Data distortion

What is Data Distortion? Data distortion is the deviation of data from its true or most accurate representation of the full picture; bad data may interject incorrect or misguided “facts” into useful information or, worse, into models and predictions of customers or business.

1. What are examples of distorted data?
2. What is it called when data is misleading?
3. What causes distortion in data visualization?
4. What's distortion?
5. Can graphs distort data?
6. How can data be misinterpreted?
7. What are irregularities in data?
8. What is an example of misleading statistical data?
9. What is an example of misleading?
10. What are the four main types of distortion?
11. What is distortion in data communication?
12. What causes distortion?
13. What is distortion effect?
14. What is distortion and types of distortion?
15. Can statistics be distorted or manipulated?
16. What is one common way of misrepresenting data?
17. What are 3 ways a graph can be misleading?
18. What are examples of misleading statistics?
19. What is an example of bad data visualization?
20. What is an example of poor data visualization?
21. How does bad data occur give an example?
22. What is a statistical fallacies?
23. What is bad quality data?
24. What is the most common problem in data visualization?
25. What are 4 characteristics of data visualization?
26. What are the four stages of data visualization?
27. What are the two basic types of data visualization?
28. What is poor data collection?

What are examples of distorted data?

A melted crayon or your reflection in a broken mirror (similar to the cover photo) are examples of distortion. In the case of data, some claim that any change to an original dataset is distortion — even when done without bias.

What is it called when data is misleading?

Misleading statistics refers to the misuse of numerical data either intentionally or by error. The results provide deceiving information that creates false narratives around a topic.

What causes distortion in data visualization?

The distortion caused by poor axis scaling is a by-product of the way we read visualizations. Axis labels require conscious attention to interpret: We have to actively read these numbers to make sense of them. However, when we look at a visualization, we form the gist of a visual scene unconsciously.

What's distortion?

: the act of twisting or altering something out of its true, natural, or original state : the act of distorting. a distortion of the facts. : the quality or state of being distorted : a product of distorting: such as. physics : a lack of proportionality in an image resulting from defects in the optical system.

Can graphs distort data?

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.

How can data be misinterpreted?

Factual information must have integrity, objectivity and accuracy. Yet it is important to recognize that information can be misinterpreted by personal bias, inaccurate statistics, and even by the addition of fictional data.

What are irregularities in data?

By data irregularity we essentially mean situations when the distribution of data points, the sampling of data space for generating the training set, and also the features describing each data point deviate from what could have been ideal, being biased, skewed, incomplete and/or misleading.

What is an example of misleading statistical data?

In 2007, toothpaste company Colgate ran an ad stating that 80% of dentists recommend their product. Based on the promotion, many shoppers assumed Colgate was the best choice for their dental health. But this wasn't necessarily true. In reality, this is a famous example of misleading statistics.

What is an example of misleading?

An advertisement states that a product is 'free'. An extra payment is mentioned in the fine print. The advertisement is likely to be misleading. An advertisement states that a discount promotion is 'storewide' or 'X% off all products'.

What are the four main types of distortion?

There are four main types of distortion that come from map projections: distance, direction, shape and area. The Mercator projection, for example, distorts Greenland because of its high latitude, in the sense that its shape and size are not the same as those on a globe.

What is distortion in data communication?

Distortion – It means changes in the form or shape of the signal. This is generally seen in composite signals made up with different frequencies. Each frequency component has its own propagation speed travelling through a medium.

What causes distortion?

The cause of distortion is the overload of amplifying a signal. A loudspeaker or a microphone has a transducer that converts energy into another form of energy. In this case, it transforms electrical signals into mechanical movements to create sound.

What is distortion effect?

Distortion effects simulate the distortion created by vacuum tubes, transistors, or digital circuits. Vacuum tubes were used in audio amplifiers before the development of digital audio technology. They are still used in musical instrument amplifiers today.

What is distortion and types of distortion?

In general, there are five types of harmonic distortion that can be observed when looking at a waveform: Amplitude distortion. Frequency distortion. Phase distortion. Intermodulation distortion.

Can statistics be distorted or manipulated?

Statistics are extensively used in studies, organizations, media, and politics. Most of the time, it is presented without the background information necessary for its correct interpretation. Sometimes misleading data is presented with a deliberate intention to manipulate people and to prompt an agenda.

What is one common way of misrepresenting data?

This is one of the most common way graphs misrepresent data: by distorting the scale. Zooming in a small portion of the y-axis exaggerate a barely detectable difference, and it is especially misleading in bar graphs, since we assume the difference in the size of the bars is proportional to the values.

What are 3 ways a graph can be misleading?

The Vertical scale is too big or too small, or skips numbers, or doesn't start at zero. The graph isn't labeled properly. Data is left out.

What are examples of misleading statistics?

In 2007, toothpaste company Colgate ran an ad stating that 80% of dentists recommend their product. Based on the promotion, many shoppers assumed Colgate was the best choice for their dental health. But this wasn't necessarily true. In reality, this is a famous example of misleading statistics.

What is an example of bad data visualization?

Using the wrong graphs/charts for their particular purpose. Not making the best use out of colors. Creating misleading graphs/charts. Trying to incorporate too much information in one graph.

What is an example of poor data visualization?

A bad graph is constructed in a way that does not convey data in a manner that is clear to the audience. For example, a graph may not have labels for one or both axes. The person who created the graph may have done it unintentionally, but it is still considered a bad data visualization example.

How does bad data occur give an example?

Bad data is an inaccurate set of information, including missing data, wrong information, inappropriate data, non-conforming data, duplicate data and poor entries (misspells, typos, variations in spellings, format etc). There's many reasons data can be rejected going through a process.

What is a statistical fallacies?

That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.

What is bad quality data?

Poor quality data is inaccurate data. It can take several forms: Missing contact fields (phone numbers, emails, physical addresses, etc.) Outdated information (old job titles, changes caused by mergers and acquisitions, etc.) Data entered in the wrong field.

What is the most common problem in data visualization?

Make a profound point with a single visualization. The problem? Humans aren't well equipped to compute the meaning of multiple values abstracted in visual form. When visualizations include too much data, information overwhelms, and data melts into a graphic soup that most viewers can't stomach.

What are 4 characteristics of data visualization?

Accurate: The visualization should accurately represent the data and its trends. Clear: Your visualization should be easy to understand. Empowering: The reader should know what action to take after viewing your visualization. Succinct: Your message shouldn't take long to resonate.

What are the four stages of data visualization?

These stages are exploration, analysis, synthesis, and presentation.

What are the two basic types of data visualization?

There are two basic types of data visualization: static and interactive. Static visualizations are something like an infographic, a single keyhole view of a particular data story.

What is poor data collection?

Poor data collection means that you do not have access to a smart, objective analysis that can study the data and be able to derive informative results out of it.