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What else can I help you with?
As the sample size increases the effect of an extreme value on the sample mean becomes smaller.?
yes
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.
Since the median is the middle value of a data set it must always be?
Not an extreme value.
What are the advantages of mode?
extreme values don't affect the mode
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.
Do extreme values affect mean?
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.
Which of measure of location is affect most by extreme value?
median
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.
What is the effect of extreme value on mean?
Outliers pull the mean in the direction of the outlier.
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.
As the sample size increases the effect of an extreme value on the sample mean becomes smaller.?
yes
What is the term for an exceptional value that can dramatically affect the mean?
That would be outlier.
How does the outlier affect the median?
An outlier can significantly impact the median by pulling it towards the extreme value of the outlier, especially when the dataset is small. This can distort the central tendency measure that the median represents and provide a misleading representation of the typical value in the dataset.
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.
Is there any distinction between an extreme point and an extreme value of a function?
no
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.
Which measure of central tendency includes data from every score?
The measure of central tendency that includes data from every score is the mean. The mean is calculated by summing all the values in a dataset and then dividing by the total number of scores, which means it takes into account each individual score in the calculation. This makes the mean sensitive to extreme values (outliers), which can significantly affect its value.
