What is a range in statistical dispersion?

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  • J

    Answered by

    Jaya Sharma | Contributor-Level 10

    2 months ago
    It is the measure of statistical dispersion which shows the difference between the maximum and minimum values of the dataset. This provides a simple method for understanding the data spread. The formula used here is: 
     
    Range = Maximum Value-Minimum Value
     
    A range is easy to understand, therefore, easy to calculate. This makes it useful as an initial measure of variability. It is highly sensistive to outliers which means if there are extreme values in dataset, range can be significantly impacted. This will give misleading impression of data spread.

Similar Questions for you

A
alok kumar singh

Variance = x 2 n ( x ¯ ) 2  

6 0 2 + 6 0 2 + 4 4 2 + 5 8 2 + 6 8 2 + α 2 + β 2 + 5 6 2 8 = ( 5 8 ) 2 = 6 6 . 2            

7 2 0 0 + 1 9 3 6 + 3 3 6 4 + 4 6 2 4 + 3 1 3 6 + α 2 + β 2 8 = 3 3 6 4 = 6 6 . 2             

2 5 3 2 . 5 + α 2 + β 2 8 3 3 6 4 = 6 6 . 2            

α2 + β2 = 897.7 × 8

= 7181.6

A
alok kumar singh

xi

fi

c.f.

0 – 4

4 – 8

8 – 12

12 – 16

16 – 20

2

4

7

8

6

2

6

13

21

27

N = f = 2 7

( N 2 ) = 2 7 2 = 1 3 . 5

So, we have median lies in the class 12 – 16

I1 = 12, f = 8, h = 4, c.f. = 13

So, here we apply formula

M = I 1 + N 2 c . f . f × h = 1 2 + 1 3 . 5 1 3 8 × 4

= 1 2 + 5 2

M = 2 4 . 5 2 = 1 2 . 2 5

20 M = 20 × 12.25

= 245

A
alok kumar singh

  a + b + 6 8 + 4 4 + 4 0 + 6 0 6 = 5 5

212 + a + b = 330

a + b = 118

x i 2 n ( x ¯ ) 2 = 1 9 4          

a 2 + b 2 + ( 6 8 ) 2 + ( 4 4 ) 2 + ( 4 0 ) 2 + ( 6 0 ) 2 6 = ( 5 5 ) 2 = 1 9 4

= 3219

11760 + a2 + b2 = 19314

a2 + b2 = 19314 – 11760

= 7554

(a + b)2 –2ab = 7554

From here b = 41.795

a + b = 118

a + b + 2b = 118 + 83.59

= 201.59

A
alok kumar singh

Kindly go throuigh the solution

Given   i = 1 1 8 ( x i α ) = 3 6 i . e i = 1 1 8 x i 1 8 α = 3 6 . . . . . . . . . . ( i )

&       i = 1 1 8 ( x i β ) 2 = 9 0 i . e i = 1 1 8 x i 2 2 β x i + 1 8 β 2 = 9 0 . . . . . . . . . . . . . ( i i )      

(i) & (ii)   i = 1 1 8 x i 2 = 9 0 1 8 β + 3 6 β ( α + 2 ) . . . . . . . . . . . . . ( i i i )

Now variance σ 2 = x i 2 n ( x i n ) 2 = 1 given

->(a - b) (a - b + 4) = 0

Since α β s o | α β | = 4  

 

V
Vishal Baghel

M e a n = 3 + 1 2 + 7 + a + ( 4 3 a ) 5 = 1 3  

Variance = 3 2 + 1 2 2 + 7 2 + a 2 + ( 4 3 a ) 2 5 ( 1 3 ) 2  

2 a 2 a + 1 5 N a t u r a l n u m b e r      

Let 2a2 – a + 1 = 5x

D = 1 – 4 (2) (1 – 5n)

= 40n – 7, which is not 4 λ o r 4 λ + 1 f r o m .  

As each square form is 4 λ o r 4 λ + 1  

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