What does mean absolute deviation MAD measure explain how do you find the mad for a set of data?

The measure of spread represents the amount of dispersion in a data-set. i.e how spread-out are the values of data-set around the central value(example- mean/mode/median).It tells how far away the data points tend to fall from the central value.

  • The lower value of the measure of spread reflects that the data points are close to the central value. In this case, the values in a data-set are more consistent.
  • Further, the distance of the data points from the central-value, the greater is the spread. whereas here, the values are not much consistent.

What does mean absolute deviation MAD measure explain how do you find the mad for a set of data?

Distribution of Data

Using the above diagram, we can infer that the narrow distribution represents a lower spread, and the broad distribution represents a higher spread.

Range

The range is the simplest measure of variation. It is defined and calculated as the difference between the largest and smallest values of the data-set.

Range = largest value – smallest value

  • A small value of range means the data is quite consistent and most of the data-points lie near to the mean.
  • Whereas a higher range means the data is quite inconsistent and the data has extreme values, and the data-points don’t lie near to the mean.
  • The range doesn’t consider each value of the dataset. Thus, it gives a rough idea of the data-set and its variability.

Examples

Example 1: The data given are: 8, 10, 4, 1, 15. Calculate the range of the given data?

Solution

The data in ascending order is = 1  4  8  10  15.

Range = largest – smallest

           = 15 – 1

Range = 14

Example 2: What is the range of these integers?

14, -18, 7, 0, -5, -8, 15, -10, 20

Solution: 

The data in ascending order is =  -18, -10, -8, -5, 0, 7, 14, 15, 20

Range = largest – smallest

           = 20 – (-18)

Range = 38

Example 3: Calculate the range of the given data:

8, 10, 5 , 14 , 42, 3566

Solution: 

The data in ascending order is = 5, 8, 10, 14, 42, 3566

Range = largest – smallest

           = 3566 – 5

Range = 3561

Mid-Range

The mid-range is the value midway between the largest and smallest value of a data-set. It is calculated as the mean of the largest value and smallest value of the data-set.

Mid-Range = (largest value + smallest value)/2

Examples

Example 1: The data given is 8, 10, 5, 9, 11. Calculate the mid-range of the given data?

Solution: 

The data in ascending order is = 5 8 9 10 11

Mid-Range = (largest value + smallest value)/2

                   = (5 + 11)/2

                   = 16/2

mid-range = 8

Example 2: You take 7 statistics tests over the course of a semester. You score 94, 88, 74, 84, 91, 87 and 79. What is the mid-range of your scores?

Solution: 

The scores in ascending order is = 74 79 84 87 88 91 94

Mid-Range = (largest value + smallest value)/2

                   = (94 + 74)/2

                   = 168/2

mid-range = 84

Example 3: The height of 8 students in centimeters is given as  120, 132, 117, 126, 110, 135, 150, and 143. Calculate the mid-range of the given data?

Solution: 

The scores in ascending order is = 110 117 120 126 132 135 143 150 

Mid-Range = (largest value + smallest value)/2

                   = (150 + 110)/2

                   = 260/2

mid-range = 130

Mean Absolute Deviation (MAD)

The mean absolute deviation (MAD) of a data-set is the average distance between each data point of the data-set and the mean of data. i.e it represents the amount of variation that occurs around the mean value in the data-set. It is also a measure of variation. It is calculated as the average of the sum of the absolute difference between each value of the data-set and the mean. 

MAD = (∑ |xi – mean| ) ÷ n 

where 1 < i < n and n is the number of data-points in the data-set.

Examples

Example 1: The data-set is 11 , 15 , 18 , 17 , 12 , 17. Calculate the mean absolute deviation of the given data-set?

Solution:

Step 1: Calculating the mean 

x̅ =  (x1 + x2 + x3 + …… + xn) / n

x̅ = (11 + 15 + 18 + 17 + 12 + 17 ) / 6 

x̅ = 15 

The mean of the given data = 15 

Step 2: Calculating the absolute difference between each data-point and mean.

