Write the value of the (log) likelihood for the fitted glm model and the value of the deviance for comparing the glm fit against the maximal model An abrasion test was performed using n = 14 moulded ceramic pieces. The following are the test results,where for the i-th piece, the result of the test was recorded (one of Survived, Broken). The data also gives x₁,the porosity index of the piece, which is a numerical quantity:(Survived,8), (Broken,16), (Broken,19), (Survived,26), (Survived,49), (Survived,54), (Survived,66),(Survived, 79), (Survived,102), (Broken,111), (Survived,114), (Broken,151), (Survived,163), (Broken,199)We want to study the resistance of pieces to abrasion as function of porosity. To this end, consider thefollowing logistic regression model,log( · ) = B₁ + B₁x₁₂πiπ iwhere the observations follow the distribution Y; Bernoulli(₂). A data value yi = 1 indicates that thepiece survived the test and y; O indicates that the piece broke. Fit this model in R using the function=

The data also gives x1, the porosity index of the piece, which is a numerical quantity: (Survived,…

Answered: Write the value of the (log) likelihood…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The maximum weights (in kilograms) for which one repetition of a half squat can be performed and the times (in seconds) to run a 10-meter sprint for 12 international soccer players are shown in the attached data table with a sample correlation coefficient r of -0.908. A 13th data point was added to the end of the data set for an international soccer player who can perform the half squat with a maximum of 205 kilograms and can sprint 10 meters in 1.98 seconds. Describe how this affects the correlation coefficient r. Use technology. Click the icon to view the data set. The new correlation coefficient r (Round to three decimal places as needed.) going from 0.908 to Data table Player 1 Ñ Ñ = 560 000 A W N 10 11 12 13 Print Maximum weight, x Time, y 1.81 1.77 2.04 1.43 2.04 1.61 1.71 1.88 1.59 1.63 1.98 1.91 1.98 170 180 160 205 150 195 180 155 185 175 155 175 205 Done X
Suppose the performance of a pile foundation system is governed by the pile with the smallest capacity. The weakest pile associated with this foundation system follows a type III asymptotic distribution of the smallest value with = 2 tons, a mean value of 15 tons and a coefficient of variation of 20%. Determine the probability that the weakest pile of this system will have capacity less than the design load of 10 tons.
What formula can we use to solve maximum likelihood estimate of regression coefficient beta in Poisson regression (with log link)?
The following data was collected to analyze whether temperature correlates with bacterial growth. Five recombinant strains of E. coli that each grows optimally at different temperatures were grown for 6 hours and their concentration was measured. Plot a xy scatter graph with a line of best fit to determine whether there is a correlation between temperature and growth rate
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A multiple regression predicting tech salaries obtains an insignificant (zero) coefficient on age and a significantly negative coefficient on being foreign-born. A simple regression of tech salaries on age obtains a significantly positive coefficient on age. These results can be explained if Group of answer choices a) the simple regression coefficient is unbiased. b) foreign-born tech workers tend to be older than non-foreign-born. c) foreign-born tech workers tend to be younger than non-foreign-born. d) age is unrelated to being foreign-born.
A study is conducted to investigate the association between income level and political party affiliation in the USA. Income level has 5 levels: Lowest (lowest 20-th percentile), low, middle, high, and very high (top 20-th percentile). Political party has 3 categories: Democratic (D), Independent (I), and Republican (R). A baseline category logit multinomial is fit on the 3 response categories using covariate of income level as ordinal (with scores 1, 2, 3, 4, and 5 for the categories lowest, low, middle, high and very high respectively). Base category of response is Independent. The fitted model is log(ˆπD/πˆI ) = 3.3 − 0.2x and log(ˆπR/πˆI ) = 1.0 + 0.3x, where x=1,2,3,4,5 (poverty levels as numeric/ordinal), πD is the probability of being Democrat, πI is the probability of being Independent, and πR is the probability of being Republican. a. Comparing the chances/probability of being Republican to Independent, interpret the effect of income level increases on the odds (of being…
Donating Blood to Grandma?Can young blood help old brains? Several studies1 in mice indicate that it might. In the studies, old mice (equivalent to about a 70-year-old person) were randomly assigned to receive blood plasma either from a young mouse (equivalent to about a 25-year-old person) or another old mouse. The mice receiving the young blood showed multiple signs of a reversal of brain aging. One of the studies2 measured exercise endurance using maximum treadmill runtime in a 90-minute window. The number of minutes of runtime are given in the table below for the 17 mice receiving plasma from young mice and the 13 mice receiving plasma from old mice. The data are also available in YoungBlood. Young 27 28 31 35 39 40 45 46 55 56 59 68 76 90 90 90 90 Old 19 21 22 25 28 29 29 31 36 42 50 51 68 Round your answers to two decimal places.(a) Calculate , the mean number of minutes on the treadmill for those mice receiving young blood.Enter your answer in…
The table shows the results after regressing probability of buying coke on coke ratio, displaying coke, and displaying pepsi. The latter two covariates are dummy variables. Please interpret the following coefficents and standard errors from the probit model.
I have transportation data with a year variable, categorical and continuous variables. I tried to create a cross section by concatenating all the categorical variables together then regress on the continuous variables with revenue as my dependent variable using Pooled OLS. Unfortunately, i have serial correlation in my model and i am not able to remove the serial correlation. Alternatively, i was thinking of looking at just one year of data or treating the data as a single cross section, including year dummy variables and selecting specific categorical variables as additional dummy variables to determine the effect on revenue. Any issues with that approach or alternative recommendations? Also, its worth noting that i had to remove 15% of my data to ensure each cross section that i created had a year from 2011-2017 to allow me to run the proc panel in SAS.
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Im regressing a model with an endogenous variable as an independent variable, and using the Multiple Indicator approach. Whats assumptions needed for the Betas to be “identified”, and separately the Beta estimates to be “consistent”? What do we mean by “identified” and “consistent”?

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