs may be created intentionally to hinder the proper interpretation of data or accidentally due to unfamiliarity with graphing software, misinterpretation of data, or because data cannot be accurately conveyed. Misleading graphs are often used in false advertising. One of the first authors to write about misleading graphs was Darrell Huff, publisher of the 1954 book How to Lie with Statistics.

The field of data visualization describes ways to present information that avoids creating misleading graphs.

It [a misleading graph] is vastly more effective, however, because it contains no adjectives or adverbs to spoil the illusion of objectivity, there's nothing anyone can pin on you.

There are numerous ways in which a misleading graph may be constructed.

The use of graphs where they are not needed can lead to unnecessary confusion/interpretation. Generally, the more explanation a graph needs, the less the graph itself is needed. Graphs do not always convey information better than tables.

The use of biased or loaded words in the graph's title, axis labels, or caption may inappropriately prime the reader.

Fabricated trends

Similarly, attempting to draw trend lines through uncorrelated data may mislead the reader into believing a trend exists where there is none. This can be both the result of intentionally attempting to mislead the reader or due to the phenomenon of illusory correlation.

Comparing pie charts of different sizes could be misleading as people cannot accurately read the comparative area of circles.

The usage of thin slices, which are hard to discern, may be difficult to interpret.

The usage of percentages as labels on a pie chart can be misleading when the sample size is small.

Making a pie chart 3D or adding a slant will make interpretation difficult due to distorted effect of perspective. Bar-charted pie graphs in which the height of the slices is varied may confuse the reader.

3D Pie chart slice perspective

A perspective (3D) pie chart is used to give the chart a 3D look. Often used for aesthetic reasons, the third dimension does not improve the reading of the data; on the contrary, these plots are difficult to interpret because of the distorted effect of perspective associated with the third dimension. The use of superfluous dimensions not used to display the data of interest is discouraged for charts in general, not only for pie charts. In a 3D pie chart, the slices that are closer to the reader appear to be larger than those in the back due to the angle at which they're presented. This effect makes readers less performant in judging the relative magnitude of each slice when using 3D than 2D

Item C appears to be at least as large as Item A in the misleading pie chart, whereas in actuality, it is less than half as large. Item D looks a lot larger than item B, but they are the same size.

Edward Tufte, a prominent American statistician, noted why tables may be preferred to pie charts in The Visual Display of Quantitative Information:

Tables are preferable to graphics for many small data sets. A table is nearly always better than a dumb pie chart; the only thing worse than a pie chart is several of them, for then the viewer is asked to compare quantities located in spatial disarray both within and between pies - Given their low data-density and failure to order numbers along a visual dimension, pie charts should never be used.

Using pictograms in bar graphs should not be scaled uniformly, as this creates a perceptually misleading comparison. The area of the pictogram is interpreted instead of only its height or width. This causes the scaling to make the difference appear to be squared.

In the improperly scaled pictogram bar graph, the image for B is actually 9 times as large as A.

The perceived size increases when scaling.

The effect of improper scaling of pictograms is further exemplified when the pictogram has 3 dimensions, in which case the effect is cubed.

The graph of house sales (left) is misleading. It appears that home sales have grown eightfold in 2001 over the previous year, whereas they have actually grown twofold. Besides, the number of sales is not specified.

An improperly scaled pictogram may also suggest that the item itself has changed in size.

Assuming the pictures represent equivalent quantities, the misleading graph shows that there are more bananas because the bananas occupy the most area and are furthest to the right.

Logarithmic scaling

Logarithmic (or log) scales are a valid means of representing data. But when used without being clearly labeled as log scales or displayed to a reader unfamiliar with them, they can be misleading. Log scales put the data values in terms of a chosen number (the base of the log) to a particular power. The base is often e (2.71828...) or 10. For example, log scales may give a height of 1 for a value of 10 in the data and a height of 6 for a value of 1,000,000 (10 ⁶) in the data. Log scales and variants are commonly used, for instance, for the volcanic explosivity index, the Richter scale for earthquakes, the magnitude of stars, and the pH of acidic and alkaline solutions. Even in these cases, the log scale can make the data less apparent to the eye. Often the reason for the use of log scales is that the graph's author wishes to display vastly different scales on the same axis. Without log scales, comparing quantities such as 10 ³ versus 10 ⁹ becomes visually impractical. A graph with a log scale that was not clearly labeled as such, or a graph with a log scale presented to a viewer who did not know logarithmic scales, would generally result in a representation that made data values look of similar size, in fact, being of widely differing magnitudes. Misuse of a log scale can make vastly different values (such as 10 and 10,000) appear close together (on a base-10 log scale, they would be only 1 and 4). Or it can make small values appear to be negative due to how logarithmic scales represent numbers smaller than the base.

