R-Studio 1.) You have an airport routes.csv file that contains 3409 airports, each row has a 3-letter code and the number of routes.  Example:  Airport NumberOfRoutes AAE 9 AAL 20 AAN 2 AAQ 3 AAR 8 AAT 2 AAX 1 AAY 1 ABA 4 ABB 2 ABD 6 ABE 13 ABI 2 ABJ 49 ABL 4 ABM 1 ABQ 42 ABR 1 ABS 1 ABT 3 ABV 30 ABX 4 ABY 4 ABZ 41 ACA 8 ACC 54 ACE 116 ACH 2 ACI 2 ACK 6 ACR 2 ACT 2 ACU 1 ACV 3 ACX 6 ACY 10 ACZ 1 ADA 17 ADB 66 ADD 105 ADE 23 ADF 2 ADK 1 ADL 51 ADQ 11 ADU 3 ADZ 11 AEB 3 AEP 65 For this dataset, consider the following models: (a) Suppose the given data points follow a power law distribution. Estimate the corresponding α  parameter.  (b) Suppose the given data points follow an exponential distribution. Estimate the corresponding λ  parameter.  (c) Suppose the given data points follow a uniform distribution. Estimate the corresponding range  parameters [a, b] of the uniform distribution. (d) Suppose the given data points follow a normal distribution. Estimate the corresponding µ and σ  parameters.

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Author:James Kurose, Keith Ross
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1.) You have an airport routes.csv file that contains 3409 airports, each row has a 3-letter code and the number of routes. 

Example: 

Airport NumberOfRoutes
AAE 9
AAL 20
AAN 2
AAQ 3
AAR 8
AAT 2
AAX 1
AAY 1
ABA 4
ABB 2
ABD 6
ABE 13
ABI 2
ABJ 49
ABL 4
ABM 1
ABQ 42
ABR 1
ABS 1
ABT 3
ABV 30
ABX 4
ABY 4
ABZ 41
ACA 8
ACC 54
ACE 116
ACH 2
ACI 2
ACK 6
ACR 2
ACT 2
ACU 1
ACV 3
ACX 6
ACY 10
ACZ 1
ADA 17
ADB 66
ADD 105
ADE 23
ADF 2
ADK 1
ADL 51
ADQ 11
ADU 3
ADZ 11
AEB 3
AEP 65

For this dataset, consider the following models:
(a) Suppose the given data points follow a power law distribution. Estimate the corresponding α 
parameter. 
(b) Suppose the given data points follow an exponential distribution. Estimate the corresponding λ 
parameter. 
(c) Suppose the given data points follow a uniform distribution. Estimate the corresponding range 
parameters [a, b] of the uniform distribution.
(d) Suppose the given data points follow a normal distribution. Estimate the corresponding µ and σ 
parameters.

 

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