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.
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.
Computer Networking: A Top-Down Approach (7th Edition)
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ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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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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