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Can outliers affect the symmetry of the data?
an outliers can affect the symmetry of the data because u can still move around it
What are outliers and how do they affect data?
Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.
How does the outlier affect the mean and median?
The mean is better than the median when there are outliers.
How do outliers affect the median?
None - as long as the ouliers move away from the median - which they should.
What does the whisker in a box-and-whisker plot represent?
The whiskers mark the ends of the range of figures - they are the furthest outliers. * * * * * No. Outliers are not part of a box and whiskers plot. The whiskers mark the ends of the minimum and maximum observations EXCLUDING outliers. Outliers, if any, are marked with an X.
Can outliers affect the symmetry of the data?
an outliers can affect the symmetry of the data because u can still move around it
Does outliers affects data?
No. Outliers are part of the data and do not affect them. They will, however, affect statistics based on the data and inferences based on the data.
What do box and whisker plots tell you about data that measures of central tenancy do not?
The box and whisker plot informs you of the 5 number summary, which comprises of the minimum and maximum, the median, and the first and third quartiles. The minumum and maximum give you the range, which is not given by measures of central tendancy. also, if it a modified box and whisker plot, outliers will be marked separatley from the rest of the plot, outliers are also not included in the measures of center.
What are outliers and how do they affect data?
Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.
How does the outlier affect the mean and median?
The mean is better than the median when there are outliers.
When is the median the most appropriate center for a distribution?
The median is the most appropriate center when the distribution is very skewed or if there are many outliers.
What measures are not affected by outliers?
Median, mode, quartiles, quintiles and so on, except when you get to very large number of percentiles.
How do outliers affect the median?
None - as long as the ouliers move away from the median - which they should.
What are the limits on outliers?
there are no limits to outliers there are no limits to outliers
When is the median more useful than the mean?
When the distribution has outliers. They will skew the mean but will not affect the median.
What measures of central location is affected most by extreme values?
The mean is most affected. Mode and Median are not influenced as much by outliers.
Is range is not considered to be an index of despersion?
The sample range could be used as an index of dispersion. However, there are objections. One is that this statistic is obviously sensitive to outliers. Another is that for many population distributions there are measures with much better characteristics, even ignoring the problem of outliers.
