The outlier is 9.
An outlier, in a set of data, is an observation whose value is distant from other observations. There is no exact definition but one commonly used definition is any value that lies outside of Median ± 3*IQR IQR = Inter-Quartile Range.
It's possible. An outlier is a number that affects the the mean of a group of numbers greatly. For example the mean in this set of numbers (2, 4, 1, 5) is 3, but if I add the number 93 the new answer is 21.
The exact definition of which points are considered to be outliers is up to the experimenters. A simple way to define an outlier is by using the lower (LQ) and upper (UQ) quartiles and the interquartile range (IQR); for example: Define two boundaries b1 and b2 at each end of the data: b1 = LQ - 1.5 × IQR and UQ + 1.5 × IQR b2 = LQ - 3 × IQR and UQ + 3 × IQR If a data point occurs between b1 and b2 it can be defined as a mild outlier If a data point occurs beyond b2 it can be defined as an extreme outlier. The multipliers of the IQR for the boundaries, and the number of boundaries, can be adjusted depending upon what definitions are required/make sense.
A set of data has no mode when there is no number that occurs more frequently than another. The data set: 1, 2, 5, 5, 6 has a mode of 5. The data set: 1, 2, 3 has no mode.
Hai. :3
If the set of numbers is sorted: 1 1 2 3 4 5 5, then you can see that 1 and 5 both lie at the outer limits of the range of data.
The outlier is 9.
An outlier, in a set of data, is an observation whose value is distant from other observations. There is no exact definition but one commonly used definition is any value that lies outside of Median ± 3*IQR IQR = Inter-Quartile Range.
Outliers are basically numbers, in a set of numbers, that don't belong in that set and/or that stand out. For example, in the data set {3, 5, 4, 4, 6, 2, 25, 5, 6, 2} the value of 25 is an outlier. For a set of numerical data (a set of numbers), any value (number) that is markedly smaller or larger than other values is an outlier. This is the qualitative definition. Mathematically, a quantitative definition often given is that an outliers is any number that is more than 1.5 times the interquartile range away from the median. However, this is not definitive and in some cases other definitions will be used.
It's possible. An outlier is a number that affects the the mean of a group of numbers greatly. For example the mean in this set of numbers (2, 4, 1, 5) is 3, but if I add the number 93 the new answer is 21.
The mean of a set of data is the sum of all those data values, divided by the numbers of values in the set. For instance, if we had 1, 3 and 5, the mean would be (1+3+5)/3 = 3. The mean doesn't always have to be one of the data points in the set. For instance, if we had the data 1, 6, 7, 7, 8. The mean would be (1+6+7+7+8)/5 = 5.8, even though 5.8 isn't one of the values in the set.
The exact definition of which points are considered to be outliers is up to the experimenters. A simple way to define an outlier is by using the lower (LQ) and upper (UQ) quartiles and the interquartile range (IQR); for example: Define two boundaries b1 and b2 at each end of the data: b1 = LQ - 1.5 × IQR and UQ + 1.5 × IQR b2 = LQ - 3 × IQR and UQ + 3 × IQR If a data point occurs between b1 and b2 it can be defined as a mild outlier If a data point occurs beyond b2 it can be defined as an extreme outlier. The multipliers of the IQR for the boundaries, and the number of boundaries, can be adjusted depending upon what definitions are required/make sense.
A set of data has no mode when there is no number that occurs more frequently than another. The data set: 1, 2, 5, 5, 6 has a mode of 5. The data set: 1, 2, 3 has no mode.
The middle # in a set of data.
A set of data may include scores that are extremely different from the rest of the group causing suspicion; scores that are remarkably different from the majority are called outliers.For a set of numerical data, any value that is markedly smaller or larger than other values. Mathematically, outliers are considered any number that is more than 1.5 times the interquartile range away from the median. For example, in the data set {3, 5, 4, 4, 6, 2, 25, 5, 6, 2} the value of 25 is an outlier.Basically the one that doesn't belong.Basically, the outlier is the number thatstands out.So let's say we have these numbers: 2,3,1,17. 17 is our outlier. Why? Because, it's obvious.17 is separate away from the all the other numbers. An outlier is an element of a data set that distinctly stands out from the rest of the data. Read more: http://wiki.answers.com/What_is_an_outlier_in_math#ixzz1FRclyotO
A bi-modal data set is a data set that has two modes. In the data set 1, 2, 2, 3, 4, 4, 5 the mode is 2 AND 4. So it is a bi-modal data set. Hope that helps.