The following are observations (x₁, y;) taken from units in a textile process: (12,12), (12,17), (14,15), (14,18), (16,24), (20,31), (24,40). For the i-th unit, x; is the length of material and y; is the number of imperfections detected. It is assumed that the number of imperfections will be modelled with a generalized linear model considering a Poisson distribution and a logarithmic link for the linear predictor ni Po + P₁x₁. Analyze the data using the function glm in R and process the data
The following are observations (x₁, y;) taken from units in a textile process: (12,12), (12,17), (14,15), (14,18), (16,24), (20,31), (24,40). For the i-th unit, x; is the length of material and y; is the number of imperfections detected. It is assumed that the number of imperfections will be modelled with a generalized linear model considering a Poisson distribution and a logarithmic link for the linear predictor ni Po + P₁x₁. Analyze the data using the function glm in R and process the data
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 91E
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Find the quantity (deviance) for testing the hypothesis ?0H0 that data supports the glm fit against the alternative ?1H1 that data supports the maximal model.
B) the degrees of freedom and pvalue for testing H0
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