answersLogoWhite

0

The data point is close to the expected value.

User Avatar

Wiki User

10y ago

What else can I help you with?

Continue Learning about Statistics

How many of scores will be within 1 standard deviation of the population mean?

Assuming a normal distribution 68 % of the data samples will be with 1 standard deviation of the mean.


What do you get with mean minus std dev?

When you subtract the standard deviation from the mean, you get a value that represents one standard deviation below the average of a dataset. This can be useful for identifying lower thresholds in data analysis, such as determining the cutoff point for values that are considered below average. In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, so this value can help in understanding the spread of the data.


What does one standard deviation mean?

Standard deviation is a measure of variation from the mean of a data set. 1 standard deviation from the mean (which is usually + and - from mean) contains 68% of the data.


What is the purpose of finding the standard deviation of a data set?

The purpose of obtaining the standard deviation is to measure the dispersion data has from the mean. Data sets can be widely dispersed, or narrowly dispersed. The standard deviation measures the degree of dispersion. Each standard deviation has a percentage probability that a single datum will fall within that distance from the mean. One standard deviation of a normal distribution contains 66.67% of all data in a particular data set. Therefore, any single datum in the data has a 66.67% chance of falling within one standard deviation from the mean. 95% of all data in the data set will fall within two standard deviations of the mean. So, how does this help us in the real world? Well, I will use the world of finance/investments to illustrate real world application. In finance, we use the standard deviation and variance to measure risk of a particular investment. Assume the mean is 15%. That would indicate that we expect to earn a 15% return on an investment. However, we never earn what we expect, so we use the standard deviation to measure the likelihood the expected return will fall away from that expected return (or mean). If the standard deviation is 2%, we have a 66.67% chance the return will actually be between 13% and 17%. We expect a 95% chance that the return on the investment will yield an 11% to 19% return. The larger the standard deviation, the greater the risk involved with a particular investment. That is a real world example of how we use the standard deviation to measure risk, and expected return on an investment.


In research how to define standard deviation?

Standard deviation shows how much variation there is from the "average" (mean). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values.

Related Questions

When a data set is normally distributed about how much of the data fall within one standard deviation of the mean?

In a normally distributed data set, approximately 68% of the data falls within one standard deviation of the mean. This is part of the empirical rule, which states that about 68% of the data lies within one standard deviation, about 95% within two standard deviations, and about 99.7% within three standard deviations.


Is standard deviation is a point in a distribution?

No, standard deviation is not a point in a distribution; rather, it is a measure of the dispersion or spread of data points around the mean. It quantifies how much individual data points typically deviate from the mean value. A lower standard deviation indicates that the data points are closer to the mean, while a higher standard deviation indicates greater variability.


Suppose that 2 were subtracted from each of the values and a data set that originally had a standard deviation of 3.5 what would be the standard deviation of the resulting data?

Subtracting a constant value from each data point in a dataset does not affect the standard deviation. The standard deviation measures the spread of the values relative to their mean, and since the relative distances between the data points remain unchanged, the standard deviation remains the same. Therefore, the standard deviation of the resulting data set will still be 3.5.


In a normal distribution what percentage of the data falls within 2 standard deviation of the mean?

In a normal distribution, approximately 95% of the data falls within 2 standard deviations of the mean. This is part of the empirical rule, which states that about 68% of the data is within 1 standard deviation, and about 99.7% is within 3 standard deviations. Therefore, the range within 2 standard deviations captures a significant majority of the data points.


A set of 1000 values has a normal distribution the mean of the data is 120 and the standard deviation is 20 how many values are within one standard deviaiton from the mean?

The Empirical Rule states that 68% of the data falls within 1 standard deviation from the mean. Since 1000 data values are given, take .68*1000 and you have 680 values are within 1 standard deviation from the mean.


What percentage is 1 standard deviation?

In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean. This means that around 34% of the data lies between the mean and one standard deviation above it, while another 34% lies between the mean and one standard deviation below it.


How many of scores will be within 1 standard deviation of the population mean?

Assuming a normal distribution 68 % of the data samples will be with 1 standard deviation of the mean.


How is standard deviation useful?

It's used in determining how far from the standard (average) a certain item or data point happen to be. (Ie, one standard deviation; two standard deviations, etc.)


What is standard deviation used for?

Standard deviation is a measure of the spread of data.


What do you get with mean minus std dev?

When you subtract the standard deviation from the mean, you get a value that represents one standard deviation below the average of a dataset. This can be useful for identifying lower thresholds in data analysis, such as determining the cutoff point for values that are considered below average. In a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, so this value can help in understanding the spread of the data.


What percentage of the data falls within 3 standard deviation of the mean?

Approximately 99.7% of the data falls within 3 standard deviations of the mean in a normal distribution. This is known as the empirical rule or the 68-95-99.7 rule, which describes how data is distributed in a bell-shaped curve. Specifically, about 68% of the data falls within 1 standard deviation, and about 95% falls within 2 standard deviations of the mean.


What percentage of the data falls outside 1 standard deviation of the mean?

One standard deviation for one side will be 34% of data. So within 1 std. dev. to both sides will be 68% (approximately) .the data falls outside 1 standard deviation of the mean will be 1.00 - 0.68 = 0.32 (32 %)