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what is mound shaped symmetrical

by Dusty Feeney DVM Published 2 years ago Updated 1 year ago

What is mound shaped symmetrical? For a symmetrical distribution, the mean is in the middle; if the distribution is also mound - shaped , then values near the mean are typical. But if a distribution is skewed, then the mean is usually not in the middle.

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And if you have a graph like that where it goes up and then has a long tail or anything along thoseMoreAnd if you have a graph like that where it goes up and then has a long tail or anything along those lines. That's not going to be symmetrical mound shaped distribution.

Full Answer

What do you mean by a mound-shaped symmetric distribution?

For a symmetrical distribution, the mean is in the middle; if the distribution is also mound-shaped, then values near the mean are typical. But if a distribution is skewed, then the mean is usually not in the middle. Example: The mean of the ten numbers 1, 1, 1, 2, 2, 3, 5, 8, 12, 17 is 52/10 = 5.2.Oct 12, 2016

What is mound shape?

For data with a roughly bell-shaped (mound-shaped) distribution, About 68% of the data is within 1 standard deviation of the mean. About 95% of the data is within 2 standard deviations of the mean. About 99.7% of the data is within 3 standard deviations of the mean.

What is a mound-shaped histogram?

In the histogram and dot plot, this shape is referred to as being a "bell shape" or a "mound". The most typical symmetric histogram or dot plot has the highest vertical column in the center. This shape is often referred to as being a "normal curve" (or normal distribution).

Is at distribution mound-shaped?

Like the normal, t-distributions are always mound-shaped. III. The t-distributions have less spread than the normal, that is, they have less probability in the tails and more in the center than the normal.

Is every symmetric distribution unimodal?

Distributions don't have to be unimodal to be symmetric. They can be bimodal (two peaks) or multimodal (many peaks). The following bimodal distribution is symmetric, as the two halves are mirror images of each other.Sep 18, 2013

What are mounds in statistics?

Although the "mound" of values occurs in the left portion of the distribution, it is the tail of the distribution, extending to the right and containing extremely large values, that determines the skewness of the distribution.

What does a symmetric histogram look like?

The histogram displays a symmetrical distribution of data. A distribution is symmetrical if a vertical line can be drawn at some point in the histogram such that the shape to the left and the right of the vertical line are mirror images of each other. The mean, the median, and the mode are each seven for these data.

What is skewed right?

A "skewed right" distribution is one in which the tail is on the right side. A "skewed left" distribution is one in which the tail is on the left side. The above histogram is for a distribution that is skewed right.

What is true with regard to both mound-shaped and uniform frequency distributions?

In a uniform distribution , all of the intervals have approximately equal frequencies. A mound-shaped distribution is approximately symmetrical. The frequencies of the intervals generally increase from each end toward the distribution's center.

What is the shape of an asymmetric distribution?

An asymmetric distribution exhibits skewness. In contrast, a Gaussian or normal distribution, when depicted on a graph, is shaped like a bell curve and the two sides of the graph are symmetrical.

What is au shaped distribution?

A U-Shaped distribution is a bimodal distribution with frequencies that steadily fall and then steadily rise. There is a higher chance of a measurement being found at the extremes than in the center of the distribution. Cyclical and sinusoidal measurements are usually in distributed in U-shapes (Bucher, 2012).Jan 29, 2017

What is left skewed?

In statistics, a negatively skewed (also known as left-skewed) distribution is a type of distribution in which more values are concentrated on the right side (tail) of the distribution graph while the left tail of the distribution graph is longer.

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