Misuse of log scales may also cause relationships between quantities to appear linear whilst those relationships are exponentials or power laws that rise very rapidly towards higher values. It has been stated, although mainly in a humorous way, that "anything looks linear on a log-log plot with thick marker pen" .

Both graphs show an identical exponential function of f( x) = 2x. The graph on the left uses a linear scale, showing clearly an exponential trend. The graph on the right, however uses a logarithmic scale, which generates a straight line. If the graph viewer were not aware of this, the graph would appear to show a linear trend.

A truncated graph (also known as a torn graph) has a y axis that does not start at 0. These graphs can create the impression of important change where there is relatively little change.

While truncated graphs can be used to overdraw differences or to save space, their use is often discouraged. Commercial software such as MS Excel will tend to truncate graphs by default if the values are all within a narrow range, as in this example. To show relative differences in values over time, an index chart can be used. Truncated diagrams will always distort the underlying numbers visually. Several studies found that even if people were correctly informed that the y-axis was truncated, they still overestimated the actual differences, often substantially.

These graphs display identical data; however, in the truncated bar graph on the left, the data appear to show significant differences, whereas, in the regular bar graph on the right, these differences are hardly visible.

There are several ways to indicate y-axis breaks:

Changing the y-axis maximum affects how the graph appears. A higher maximum will cause the graph to appear to have less volatility, less growth, and a less steep line than a lower maximum.

Changing the ratio of a graph's dimensions will affect how the graph appears.

The scales of a graph are often used to exaggerate or minimize differences.

The lack of a starting value for the y axis makes it unclear whether the graph is truncated. Additionally, the lack of tick marks prevents the reader from determining whether the graph bars are properly scaled. Without a scale, the visual difference between the bars can be easily manipulated.

Though all three graphs share the same data, and hence the actual slope of the ( x, y) data is the same, the way that the data is plotted can change the visual appearance of the angle made by the line on the graph. This is because each plot has a different scale on its vertical axis. Because the scale is not shown, these graphs can be misleading.

The intervals and units used in a graph may be manipulated to create or mitigate change expression.

Graphs created with omitted data remove information from which to base a conclusion.

In the scatter plot with missing categories on the left, the growth appears to be more linear with less variation.

In financial reports, negative returns or data that do not correlate with a positive outlook may be excluded to create a more favorable visual impression.[citation needed ]

The use of a superfluous third dimension, which does not contain information, is strongly discouraged, as it may confuse the reader.

The third dimension may confuse readers[9]

The blue column in the front appears larger than the green column in the back due to perspective, despite having the same value

When scaling in three dimensions, the effect of the change is cubed

Graphs are designed to allow easier interpretation of statistical data. However, graphs with excessive complexity can obfuscate the data and make interpretation difficult.

Poorly constructed graphs can make data difficult to discern and thus interpret.

Misleading graphs may be used in turn to extrapolate misleading trends.

Several methods have been developed to determine whether graphs are distorted and to quantify this distortion.

where

A graph with a high lie factor (>1) would exaggerate change in the data it represents, while one with a small lie factor (>0, <1) would obscure change in the data. A perfectly accurate graph would exhibit a lie factor of 1.

where

The graph discrepancy index, also known as the graph distortion index ( GDI), was originally proposed by Paul John Steinbart in 1998. GDI is calculated as a percentage ranging from −100% to positive infinity, with zero percent indicating that the graph has been properly constructed and anything outside the ±5% margin is considered to be distorted. Research into the usage of GDI as a measure of graphics distortion has found it to be inconsistent and discontinuous, making the usage of GDI as a measurement for comparisons difficult.

