In my last post I touched on the concept of Central Tendency (CT); that is the theory that in any data set there may be varying values for each data point but that on the whole there is one central value around which the values congregate. I’m going to address three of the most common measures of central tendency in this post. They are the mean, the median, and the mode. The mean, also known as an average, is the most commonly used measure of central tendency that most people are familiar with. This measure is arrived at by adding the individual observations in the data set and then dividing the sum of those values by the number of observations. In my last post I gave the example of daily stock prices that were $3.00, $4.00, $3.00, $6.00, $4.00, $32.00, $3.00. In this instance the sum of the values is 55. And 55 divided by 7 (the number of observations) is $7.86. Therefore the mean of that data set is $7.86. But as I pointed out in my last post, the extreme value of $32.00 skewed the mean higher than any of the other values in the set. That is one weakness of the mean value – it is very sensitive to extreme values. To alleviate that sensitivity, one might seek a different measure of central tendency. Let’s look at the median next, as it does some of the work of desensitizing the CT measure from extreme values. The median is arrived at by arranging the values in order from lowest to highest and choosing the middle value. If the number of values is even the median is considered to be equal to the mean of the middle two values. In our case we have an odd number of values and the middle value is $4.00. $3.00 $3.00 $3.00 --------- $4.00 --------- $4.00 $6.00 $32.00 Thus we see that the median can act to filter out the bias towards extreme values to which the mean is susceptible by placing those values at either end of the continuum and finding the middle of the road value. The last common measure of central tendency that I want to talk about here is the mode. The mode is nothing more than the most commonly reoccurring observation. In our case there are three instances of the value of $3.00, the most of any other value – making $3.00 the mode.
"Measures of central tendency are statistical measures." is an accurate statement.
well...the measures of the central tendency would be 30 minutes
mode
One advantage to using central tendency is the fact that is represents all data. A disadvantage to using central tendency is the fact that extremes can skew the data.
Because it measures the averages of a collection of data
"Measures of central tendency are statistical measures." is an accurate statement.
Benefits of Central Tendency
One of the measures of central tendency IS the average, also known as mean. You can't calculate the average from other measures of central tendency.
"What are the benefits of measures of central tendency? Explain with an example
easures of central tendency
The mean of 9 is 9. The median of 9 is 9. The mode of 9 is 9. These are the commonest measures of central tendency.
well...the measures of the central tendency would be 30 minutes
None. Measures of central tendency are not significantly affected by the spread or dispersion of data.
difference
call thi
The mean and median are two measures of central tendency. In introductory statistics many schools include the mode as another example of central tendency but the mode could well be at the end of a distribution.
Common measures of central tendency are the mean, median, mode. Common measures of dispersion are range, interquartile range, variance, standard deviation.