The median
is usually preferred to other measures of central tendency when your data set is skewed (i.e., forms a skewed distribution) or you are dealing with ordinal data.
Which measure of central tendency is best for skewed distribution?
The median
is the most informative measure of central tendency for skewed distributions or distributions with outliers. For example, the median is often used as a measure of central tendency for income distributions, which are generally highly skewed.
What is the best measure of spread for a positively skewed distribution?
When it is skewed right or left with high or low outliers then
the median
is better to use to find the center. The best measure of spread when the median is the center is the IQR. As for when the center is the mean, then standard deviation should be used since it measure the distance between a data point and the mean.
Which measure of central tendency is the largest in a positively skewed distribution?
In positively skewed distributions, the mode is less than the median and the median is less than
the mean
. Therefore, the mean is the highest measure of central tendency in positively skewed distributions.
Which measure of central tendency is most appropriate for describing the center of a positively skewed distribution?
If the distribution is symmetrical, the mean is the best measure of central tendency. If the distribution is skewed either positively or negatively,
the median
is more accurate.
What is the best measure of central tendency for a skewed right histogram?
The median
is usually preferred to other measures of central tendency when your data set is skewed (i.e., forms a skewed distribution) or you are dealing with ordinal data.
What is the most stable and useful measure of central tendency?
As
mean
uses all the observations in a given distribution. Hence, mean is considered as the most stable central tendency.
What measure of spread is most reliable?
The standard deviation
is by far the most widely used measure of spread. It takes every score into account, has extremely useful properties when used with a normal distribution, and is tractable mathematically and, therefore, it appears in many formulas in inferential statistics.
What is the most reliable measure of variability?
The standard deviation
is the most commonly used and the most important measure of variability.
Which of the following tools are most appropriate to measure the center and spread for this distribution?
Which of the following tools are most appropriate to measure the center and spread for this distribution?
Mean and standard deviation
(this histogram is bell shaped with a central peak and some of the data values to the right. The mean is the most appropriate measure of center.
Which measure of central tendency is considered the most precise?
Mean
is generally considered the best measure of central tendency and the most frequently used one.
What is the best measure of central tendency for age?
Clearly
median
seems to be the statistic of choice when it comes to ages.
What measure of central tendency is most affected by extreme scores?
Median
. The median is the middle value in a distribution. It is the point at which half of the scores are above, and half of the scores are below. It is not affected by outliers, so the median is preferred as a measure of central tendency when a distribution has extreme scores.
What is positively skewed?
A positively skewed distribution is
the distribution with the tail on its right side
. The value of skewness for a positively skewed distribution is greater than zero. As you might have already understood by looking at the figure, the value of mean is the greatest one followed by median and then by mode.
Why is the mean not a good measure of central tendency for a skewed distribution?
Explanation: The mean is not a good measurement of central tendency
because it takes into account every data point
. If you have outliers like in a skewed distribution, then those outliers affect the mean one single outlier can drag the mean down or up. This is why the mean isn't a good measure of central tendency.
How do you describe a skewed distribution?
What Is a Skewed Distribution? A distribution is said to be skewed
when the data points cluster more toward one side of the scale than the other, creating a curve that is not symmetrical
. In other words, the right and the left side of the distribution are shaped differently from each other.