Data-Point

Absolute Difference from mean 

11

|11 – 15| = 4 

12

|12 – 15| = 3

15

|15 – 15| = 0

17

|17 – 15| = 2

17

|17 – 15| = 2

18

|18 – 15| = 3

Step 3: Adding the Absolute Difference together

(∑ |xi – mean| ) = 4 + 3 + 0 + 2 + 2 + 3 

(∑ |xi – mean| ) = 14 

Step 4: Dividing the sum of absolute difference and the number of data-points.

MAD =  (∑ |xi – mean|) ÷ n 

MAD = 14/6 

MAD = 2.33

Hence, we can conclude that, on average, each data-point is 2 distance away from the mean. 

Example 2: The following table shows the number of oranges that grew on Nancy’s orange tree each season

Season

Number of Oranges

Winter

5

Summer

17

Spring

24

Fall

10

Find the mean absolute deviation (MAD) of the data set?

Solution:

Step 1: Calculating the mean

x̅ =  (x1 + x2 + x3 + …… + xn) / n

x̅ = (5 + 17 + 24 + 10) / 4

x̅ = 56/4

The mean of the given data = 14

Step 2: Calculating the absolute difference between each data-point and mean

Data-Point

Absolute Difference from mean 

5 |5 – 14| = 9 
17 |17 – 14| = 3 
24 |24 – 14| = 10
10 |10 – 14| = 4

Step 3:Adding the Absolute Difference together

(∑ |xi – mean| ) = 9 + 3 + 10 + 4 

(∑ |xi – mean| ) = 26

Step 4: Dividing the sum of absolute difference and the number of data-points

MAD =  (∑ |xi – mean| ) ÷ n

MAD = 26 / 4

MAD = 6.5

Example 3: Consider the following data-set

Name of the student

Marks in Maths

Chetan 90
Shubham 74
Riya 80
Manu 92

Calculate the mean absolute deviation of the given data?

Solution:

Step 1: Calculating the mean

x̅ =  (x1 + x2 + x3 + …… + xn) / n

x̅ = (90 + 74 + 80 + 92) / 4

x̅ = 336/4

The mean of the given data = 84

Step 2: Calculating the absolute difference between each data-point and mean

Data-Point

Absolute Difference from mean 

90 |90 – 84| = 6
74 |74 – 84| = 10 
80 |80 – 84| = 4
92 |92 – 84| = 8

Step 3: Adding the Absolute Difference together

(∑ |xi – mean| ) = 6 + 10 + 4 + 8

(∑ |xi – mean| ) = 28

Step 4: Dividing the sum of absolute difference and the number of data-points

MAD =  (∑ |xi – mean|) ÷ n

MAD = 28 / 4

MAD = 7


What does mean absolute deviation measure explain how do you find the MAD for a set of data?

Mean absolute deviation (MAD) of a data set is the average distance between each data value and the mean. Mean absolute deviation is a way to describe variation in a data set. Mean absolute deviation helps us get a sense of how "spread out" the values in a data set are.

How do you find the MAD in a set of data?

Take each number in the data set, subtract the mean, and take the absolute value. Then take the sum of the absolute values. Now compute the mean absolute deviation by dividing the sum above by the total number of values in the data set. Finally, round to the nearest tenth.

How do you calculate MAD deviation?

Median Absolute Deviation-subtract the median from each value in the data set and make the difference positive. Add up these quantities and divide by the number of values in the data set. Mean Absolute Deviation-subtract the mean from each value in the data set and make the difference positive.

How does the mean absolute deviation MAD of the data in set 1?

How does the mean absolute deviation (MAD) of the data in set 1 compare to the mean absolute deviation of the data in set 2? The MAD of set 1 is 5 less than the MAD of set 2. Without calculating any statistics, Jadyn knows that data set 1 would have the least mean absolute deviation among the three sets.