The data-ink ratio should be relatively high. Otherwise, the chart may have unnecessary graphics.

The data density should be relatively high, otherwise a table may be better suited for displaying the data.

Graphs are useful in the summary and interpretation of financial data. Graphs allow trends in large data sets to be seen while also allowing the data to be interpreted by non-specialists.

Graphs are often used in corporate annual reports as a form of impression management. In the United States, graphs do not have to be audited, as they fall under AU Section 550 Other Information in Documents Containing Audited Financial Statements.

Several published studies have looked at the usage of graphs in corporate reports for different corporations in different countries and have found frequent usage of improper design, selectivity, and measurement distortion within these reports. The presence of misleading graphs in annual reports have led to requests for standards to be set.

Research has found that while readers with poor levels of financial understanding have a greater chance of being misinformed by misleading graphs, even those with financial understanding, such as loan officers, may be misled.

The perception of graphs is studied in psychophysics, cognitive psychology, and computational visions.

1. Tufte, Edward R. (2006). The visual display of quantitative information (4th print, 2nd ed.). Cheshire, Conn.: Graphics Press. p. 178. ISBN 9780961392147.

2. Whitbread, p. 150

3. ^ Few, Stephen (August 2007). "Save the Pies for Dessert" (PDF). Visual Business Intelligence Newsletter. Perceptual Edge.

4. Rumsey, p. 156.

5. Utts, pp. 146-147.

6. ^ Hanel, Paul H.P.; Maio, Gregory R.; Manstead, Antony S. R. (2019). "A New Way to Look at the Data: Similarities Between Groups of People Are Large and Important". Journal of Personality and Social Psychology. 116 (4): 541-562. doi:10.1037/pspi0000154. PMC . PMID 30596430.

7. ^ Moore, David S.; Notz, William (9 November 2005). Statistics: Concepts And Controversies. Macmillan. pp. 189-190. ISBN 978-0-7167-8636-8.

8. ^ Smith, Charles Hugh (29 Mar 2011). "Extrapolating Trends Is Exciting But Misleading". Business Insider.

9. Fulkerson, Cheryl Linthicum; Marshall K. Pitman; Cynthia Frownfelter-Lohrke (June 1999). "Preparing financial graphics: principles to make your presentations more effective". The CPA Journal. 69 (6): 28-33.

10. ^ McNelis, L. Kevin (June 1, 2000). "Graphs, An Underused Information Presentation Technique". The National Public Accountant. 45 (4): 28-30.(subscription required)

11. ^ Mohd Isa, Rosiatimah (2006). "The incidence and faithful representation of graphical information in corporate annual report: a study of Malaysian companies". Technical Report. Institute of Research, Development and Commercialization, Universiti Teknologi MARA. Archived from the original on 2016-08-15. Also published as: Mohd Isa, Rosiatimah (2006). "Graphical Information in Corporate Annual Report: A Survey of Users and Preparers Perceptions". Journal of Financial Reporting and Accounting. 4 (1): 39-59. doi:10.1108/19852510680001583.

12. ^ Beattie, Vivien; Jones, Michael John (2008). "Corporate reporting using graphs: a review and synthesis". Journal of Accounting Literature. 27: 71-110. ISSN 0737-4607.

13. Christensen, David S.; Albert Larkin (Spring 1992). "Criteria For High Integrity Graphics". Journal of Managerial Issues. Pittsburg State University. 4 (1): 130-153. JSTOR 40603924.

14. ^ Steinbart, P. (September 1989). "The Auditor's Responsibility for the Accuracy of Graphs in Annual Reports: Some Evidence for the Need for Additional Guidance". Accounting Horizons: 60-70.

A discussion of misleading graphs, Mark Harbison, Sacramento City College

Robbins, Naomi B. (2005). Creating more effective graphs. Hoboken, N.J.: Wiley-Interscience. ISBN 9780471698180.

Goundar, Nadesa (2009). "Impression Management in Financial Reports Surrounding CEO Turnover" (PDF). Masters Dissertation. Unitec Institute of Technology. hdl:10652/1250.

Harvey, J. Motulsky (June 2009). "The Use and Abuse of Logarithmic Axes" (PDF). GraphPad Software Inc. Archived from the original on 2010-11-23.

