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How much data is within 1.28 standard deviations of mean on bell shaped curve?
Wiki User
∙ 13y ago
80%
Wiki User
∙ 13y ago
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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.
Describe the properties of a normal distribution?
A normal distribution is symmetric and when looked at on a graph, the graph looks like a bell shaped curve. Approximately 95 percent of its values should lie within two standard deviations of the mean. Frequency of the data lies mostly in the middle of the curve.
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 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.
Does the curve in a normal distribution stop at plus or minus 3 standard deviations?
No. The curve in a normal distribution goes on out to plus and minus infinity. You might never see any observations out there, but if you were to make an infinite number of observations, you theoretically would.
What is the proportion of the total area under the normal curve within plus or minus 2 standard deviations?
95%
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.
What is the proportion of the total area under the normal curve within plus and minus two standard deviations of the mean?
95
Describe the properties of a normal distribution?
A normal distribution is symmetric and when looked at on a graph, the graph looks like a bell shaped curve. Approximately 95 percent of its values should lie within two standard deviations of the mean. Frequency of the data lies mostly in the middle of the curve.
What does normality mean in health and social care?
All minor deviations occurring with two standard deviations under the Gaussian curve are considered normal. Deviations occurring outside of two standard deviations are considered abnormal.
How do you draw a bell curve?
A bell curve reaches its highest point in the middle and is lower on the sides. It can represent standard deviations from the mean.
If a data point has a corresponding score of -1.5 then it is one and a half standard deviations above the mean value.?
If you are talking about the z-value of a point on the normal curve, then no, it is 1.5 standard deviations BELOW the mean.
Is nearly all the area under the normal curve between z-3.00 and z3.00?
yes, since according to the 68-95-99.7 rule, the area within 3 standard deviations is 99.7%
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 abnormal distribution?
A standard distribution regards 95% of all data being within 2-standard deviations of either side. Similarly, within one standard deviation either way is 68% of all data. This creates a bell curve distribution. An abnormal distribution would be erratic and not follow such a statistical structure of representation.
What are the characteristics of a normal distribution curve?
Characteristics of a Normal Distribution1) Continuous Random Variable.2) Mound or Bell-shaped curve.3) The normal curve extends indefinitely in both directions, approaching, but never touching, the horizontal axis as it does so.4) Unimodal5) Mean = Median = Mode6) Symmetrical with respect to the meanThat is, 50% of the area (data) under the curve lies to the left ofthe mean and 50% of the area (data) under the curve liesto the right of the mean.7) (a) 68% of the area (data) under the curve is within onestandard deviation of the mean(b) 95% of the area (data) under the curve is within twostandard deviations of the mean(c) 99.7% of the area (data) under the curve is within threestandard deviations of the mean8) The total area under the normal curve is equal to 1.
When a driver first sees danger until he gets his foot on the brake is thought to follow a normal model with a mean of 1.5 sec and SD of 0.18 sec. Use the 68-95-99.7 rule to draw the normal model.?
The mean time it will take for a a drive to hit the break is 1.5 seconds. 68% of drivers will be within a Standard Deviations of that value, that is 1.32 - 1.68 seconds. 95% of drivers will be within two standard deviations of that value, 1.14 - 1.86 seconds. 99.7% of drivers will be within three standard deviations of that value, 0.96 - 2.04. So what you need to do is draw a bell shaped curve and then draw an axis with 1.5 s directly under the highest point on your bell, and then the other values at appropriate distances to show the correct percentage of the area.
