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In a standard normal distribution 95 percent of the data is within plus standard deviations of the mean?
95% is within 2 standard deviations of the mean.
What percentage of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution?
99.7% of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution.
What percentage of a normal distribution is within 2 standard deviations of the mean?
I believe the standard deviations are measured from the median, not the mean.1 Standard Deviation is 34% each side of median, so that is 68% total.2 Standard Deviations is 48% each side of median, so that is 96% total.
What makes the range less desirable than the standard deviation as a measure of dispersion?
Range can include outliers that are not normal values and can skew overall data. Most relevant values can be found within one or two standard deviations on a normal curve.
How much data is within 1.28 standard deviations of mean on bell shaped curve?
80%
What is the proportion of the total area under the normal curve within plus or minus 2 standard deviations?
95%
What is the proportion of the total area under the normal curve within plus and minus two standard deviations of the mean?
95
In a standard normal distribution 95 percent of the data is within plus standard deviations of the mean?
95% is within 2 standard deviations of the mean.
What percentage of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution?
99.7% of scores fall within -3 and plus 3 standard deviations around the mean in a normal distribution.
What is the probability of an event occurring within 5 standard deviations from the mean?
The probability of an event occurring within 5 standard deviations from the mean is extremely rare, as it falls outside the normal range of outcomes.
Statistic question help?
When using Chebyshev's Theorem the minimum percentage of sample observations that will fall within two standard deviations of the mean will be __________ the percentage within two standard deviations if a normal distribution is assumed Empirical Rule smaller than greater than the same as
What percentage of a normal distribution is within 2 standard deviations of the mean?
I believe the standard deviations are measured from the median, not the mean.1 Standard Deviation is 34% each side of median, so that is 68% total.2 Standard Deviations is 48% each side of median, so that is 96% total.
What does cardiomediastinal contour is grossly within normal limits mean?
This means that the overall appearance of the heart and mediastinum (the area in the chest that contains the heart and other structures) is within the normal range when observed visually. There are no obvious abnormalities or significant deviations from what is typically seen.
In statistics what does the empirical rule states?
Nearly all the values in a sample from a normal population will lie within three standard deviations of the mean. Please see the link.
How does the bell curve relates to the empirical rule?
The bell curve, also known as the normal distribution, is a symmetrical probability distribution that follows the empirical rule. The empirical rule states that for approximately 68% of the data, it lies within one standard deviation of the mean, 95% within two standard deviations, and 99.7% within three standard deviations when data follows a normal distribution. This relationship allows us to make predictions about data distribution based on these rules.
What is chebychev's rule?
Chebyshev's rule, also known as Chebyshev's inequality, is a statistical theorem that describes the proportion of values that fall within a certain number of standard deviations from the mean in any distribution. It states that for any set of data, regardless of the shape of the distribution, at least (1 - 1/k^2) where k is greater than 1, of the data values will fall within k standard deviations of the mean.
What makes the range less desirable than the standard deviation as a measure of dispersion?
Range can include outliers that are not normal values and can skew overall data. Most relevant values can be found within one or two standard deviations on a normal curve.
