Using the dataset "Taxi ridership data": (1) Using X = Driver's year of employment (work experience) and Y = Number of passengers served in a day, fit a Poisson loglinear model. Report the prediction equation. (2) Estimate the mean of Y for drivers with an average work experience of 2.44 years. (3) Use to describe the effect of work experience. Construct a 95% confidence interval for ß and for the multiplicative effect of a 1 year increase.< (4) Conduct a Wald test of the hypothesis that the mean of Y is independent of work experience. Interpret. (5) Conduct a likelihood-ratio test about the work experience effect. Interpret.<
Using the dataset "Taxi ridership data": (1) Using X = Driver's year of employment (work experience) and Y = Number of passengers served in a day, fit a Poisson loglinear model. Report the prediction equation. (2) Estimate the mean of Y for drivers with an average work experience of 2.44 years. (3) Use to describe the effect of work experience. Construct a 95% confidence interval for ß and for the multiplicative effect of a 1 year increase.< (4) Conduct a Wald test of the hypothesis that the mean of Y is independent of work experience. Interpret. (5) Conduct a likelihood-ratio test about the work experience effect. Interpret.<
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
question as per image and "taxi rideship data" as per below:\
| X | Y |
| 3.05 | 8 |
| 2.6 | 4 |
| 2.15 | 0 |
| 1.85 | 0 |
| 3 | 1 |
| 2.3 | 3 |
| 1.3 | 0 |
| 2.1 | 0 |
| 2 | 8 |
| 3.15 | 6 |
| 2.8 | 5 |
| 2.8 | 4 |
| 3.6 | 3 |
| 1.6 | 4 |
| 2.3 | 3 |
| 2.05 | 5 |
| 3.05 | 8 |
| 2.4 | 3 |
| 2.25 | 6 |
| 2.25 | 4 |
| 2.9 | 0 |
| 2.25 | 3 |
| 1.7 | 0 |
| 3.2 | 0 |
| 1.97 | 1 |
| 1.6 | 1 |
| 2.9 | 1 |
| 2.3 | 4 |
| 2.1 | 2 |
| 1.4 | 0 |
| 3.28 | 2 |
| 2.3 | 0 |
| 2.3 | 6 |
| 2.25 | 10 |
| 2.4 | 5 |
| 3.32 | 3 |
| 2.1 | 8 |
| 3 | 9 |
| 1.6 | 0 |
| 1.85 | 2 |
| 2.28 | 3 |
| 2.2 | 0 |
| 3.28 | 4 |
| 2.35 | 0 |
| 1.55 | 0 |
| 2.1 | 0 |
| 2.15 | 0 |
| 2.3 | 14 |
| 2.2 | 0 |
| 1.6 | 1 |
| 3.15 | 3 |
| 3.2 | 4 |
| 2.7 | 5 |
| 1.9 | 0 |
| 2.5 | 6 |
| 2.6 | 6 |
| 2.1 | 5 |
| 2 | 5 |
| 2.75 | 0 |
| 2.45 | 3 |
| 3.2 | 10 |
| 2.8 | 7 |
| 1.9 | 0 |
| 1.2 | 0 |
| 1.65 | 0 |
| 3.05 | 0 |
| 3.85 | 5 |
| 1.55 | 0 |
| 2.2 | 1 |
| 2.55 | 1 |
| 2.4 | 1 |
| 3.25 | 3 |
| 3.33 | 2 |
| 2.4 | 5 |
| 2.22 | 0 |
| 3.2 | 3 |
| 1.95 | 6 |
| 3.05 | 7 |
| 2.25 | 6 |
| 2.92 | 3 |
| 3.73 | 4 |
| 2.85 | 4 |
| 1.9 | 0 |
| 1.8 | 0 |
| 3.05 | 8 |
| 1.8 | 0 |
| 2.62 | 0 |
| 2.3 | 9 |
| 1.9 | 0 |
| 2.65 | 0 |
| 2.95 | 8 |
| 2.7 | 5 |
| 2.6 | 2 |
| 2.7 | 5 |
| 2.6 | 0 |
| 1.85 | 0 |
| 2.8 | 6 |
| 3.3 | 5 |
| 2.1 | 4 |
| 2.9 | 5 |
| 3 | 15 |
| 2.25 | 0 |
| 2.15 | 5 |
| 2.4 | 0 |
| 1.65 | 1 |
| 1.6 | 0 |
| 2.1 | 5 |
| 2.55 | 4 |
| 2.75 | 0 |
| 2.55 | 0 |
| 2.8 | 1 |
| 3 | 1 |
| 2.55 | 4 |
| 3.1 | 1 |
| 2.5 | 6 |
| 1.8 | 0 |
| 2.5 | 6 |
| 1.65 | 2 |
| 1.47 | 4 |
| 1.8 | 0 |
| 2.2 | 0 |
| 2.63 | 6 |
| 2 | 0 |
| 3.02 | 4 |
| 2.3 | 0 |
| 1.95 | 4 |
| 3.5 | 4 |
| 2.15 | 0 |
| 2.17 | 2 |
| 2.63 | 0 |
| 2.1 | 0 |
| 1.95 | 0 |
| 3.05 | 11 |
| 2 | 1 |
| 1.95 | 4 |
| 2 | 3 |
| 2.6 | 0 |
| 2 | 0 |
| 2.65 | 0 |
| 3.1 | 3 |
| 3.25 | 9 |
| 3 | 3 |
| 2.7 | 6 |
| 2.7 | 3 |
| 2.55 | 0 |
| 2.8 | 1 |
| 1.3 | 0 |
| 1.8 | 0 |
| 2.2 | 3 |
| 2.25 | 0 |
| 2.3 | 0 |
| 1.9 | 0 |
| 2.45 | 0 |
| 2.25 | 0 |
| 2.87 | 1 |
| 2 | 1 |
| 1.9 | 2 |
| 2.1 | 0 |
| 3.23 | 12 |
| 1.8 | 6 |
| 2.9 | 3 |
| 2.02 | 2 |
| 2.9 | 4 |
| 3.1 | 5 |
| 5.2 | 7 |
| 2.4 | 0 |
| 1.9 | 10 |
| 2 | 0 |
| 3.2 | 0 |
| 2.35 | 4 |
| 2.75 | 7 |
| 2.75 | 3 |
| 2 | 0 |
Transcribed Image Text:Using the dataset "Taxi ridership data":<
(1) Using X = Driver's year of employment (work experience) and Y = Number of
passengers served in a day, fit a Poisson loglinear model. Report the prediction
equation.<
(2) Estimate the mean of Y for drivers with an average work experience of 2.44
years.
(3) Use to describe the effect of work experience. Construct a 95% confidence
interval for ß and for the multiplicative effect of a 1 year increase.<
(4) Conduct a Wald test of the hypothesis that the mean of Y is independent of
work experience. Interpret.
(5) Conduct a likelihood-ratio test about the work experience effect. Interpret.<
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