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That paper includes an example of frequency aliasing dating back to 1922. The first published use of the term "aliasing" in this context is due to Blackman and Tukey in 1958. [ 5 ] In their preface to the Dover reprint [ 6 ] of this paper, they point out that the idea of aliasing had been illustrated graphically by Stumpf [ 7 ] ten years prior.
More relevant to frequency estimations but still a possible cause of the frequency illusion, the split-category effect is the phenomenon in which, when events are split into smaller subcategories, this can increase the predicted frequency of occurrence. [10] An example of this is asking a person to predict the number of dogs in a country or ...
The feature integration theory provides explanation for illusory conjunctions; because features exist independently of one another during early processing and are not associated with a specific object, they can easily be incorrectly combined both in laboratory settings, as well as in real life situations. [8]
For example, when getting to know others, people tend to ask leading questions which seem biased towards confirming their assumptions about the person. However, this kind of confirmation bias has also been argued to be an example of social skill; a way to establish a connection with the other person. [9]
Aliasing is an automatic and unavoidable result of observing such a fraction. [3] [4] The aliasing properties of a design are often summarized by giving its resolution. This measures the degree to which the design avoids aliasing between main effects and important interactions. [5]
Visualization of Simpson's paradox on data resembling real-world variability indicates that risk of misjudgment of true causal relationship can be hard to spot. Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined.
The shutter behavior of the camera influences aliasing, as the overall shape of the exposure over time determines the band-limiting of the system before sampling, an important factor in aliasing. A temporal anti-aliasing filter can be applied to a camera to achieve better band-limiting and reduce the wagon-wheel effect. [2]
For example, a factory that is lit from a single-phase supply with basic lighting will have a flicker of 100 or 120 Hz (depending on country, 50 Hz x 2 in Europe, 60 Hz x 2 in US, double the nominal frequency), thus any machinery rotating at multiples of 50 or 60 Hz (3000–3600rpm) may appear to not be turning, increasing the risk of injury to ...