I think it means that our data includes outliers.
The mean will increase very substantially, the median will remain unchanged.The mean will increase very substantially, the median will remain unchanged.The mean will increase very substantially, the median will remain unchanged.The mean will increase very substantially, the median will remain unchanged.
If a data set consists of 1000 different values can the mean and the median be the same
The mean will increase substantially. The median may increase slightly or substantially - depending on how many observations are in the central values of the distribution. The mode should not change at all.
The mean and median of a data set can differ due to the presence of outliers or skewed data. The mean is sensitive to extreme values, which can pull it in one direction, while the median, being the middle value, remains unaffected by such extremes. In a skewed distribution, the mean may be pulled toward the tail, resulting in a disparity between the two measures of central tendency. Thus, when data is not symmetrically distributed, the mean and median can yield different results.
the median and mode are but the mean is not
The mean will increase very substantially, the median will remain unchanged.The mean will increase very substantially, the median will remain unchanged.The mean will increase very substantially, the median will remain unchanged.The mean will increase very substantially, the median will remain unchanged.
If a data set consists of 1000 different values can the mean and the median be the same
(10,10,30,30,30,50,50) (20,20,30,30,30,40,40) These two sets have the same mean, median and mode.
The mean will increase substantially. The median may increase slightly or substantially - depending on how many observations are in the central values of the distribution. The mode should not change at all.
No, not all data sets have a mode but all data sets have a mean and median.
The mean and median of a data set can differ due to the presence of outliers or skewed data. The mean is sensitive to extreme values, which can pull it in one direction, while the median, being the middle value, remains unaffected by such extremes. In a skewed distribution, the mean may be pulled toward the tail, resulting in a disparity between the two measures of central tendency. Thus, when data is not symmetrically distributed, the mean and median can yield different results.
well because in the mean you have to add them and its different from the median and the mode
You can estimate the median and the mean.
Yes.
The median is used when reporting ordinal data.
the median and mode are but the mean is not
mean~ all the numbers in the data added together divided by the number of data. The mean is the same as the average. median~ the exact middle of the set of data. Example: 1,1,2,2, the median is 1.5 mean- the average median- the middle number in a set of numbers in a group.Example of Median-1,3,5,7,9,4,5 (put them in order and list them from least to greatest)1,3,4,5,5,7,9the median is 5!