0
What is the proportion of the total area under the normal curve within plus or minus 2 standard deviations?
Wiki User
∙ 12y ago
95%
Wiki User
∙ 12y ago
Add your answer:
Earn +20 pts
What is the proportion of the total area under the normal curve within plus and minus two standard deviations of the mean?
95
What percentage of data would fall within 1.75 standard deviations of the mean?
About 81.5%
Why is the standard deviation one?
The standard deviation provides in indication of what proportion of the entire distribution of the sample falls within a certain distance from the mean or average for that sample. If your data falls on a normal (or bell shaped) distribution, a SD of 1 indicates that about 68% of your data points (scores or whatever else) fall within 1 point (plus or minus) of the average (mean) of the data, and 95% fall within 2 points.
What percent of a normal population is within 2 standard deviations of the mean?
By the definition of standard deviation, 95.46% of the normal population will be within 2 SD of the mean. Explanation: The normal distribution of a population means it follows the "bell curve". The center of this bell curve is the population's mean value. One standard deviation defines two areas (on the left and right side of the central "mean" value) under the bell curve that each have 34.13% of the population. The next standard deviation adds two additional areas under the curve, each having 13.6% of the population. Adding the areas under the curves on both sides gives us (34.13% + 13.6%) x 2 = 95.46%
State the main reason for using the empirical rule rather than chebyshevs theorem?
The empirical rule can only be used for a normal distribution, so I will assume you are referring to a normal distribution. Chebyshev's theorem can be used for any distribution. The empirical rule is more accurate than Chebyshev's theorem for a normal distribution. For 2 standard deviations (sd) from the mean, the empirical rule says 95% of the data are within that, and Chebyshev's theorem says 1 - 1/2^2 = 1 - 1/4 = 3/4 or 75% of the data are within that. From the standard normal distribution chart, the answer for 2 sd from the mean is 95.44% So, as you can see the empirical rule is more accurate.
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 proportion of the total area under the normal curve within plus or minus 2 statndard deviations?
It is 0.9955 of the total area.
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.
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
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.
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.
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 percentage of data would fall within 1.75 standard deviations of the mean?
About 81.5%
How much data is within 1.28 standard deviations of mean on bell shaped curve?
80%
What is the measures that fall beyond three standard deviations of the mean called?
You may be referring to the statistical term 'outlier(s)'. Also, there is a rule in statistics called the '68-95-99 Rule'. It states that in a normally distributed dataset approximately 68% of the observations will be within plus/minus one standard deviation of the mean, 95% within plus/minus two standard deviations, and 99% within plus/minus three standard deviations. So if your data follow the classic bell-shaped curve, roughly 1% of the measures should fall beyond three standard deviations of the mean.
