Q3. You are given the following information for a mortality study with right-censored data. Thestudy begins at time 0 with 40 individuals.Time Number of Deaths Number Censored2TIT37023568INST 5| co | cond the upper limit of the 95% log-transformation confience interval for S(8).

Given the information for a mortality study with right-censored data as Time Number of Deaths…

Answered: Q 3. You are given the following…

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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Compare the three samples - monodisperse or disperse? Bimodal or multimodal?
4. When the Titanic sank in 1912, there were over 1,300 passengers aboard. A random sample of 50 passengers that were aboard is taken. The amount they paid for the voyage and whether or not they survived is recorded. A model is fit to predict the probability they survived when the ship sank is obtained. Survived Logistic Fit of Survived By Fare 1.00 0.75 0.50- 0.25- 50 4 Parameter Estimates 100 Term Intercept -1.404254 0.4353289 Fare 0.01246686 0.0097945 For log odds of Yes/No Fare Estimate Std Error ChiSquare 10.41 1.62 150 200 Prob> ChiSq 0.0013 0.2031 No Yes a) Suppose someone paid a fare of 25 pounds. Predict the probability they survived. b) How much would someone pay to have at least a 65% chance of survival?
Q2. You collected 500 weeks of data (2500 days total). Based on that you find Tuesday's mean return is 12 bps. Mean return of all days is 2 bps. Stdev across all days is 100 bps. There is no noticeable difference b/w Tuesday stdev vs other weekdays' stdev. Based on q1c find D Q1c. what is the mean log return and stdev of log return over one year period and four year period (assuming 252 trading days per year)? Q1d. based on Q1c what is the probably of losing money (negative log return) or doubling your money (total log return = ln(2)) over 1 year and 4 year period?
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Can gender, educational level, and age predict the odds that someone votes for a particular candidate in the election? Over 1500 voters were selected, and data were col-lected on the highest year of school completed, their age, and their gender. We wish to t a logistic regression model: log(1 p p ) = 0 + 1Age + 2Education + 3Gender, where p is the binomial probability that a person voted for candidate Johnson, and gender is coded as the indicator for female. The R output is given below. parameter df estimate s.e z p-value (Intercept) 1 .1119 .3481 .321 .748 Age 1 .0020 .0032 .613 .54 Education 1 -.0100 .0184 .547 .585 Gender 1 .4282 .1040 4.117 .000 Null deviance: 255.95 on 1499 degrees of freedom Residual deviance: 220.80 on 1496 degrees of freedom Write down the tted logistic regression and give a short summary about the data analysis . Calculate the probability of voting for Johnson for a…
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Q1. 807 people were randomly selected and data was collected on whether or not they smoked cigarettes in the past 12 months (smoked = 1 if they did, smoked = 0 otherwise), their years of schooling (educ), the natural log of their annual income in dollars (In[income]), age in years (age), and race (white = 1 if white, white = 0 otherwise). The following logit models were estimated and the results are summarized in the table below. The numbers in parentheses are the standard errors. (1) logit (2) logit (3) sample average constant 1.43 0.02 (0.40) (1.06) educ -0.10 -0.11 12 (0.03) (0.03) In[income] 0.16 10.8 (0.11) age -0.02 -0.02 41 (0.0004) | (0.0004) white 0.02 0.7 (0.23) log-likelihood -525 -524 In column (2), the regression equation for smokeď* is: smoked* = x'3 + e = B1 + B2educ + B3 In[income] + B4age + B5white + e In column (3), the sample averages of the regressors are listed. For example, 12 is the sample average of educ, 10.8 is the average of In[income], etc. (a) Using the…
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Out of 100 patients, 41 were not cured and 59 were cured. The 41 not cured, 25 were not given treatment and 16 were given. Of 59 cured, 22 were not given treatment and 37 were given treatment. If control condition is no treatment given then slope of logit is equal to?"
When we fit a logistic regression model with a single explanatory term, x, we often assume that logit (pi) Bo + ₁x₂ where, for the ith observation, p; is the probability of a trial being successful and *; is the value of the explanatory variable. Which of the following is a good reason for using the logit link function? We can't use more than one explanatory term unless we use this link function. It allows us to model nonconstant variance in the response variable. It ensures that the probability of success is between 0 and 1. It ensures that the variance of the response is the same for all observations.

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Q 3. You are given the following information for a mortality study with right-censored data. The study begins at time 0 with 40 individuals. Time Number of Deaths Number Censored 0235060 8 2 3 7 5 3 - 3 1 Find the upper limit of the 95% log-transformation confidence interval for S(8).