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Use these methods to normalize the following group of data:
200, 300, 400, 600, 1000
a) min-max normalization by setting min = 0 and max = 1
b) z-score normalization
c) normalization by decimal scaling

Respuesta :

augustesabrina62

Step-by-step explanation:

b is the answer , z-score normalization

fichoh

Normalization is applied to data values in other to ensure that the data scales well, such that data values conforms to a certain range. The output of the various normalization techniques are given below ;

Given the data:

  • 200, 300, 400, 600, 1000

1.)

Min - Max normalization :

  • [tex]\frac{value - min}{max - min} [/tex]

  • Min = minimum = 200

  • Max = maximum = 1000

Value = 200 :

[tex]\frac{200 - 200}{1000 - 200} = 0[/tex]

Value = 300 :

[tex]\frac{300 - 200}{1000 - 200} = 0.125[/tex]

Value = 400 :

[tex]\frac{400 - 200}{1000 - 200} = 0.25[/tex]

Value = 600 :

[tex]\frac{600 - 200}{1000 - 200} = 0.5[/tex]

Value = 1000 :

[tex]\frac{1000 - 200}{1000 - 200} = 1[/tex]

Normalized values = (0, 0.125, 0.25, 0.5, 1)

2.)

Zscore normalization :

  • [tex]\frac{value - μ}{σ} [/tex]

Using a calculator :

  • Mean, μ = 500
  • Standard deviation = 316.227

Value = 200 :

[tex]\frac{200 - 500}{316.227} = -0.949[/tex]

Value = 300 :

[tex]\frac{300 - 500}{316.227} = -0.632[/tex]

Value = 400 :

[tex]\frac{400 - 500}{316.227} = -0.316[/tex]

Value = 600 :

[tex]\frac{600 - 500}{316.227} = 0.316[/tex]

Value = 1000 :

[tex]\frac{1000 - 500}{316.227} = 1.581[/tex]

Normalized values = (-0.949, -0.632, -0.316, 0.316, 1.581)

3.)

Decimal Scaling :

  • Maximum value = 1000

  • Hence, we can divide our values by 10000

200 / 10000 = 0.02

300/1000 = 0.03

400/1000 = 0.04

600/1000 = 0.06

1000/1000 = 0.1

Hence, the Normalized values (0.02, 0.03, 0.04, 0.06, 0.1)

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