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What does the standard deviation tell us about the mean?
The standard deviation tells us nothing about the mean.
What does standard deviation show us about a set of scores?
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
What does a large standard deviation tell us?
It means that the data are spread out around their central value.
What would the Z score be if Z equals 0 and Z equals -1.41?
1.41
What percent of a normal population is within 2 standard deviations of the mean?
In a normal distribution, approximately 95% of the population falls within 2 standard deviations of the mean. This is known as the 95% rule or the empirical rule. The empirical rule states that within one standard deviation of the mean, about 68% of the population falls, and within two standard deviations, about 95% of the population falls.
US IQ Standard deviation?
US IQ standard Deviation is 16.
What does the standard deviation tell us about the mean?
The standard deviation tells us nothing about the mean.
What is the standard deviation of height in the US population?
The standard deviation of height in the US population is approximately 3 inches.
What does the standard deviation tell us?
standard deviation is the square roots of variance, a measure of spread or variability of data . it is given by (variance)^1/2
What does standard deviation show us about a set of scores?
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
What does the number from the standard deviation tell us?
the variation of a set of numbrs
Age of death of all US Vice Presidents?
All US Vice Presidents are not yet dead.
Why is standard deviation used?
It gives us an idea how far away we are from the center of a normal distribution.
What does a large standard deviation tell us?
It means that the data are spread out around their central value.
How many us presidents were under the age of 40?
zero
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.
What standard deviation tells us about a distribution?
It is a measure of the spread of the distribution: whether all the observations are clustered around a central measure or if they are spread out.
