Two different sets of data that each have six values and a mean of 21 could be:
Both sets demonstrate that different combinations of numbers can yield the same mean.
If the skewness is different, then the data sets are different.Incidentally, there is one [largely obsolete] definition of skewness which is in terms of the mean and median. Under that definition, it would be impossible for two data sets to have equal means and equal medians but opposite skewness.
A scatter plot displays two sets of data as ordered pairs. Each point on the graph represents an individual pair of values, typically corresponding to two different variables. This visual representation helps to identify relationships, trends, or correlations between the two sets of data.
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.
The sample mean is not necessarily equal to one of the values in the sample. It is calculated by summing all the values in the sample and dividing by the number of observations. While the mean can coincide with one of the sample values, this is not a requirement and often does not occur, especially in larger or more diverse data sets.
Yes, extreme values, also known as outliers, can significantly affect the mean of a data set. Since the mean is calculated by summing all values and dividing by the number of values, a single extreme value can disproportionately skew the result. This is why the mean may not always be the best measure of central tendency for data sets with outliers; alternatives like the median can provide a more accurate representation of the typical value.
No. Here's one set of data where the mean is not one of the values: a set of 250,000 numbers. 125,000 of them are "1", 125,000 are "3". The mean of this data set is "2", which is not among the data.
(10,10,30,30,30,50,50) (20,20,30,30,30,40,40) These two sets have the same mean, median and mode.
No, not all data sets have a mode but all data sets have a mean and median.
If the skewness is different, then the data sets are different.Incidentally, there is one [largely obsolete] definition of skewness which is in terms of the mean and median. Under that definition, it would be impossible for two data sets to have equal means and equal medians but opposite skewness.
A scatter plot displays two sets of data as ordered pairs. Each point on the graph represents an individual pair of values, typically corresponding to two different variables. This visual representation helps to identify relationships, trends, or correlations between the two sets of data.
No, because sometimes sets of data can have different numbers and other sets of data can have modes in them.
It is a positive relationship.
The minimum and maximum are the same. The mean, median, and mode can be different.
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.
The sample mean is not necessarily equal to one of the values in the sample. It is calculated by summing all the values in the sample and dividing by the number of observations. While the mean can coincide with one of the sample values, this is not a requirement and often does not occur, especially in larger or more diverse data sets.
Yes, extreme values, also known as outliers, can significantly affect the mean of a data set. Since the mean is calculated by summing all values and dividing by the number of values, a single extreme value can disproportionately skew the result. This is why the mean may not always be the best measure of central tendency for data sets with outliers; alternatives like the median can provide a more accurate representation of the typical value.
You can have several series which results in lots of bars in sets for different values. The type of chart you have is partially depending on the data you have.