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correlation is drawn from all data points. if you look at the r^2 value and it's below 0.99 for example (should be higher in non research work (and in much research work) it indicates that 1 of your points may be an outlier. If you input all datapoints into excel, you may be able to see the point that's throwing it off. There are also statistical tests you can do to spot an outlier.
In other words, correlation is not independent of an outlier. it will make the r^2 value worse. If the outlier is taken out, then the correlation could be deemed independent but only because you manipulated it and had taken the outlier out
What else can I help you with?
Can there be 2 outliers in a set of data?
There is no limit to the number of outliers there can be in a set of data.
What are limits on outliers?
apparently there is no limit to outliers. at least according to everybody else's answers.
Is the median particularly sensitive to outliers in the data?
It is not.
What is the meaning of 0.79 coefficient correlation?
good correlation
How can you determine which measure of central tendency is best for the set if data?
Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)
Is correlation a resistant measure?
i think correlatioin is a nonresistant measure because if you take out outliers than only the data that's close together is there...this will increase the correlation closer to -1 or 1, depending on the slope
Is metal nonresistant?
Care to clarify? The question is way too broad to give a useful answer. What type of metal? resistant or non-resistant to what?
Is the correlation coefficient resistant?
No, it is not resistant to changes in data.
In general the median of a data set is more resistant to outliers than the mean.?
Yes, it is.
Is the correlation coefficient r a resistant measure of association?
no
How do you use nonresistant in a sentence?
Nonresistant is defined as the inability to withstand the effect of something, or a person who does not resist force. A sample sentence is "Shale is a nonresistant form of sandstone."
What is the least resistant to outliers mean median or mode?
The mean is the least resistant to outliers because it is influenced by every value in the dataset, including extreme values. In contrast, the median, which represents the middle value, is less affected by outliers, as it depends only on the order of the data. The mode, being the most frequently occurring value, is also generally unaffected by outliers. Thus, in terms of sensitivity to extreme values, the mean is the most vulnerable.
What are the three ways to describe data in a scatter plot?
You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.
Which descriptive summary measures are considered to be resistant statistics?
Median is a good example of a resistant statistic. It "resists" the pull of outliers. The mean, on the other hand, can change drastically in the presence of an outlier.The interquartile range is a resistant measure of spread.
How do use nonresistance in a sentence?
Nonresistant is defined as the inability to withstand the effect of something, or a person who does not resist force. A sample sentence is "Shale is a nonresistant form of sandstone."
What are the limits on outliers?
there are no limits to outliers there are no limits to outliers
How is the correlation imperfect?
Correlation is considered imperfect because it measures the strength and direction of a relationship between two variables but does not imply causation. Factors such as outliers, non-linear relationships, or the influence of a third variable can distort the correlation coefficient, leading to misleading interpretations. Additionally, correlation only captures linear associations, meaning that even if two variables are correlated, their relationship may not be consistent across all ranges or contexts.
