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When is each measure of central tendency most useful?
Mode: Data are qualitative or categoric. Median: Quantitative data with outliers - particularly if the distribution is skew. Mean: Quantitative data without outliers, or else approx symmetrical.
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. :)
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.
Is the mean or median more accurate?
None of them is "more accurate". They are answers to two different questions.
What are the advantages and disadvantages of median?
Median cannot be used for qualitative data (a mode can).The sampling distribution of the median is complicated (the mean is well studied).Median can usually be used for data that can be ordered without there being a ratio scale. For example, "small-medium-large", or "very negative-negative-neutral-positive-very positive". A mean cannot be calculated without arbitrarily assigning a numerical value to the terms.A median is not dependent on all the values which means that it is not distorted by outliers (extreme values).It is easy to find the median value from cumulative frequency charts.
When is each measure of central tendency most useful?
Mode: Data are qualitative or categoric. Median: Quantitative data with outliers - particularly if the distribution is skew. Mean: Quantitative data without outliers, or else approx symmetrical.
When the median and mean are substantially different what does that tell you about the data?
I think it means that our data includes outliers.
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. :)
In general the median of a data set is more resistant to outliers than the mean.?
Yes, it is.
Why do they invented the stem and the leaf plot?
to organize your data set and figure out mean, median, mode, range, and outliers.
Under what conditions might you prefer to use the median rather than the mean as the best measure of central tendency?
the median is perferred when the data is strongly skewed or has outliers. =)
Advantages and disadvantages of median 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.
What is the primary disadvantage of using the range to compare the variability of data sets?
The range is very sensitive to outliers. Indeed if there are outliers then the range will be unrelated to any other elements of the sample.
What are outliers and how do they affect data?
Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.
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.
How can the median and mean be different?
You will notice a difference in the data if you have outliers. The mean of a set is going to be heavily influenced by outliers due to the mean being dependant on the quantity of each unit (i.e. 2 cats, 7 cats, 300 cats, etc.) The median, however, is not influenced by outliers because it accounts for the number of units rather than the quantity associated with the units.
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.
