Skip to main content

THE MODE


In the previous posts, three measures of location have been discussed, namely the arithmetic mean, the median, and the quartiles. In this post, one more measure of location, the mode, will be discussed. Mode can be applied on data with any level of measurement.

If a group of data is given, its mode (denoted by Mo) is the data with the highest frequency of occurrence. In other words, the mode of a data set is the set member that appears most often.


Example 1
In a class, there are 30 and 10 male and female students, respectively. There are more men than women, so the mode of sex in the class is male.


Example 2
The following is a list of the favourite colours of some kindergarten students.



The mode of the favourite colours is red, because red appears most often.


Example 3
The following are 13 math test scores data of some junior high school students:
76   47   56   42   78   80   76   45   78   76   80   95   80
This data has two modes, namely (Mo)1 = 76 and (Mo)2 = 80. Both of these data appear 3 times (with a frequency of 3), while other data appear less than 3 times.

As Example 3 demonstrated, it is possible for a group of data to have more than one mode. The data in Example 3 is an example of bimodal data, which has two modes. If a group of data has only one mode, that data is called unimodal data. But if a group of data has more than two modes, the data is called multimodal data.

Comments

Post a Comment

Popular posts from this blog

CONSTRUCTING THE FREQUENCY DISTRIBUTION TABLE

The frequency distribution table is a table that divides data into groups (classes) and shows how many data values occur in each group/class. Below is an example of frequency distribution table. Now we are learning how to create a frequency distribution table. Suppose we have a collection of ungrouped data on last year’s advertising expenditures of 40 logistics companies, recorded in millions Rupiahs. To construct a frequency distribution table of the ungrouped data, apply the following steps. Step 1: Find the range of the data The range (R) is defined as the difference between the largest data and the smallest data. In this case, R = 307 - 242 = 65. Step 2: Determine the number of categories/classes (k) Applying Sturges rule (k = 1 + 3,322 log n, where n = the number of data), we have: $k = 1 + 3.322 \: log \: 40 \approx 6.32$ As the value of k must be a natural number, 6.32 is rounded up to 7, so k = 7. Step 3: Determine the class width (c) To find c, use $
Post a Comment
Read more

THE QUARTILES AND MEDIAN OF GROUPED DATA

In this post,  we will learn how to determine the quartiles when some quantitative data are presented in a frequency distribution table. For example, we have the following data, showing Flesch Readability Score of 80 monthly bulletin articles published by Britt and Co. Ltd. Find the quartiles of these readability scores. To answer this, first augment the table with a new column to the right of the frequency column, namely Data Numbers column. There are 5 data in the first class, so the class contains data no. 1 to  no. 5. There are 7 data in the second class, so the class contains data no. 6 to no. 12. There are 13 data in the third class, so the class contains data no. 13 to no. 25. Continuing this way, we get the following: In this case, finding the first quartile means finding the  20 th  data, after the data have been ordered from the smallest to the highest (20 = ¼ x 80). Note that the  20 th  data is in the third class (20 is in the range of 13 - 25, as s
Post a Comment
Read more

CALCULATING THE MEAN OF GROUPED DATA

Sometimes quantitative data are presented in the form of a frequency distribution table (FDT). A typical FDT is as follows. Suppose that the table above presents the duration of 16 cell phone conversations between pairs of teens. There are 2 conversations with duration from 30 seconds to 44 seconds, 3 conversations with duration from 45 seconds to 59 seconds, etc. How do we calculate the mean of the data? Step 1: Determine the midpoint of each class If M i denotes the midpoint of class i, $M_{i} = \frac{LB_{i}+UB_{i}}{2}$ where  LB i  = lower bound of class i and  UB i  = upper bound of class i. The lower bounds of class 1, 2, 3, 4, 5 are 30, 45, 60, 75, 90, respectively and the upper bounds are 44, 59, 74, 89, 104, respectively. Then, $M_{1} = \frac{30+44}{2} = 37$.  Similarly, $M_{2} = \frac{45+59}{2} = 52$. Continuing this way, we have the following table. Step 2: Multiply each class frequency f i by the corresponding class midpoint M i , resulting in f i M
Post a Comment
Read more