This would increase the mean by 6 points but would not change the standard deviation.
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
It is 15 points.
There are two points of infection (the points where the curvature changes its direction) which lie at a distance of one standard deviation above mean and one standard deviation below mean.
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.
The mean of a distribution is a measure of central tendency, representing the average value of the data points. In this case, the mean is 2.89. The standard deviation, which measures the dispersion of data points around the mean, is missing from the question. The standard deviation provides information about the spread of data points and how closely they cluster around the mean.
The standard deviation is a measure of how spread out the numbers are. Three points is needed to calculate a statistically valid meaningful standard deviation.
Standard deviation is the square root of the variance. Since you stated the variance is 4, the standard deviation is 2.
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
The lowest value that standard deviation can be is zero. This occurs when all the data points in a dataset are identical, meaning there is no variation among them. In such cases, the standard deviation, which measures the dispersion of data points around the mean, indicates that there is no spread.
It is 15 points.
A standard deviation of zero means that all the data points are the same value.
There are two points of infection (the points where the curvature changes its direction) which lie at a distance of one standard deviation above mean and one standard deviation below mean.
In statistical analysis, the value of sigma () can be determined by calculating the standard deviation of a set of data points. The standard deviation measures the dispersion or spread of the data around the mean. A smaller standard deviation indicates that the data points are closer to the mean, while a larger standard deviation indicates greater variability. Sigma is often used to represent the standard deviation in statistical formulas and calculations.
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.
To calculate the standard deviation of a portfolio in Excel, you can use the STDEV.P function. This function calculates the standard deviation based on the entire population of data points in your portfolio. Simply input the range of values representing the returns of your portfolio into the function to get the standard deviation.
Yes, a standard deviation of 4.34 can be correct. Standard deviation is a measure of dispersion or variability in a data set. It represents the average amount by which individual data points deviate from the mean. Therefore, a standard deviation of 4.34 simply indicates that there is some variability in the data, with data points on average deviating by 4.34 units from the mean.
Standard deviation is the spread of the data. If each score has 7 added, this would not affect the spread of the data - it would be just as evenly spaced or clumped up, but 7 greater. The only thing that would affect the spread is multiplying every data point by 0.9. This makes distances between the data points 0.9 times as big, and thus makes the standard deviation 0.9 times as big. The standard deviation was 5.6, and so now is 5.6x0.9 = 5.04