Mather, Paul; Ramsay, Alan; Steen, Adam (1 January 2000). "The use and representational faithfulness of graphs in Australian IPO prospectuses". Accounting, Auditing & Accountability Journal. 13 (1): 65-83. doi:10.1108/09513570010316144. Archived from the original on 2012-07-09.

Galliat, Tobias (Summer 2005). "Visualisierung von Informationsräumen" (PDF). Fachhochschule Köln, University of Applied Sciences Cologne. Archived from the original (PDF) on 2006-01-04.

Carvalho, Clark R.; McMillan, Michael D. (September 1992). "Graphic Representation in Managerial Decision Making: The Effect of Scale Break on the Dependent Axis" (PDF). AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH.

Johnson, R. Rice; Roemmich, R. (October 1980). "Pictures that Lie: The Abuse of Graphs in Annual Reports". Management Accounting: 50-56.

Davis, Alan J. (1 August 1999). "Bad graphs, good lessons". ACM SIGGRAPH Computer Graphics. 33 (3): 35-38. doi:10.1145/330572.330586. Archived from the original on 2000-03-05.

Louwers, T.; Radtke, R; Pitman, M. (May-June 1999). "Please Pass the Salt: A Look at Creative Reporting in Annual Reports". Today's CPA: 20-23.

Lane, David M.; Sándor, Anikó (1 January 2009). "Designing better graphs by including distributional information and integrating words, numbers, and images" (PDF). Psychological Methods. 14 (3): 239-257. doi:10.1037/a0016620. PMID 19719360.

Campbell, Mary Pat (Feb 2010). "Spreadsheet Issues: Pitfalls, Best Practices, and Practical Tips". Actuarial Practice Forum. Archived from the original on 2019-04-23.

Arocha, Carlos (May 2011). "Words or Graphs?". The Stepping Stone. Archived from the original on 2019-04-23.

# data[].attributes.attachment_link.description
In statistics, a misleading graph, also known as a distorted graph, is a graph that misrepresents data, constituting a misuse of statistics and with the result that an incorrect conclusion may be derived from it. Graphs may be misleading by being excessively complex or poorly constructed.

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This graph is about people who prefer  PS or Xbox

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This graph is about average scores in math in 2003. This graph is misleading because instead of starting at 0 it starts at 299.

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This graph is about the percent who agreed in court. The different options were Democrafts, Republicans and indepenedents.
This graph misleads you by skipping numbers and starting at 50 instead of 0.

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This graph is about who agreed with court or not

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this graph is about the massive increase in house prices this year. The graph is misleading because it started at 79 thousand and went up by 1 thousand dollars when 1999 is only bigger by 2 grand.

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This graph is misleading because some of the icons are not touching the x axis

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This is a  computer score
This is misleading because the graph is starting on 95.5

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This graph is misleading because it doesn't start at zero along the y axis.

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this graph is misleading because it docent start at 0.

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This graph misleads by not showing you the title and not starting at 0 on the y axis.

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This graph is about ticket prices for a baseball game and basketball a game. The different options were the price for a baseball game and the price for a basketball game. The graph is misleading because the ball for a basketball game in 2001 is way bigger than all the rest   so it looks way expensive than other ones.

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This graph is is about the bowling averages by Diana, Hilde and Emily. The graph is misleading because the scale along the Y axis does not start at 0, which makes the differences seem larger than they really are.

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this graph is about number of adult frogs in south pond, the options are May and September. the misleading thing is both of the frogs are different sizes

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this graph is about the bowling Averages of there score in a bowling game

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The graph is about ticket prices for baseball and basketball games from 1991 to 2001. In 1991 the tickets for baseball were only $10 and in 2001 they only jumped up by $10 but they make it seem like It was a major increase by making the next ball more than twice the size of the previous. This continues with basketball as well.

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This graph is about the massive increase in house prices. This graph is misleading because it was adding up by $1000 each time and it didn't show the starting number which was 79,000 on the y axis.

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The graph is about the favourite foods of 2914 people. The different options were pizza, hotdogs or hamburgers
The graph is misleading because the scale along the y-axis has not started at 0, therefore the zooming in the graphs makes the differences seem larger than what they really are.