## What is an example of symmetrical data?

A symmetrical distribution is one where splitting the data down the middle produces mirror images. Bell curves are a commonly-cited example of symmetrical distributions.

**What is an example of a symmetrical distribution?**

Standardized test scores are an example of a symmetrical distribution. The mean, median, and mode of the data set will all occur at the same value.

### What is symmetric in statistics?

In statistics, a symmetric distribution is a distribution in which the left and right sides mirror each other. The most well-known symmetric distribution is the normal distribution, which has a distinct bell-shape.

**How do you find symmetric in statistics?**

If the data are symmetric, they have about the same shape on either side of the middle. In other words, if you fold the histogram in half, it looks about the same on both sides. Histogram C in the figure shows an example of symmetric data. With symmetric data, the mean and median are close together.

#### What is asymmetric data?

The term data asymmetry refers to any occasion when there a disparity in access to data. In all cases this results in the data steward being able to unlock more value than a contributor.

**What are the types of symmetry in statistics?**

Mean, Mode and Median in a Symmetric Distribution In a symmetric distribution, the mean, mode and median all fall at the same point. The mode is the most common number and it matches with the highest peak (the “mode” here is different from the “mode” in bimodal or unimodal, which refers to the number of peaks).

## What are the rules of symmetry?

If a graph does not change when reflected over a line or rotated around a point, the graph is symmetric with respect to that line or point. The following graph is symmetric with respect to the x-axis (y = 0). Note that if (x, y) is a point on the graph, then (x, – y) is also a point on the graph.

**Which of the following distribution is symmetrical?**

The correct answer is (C) Normal distribution. The normal distribution is a probability distribution symmetric about its mean.

### What is an example of a asymmetric communication?

Asymmetric Digital Subscriber Line (ADSL) is an example of asymmetric communications. ADSL technology transmits digital information at a high bandwidth on existing phone lines.

**Is the distribution symmetric or skewed?**

A distribution is said to be symmetrical when the distribution on either side of the mean is a mirror image of the other. In a symmetrical distribution, mean = median = mode. If a distribution is non-symmetrical, it is said to be skewed.

#### What is an example of a symmetric distribution?

Example 1 (Symmetric, Bell-Shaped Distribution) The bell curve below is perfectly symmetric, because it can be divided into two halves (a left half and a right half) that are mirror images of each other. Think of it as a “smoothed-out” histogram. Example 2 (Approximately Symmetric Distribution: Presidents’ Ages)

**How do you know if the distribution is perfectly symmetric?**

If the skewness of S is zero then the distribution represented by S is perfectly symmetric. If the skewness is negative, then the distribution is skewed to the left, while if the skew is positive then the distribution is skewed to the right (see Figure 1 below for an example). where x̄ is the mean and s is the standard deviation of S.

## How do you know if the data set is symmetric?

The mean is slightly greater than the median. This would indicate that the data set is skewed right. The median is slightly closer to the third quartile than the first quartile. This would indicate that the data set is skewed left. Since these differences are so small and since they contradict each other, we conclude that the data set is symmetric.

**How symmetric is the distribution of computer ownership?**

This is a fairly symmetric distribution (“fairly symmetric” implies that it may not be perfectly symmetric, but at least it’s not very skewed). The distribution is basically normal, and you see one single group. Table 3.5.2. Rates of Computer Ownership