It's obviously part of the lethogram which is used to measure ciramic units.
You draw a series of line segments joining the points which would be the middle of the top of each bar of the histogram.
NO where!
bimodal histogram is a histogram where there are two clear high points on the graph. ex.) age of people at a preschool play group. There would be preschool age and adult age. Not many teenagers or elderly. Bimodal...the ages representing preschool and adult (parents?) would stand above the rest
A histogram is used to analyze a distribution of data. It look like a graph and can be used in many formats - the most popular may be in Photography, showing the distribution of shadows and light in a visual representation.
In many cases, histograms help interpretations. But you can probably think of cases where this is not true. Perhaps you have too few values. Perhaps your data has many flaws or errors in it. Sometimes, people will select the data that they want think supports their idea, and make histograms using only this data. See related link on histogram.
You draw a series of line segments joining the points which would be the middle of the top of each bar of the histogram.
As a visual representation of data, then a histogram is a way of analysing data.
NO where!
A histogram
bimodal histogram is a histogram where there are two clear high points on the graph. ex.) age of people at a preschool play group. There would be preschool age and adult age. Not many teenagers or elderly. Bimodal...the ages representing preschool and adult (parents?) would stand above the rest
All that histogram equalization does is remap histogram components on the intensity scale. To obtain a uniform (­at) histogram would require in general that pixel intensities be actually redistributed so that there are L groups of n=L pixels with the same intensity, where L is the number of allowed discrete intensity levels and n is the total number of pixels in the input image. The histogram equalization method has no provisions for this type of (arti®cial) redistribution process.
No. That would be a histogram.
Choosing wider class boundaries would cause a histogram of the data to present the appearance of a uniform distribution. This is because the data points within each wider class would be spread out more evenly, giving the histogram a more uniform look.
A histogram is used to analyze a distribution of data. It look like a graph and can be used in many formats - the most popular may be in Photography, showing the distribution of shadows and light in a visual representation.
In many cases, histograms help interpretations. But you can probably think of cases where this is not true. Perhaps you have too few values. Perhaps your data has many flaws or errors in it. Sometimes, people will select the data that they want think supports their idea, and make histograms using only this data. See related link on histogram.
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