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What is the Extreme high or low values in a data set which affect the mean?
Extreme high or low values in a data set, known as outliers, can significantly skew the mean. For instance, a few very high values can inflate the mean, making it higher than the central tendency of the majority of the data. Conversely, extreme low values can drag the mean down, misrepresenting the typical value of the dataset. This sensitivity makes the mean less reliable as a measure of central tendency when outliers are present.
Advantages and disadvantages of mean in statistics?
MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.
Why it is useful to fiNd the meaN mediaN aNd mode of a set of data?
when there are extreme values in the data
When an observation in a data is abnormally more than and less than the remaining observations in the data does it affect Mean Median Mode?
Yes, an observation that is abnormally larger or smaller than the rest of the data can significantly affect the mean, as it will pull the average towards that extreme value. However, the median and mode are less influenced by outliers, as they are not as sensitive to extreme values. The median is the middle value when the data is arranged in order, so outliers have less impact on its value. The mode is the most frequently occurring value, so unless the outlier is the most common value, it will not affect the mode.
The mode may be more useful than the mean when there are extreme values in the data set?
True. I've included a link which will help you understand why.
What are the advantages of mode?
extreme values don't affect the mode
Do extreme values affect the median?
No they do not (or at least they have less of a significant impact) and this is the benefit of using the median average over the mean average.
What is the Extreme high or low values in a data set which affect the mean?
Extreme high or low values in a data set, known as outliers, can significantly skew the mean. For instance, a few very high values can inflate the mean, making it higher than the central tendency of the majority of the data. Conversely, extreme low values can drag the mean down, misrepresenting the typical value of the dataset. This sensitivity makes the mean less reliable as a measure of central tendency when outliers are present.
How extreme value affect mean?
An extreme value will drag the mean value towards it.
Which summary measures are influenced by extreme values?
mode and mean
When is the mean used as a measure of central tendency?
When there aren't extreme values (outliers)
A good statistical indicator to avoid the distortion of extreme values is the?
weighted mean
When do you use mean and median?
The mean is used to measure the average of a set of values, especially when the data is normally distributed. The median is used to find the middle value of a dataset when there are extreme values or outliers present, as it is less affected by extreme values.
Advantages and disadvantages of mean in statistics?
MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.
Why it is useful to fiNd the meaN mediaN aNd mode of a set of data?
when there are extreme values in the data
Do extremely high or low scores affect the value of the median?
No, extremely high or low values will not affect the median. Because the median is the middle number of a series of numbers arranged from low to high, extreme values would only serve as the end markers of the values.
The measure of location that is the most likely to be influenced by extreme values in the data set is the range?
mean
