# Why are the measures of central tendency like mean, median and mode important in research?

*print*Print*list*Cite

### 2 Answers

Measures of central tendency include mean, mode and median among several others. They are important in research to analyze the data has been collected.

When a research is conducted, information on the characteristics of a large number of individuals that make up the population under study is collected. It is not possible to arrive at any conclusion based on the details of each person as the individual information is diverse in nature.

To arrive at any trend all the pieces of data collected are manipulated and studied. For example, if a research requires collecting the weight of a large number of people the mean gives an idea of the weight of people in general. The median would be the weight of the largest number of people and the mode would be the weight of people that is half-way between the highest and the lowest.

**Central Tendency.** The central tendency of a distribution is an estimate of the "center" of a distribution of values. There are three major types of estimates of central tendency:

- Mean
- Median
- Mode

The **Mean** or average is probably the most commonly used method of describing central tendency. To compute the mean all you do is add up all the values and divide by the number of values. For example, the mean or average quiz score is determined by summing all the scores and dividing by the number of students taking the exam. For example, consider the test score values:

**15, 20, 21, 20, 36, 15, 25, 15**

The sum of these 8 values is 167, so the mean is 167/8 = 20.875.

The **Median** is the score found at the exact middle of the set of values. One way to compute the median is to list all scores in numerical order, and then locate the score in the center of the sample. For example, if there are 500 scores in the list, score #250 would be the median. If we order the 8 scores shown above, we would get:

**15,15,15,20,20,21,25,36**

There are 8 scores and score #4 and #5 represent the halfway point. Since both of these scores are 20, the median is 20. If the two middle scores had different values, you would have to interpolate to determine the median.

The **mode** is the most frequently occurring value in the set of scores. To determine the mode, you might again order the scores as shown above, and then count each one. The most frequently occurring value is the mode. In our example, the value 15 occurs three times and is the model. In some distributions there is more than one modal value. For instance, in a bimodal distribution there are two values that occur most frequently.

Notice that for the same set of 8 scores we got three different values -- 20.875, 20, and 15 -- for the mean, median and mode respectively. If the distribution is truly normal (i.e., bell-shaped), the mean, median and mode are all equal to each other.

The **Standard Deviation** is a more accurate and detailed estimate of dispersion because an outlier can greatly exaggerate the range (as was true in this example where the single outlier value of 36 stands apart from the rest of the values. The Standard Deviation shows the relation that set of scores has to the mean of the sample. Again lets take the set of scores: