Consider a 1-dimensional logistic regression problem with parameters (w, b) where w and bare scalars. Consider a datasample x = 2, with label y = 0. If the output of the logistic neuron is 0.6. What is the value of gradient d, where L(.) isthe logistic loss.dwO 1.2O -1.2-0.80.8 (True or False) The gradient of an objective function L(w) where (w E Rd) is a vector in the parameter space of wwhose direction points to the maximum increase in L(w).FalseTrue

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Answered: Consider a 1-dimensional logistic…

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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One of the standard curves used is harmonic decline model, that is: Q = bx/(1+ ax²) where Q is the rate of production and x is the time, b and a are the constants of the regression model. If we apply linear least squares fit for estimating b and a, what will be the value of the summation of squared errors.S Sr x, Months 11 16 18 22 90 75 65 Q, Barrels/Day 1 9 44 100 50 Sr= {(y- P(x)} 2 - (9,- #2) ²
Please help find estimator of beta 0. Image of question attached.
Consider the following estimated model, where the dependent variable is the log of the hourly wage: log(wage) = 0.417 - 0.238female + 0.17educ + 0.0232 exper - 0.00058exper? +0.0295tenure – 0.00059tenure? female 1 if the person is female, and 0 if the person is male educ = level of education, in years exper = level of expertise, in years tenure = duration of tenure, in years Given that the above regression model has 313 observations, then its degrees of freedom is equal to For the same levels of education, expertise, and tenure, women earn exactly % less compared to men, holding other factors fixed.
We are interested in estimating the following model log(wage) = Bo + Bieduc + Bzexper + u where • wage=hourly wage, in US dollars; • educ=number of years of education; • exper=number of years of work experience. The variable ctuit is the change in college tuition facing students from age 17 to age 18 and is used as an IV for educ. We run the first stage regression for educ and get the following output: Source s df MS Number of obs 1,230 F (2, 1227) 550.19 Model 3220.84426 2 1610.42213 Prob > F 0.0000 Residual 3591.43541 1,227 2.92700523 0.4728 R-squared Adj R-squared 0.4719 Total 6812.27967 1,229 5.54294522 Root MSE 1.7108 educ Coef. Std. Err. t P>|t| [95% Conf. Interval] ctuit -.1859575 .0608175 -3.06 0.002 -.3052752 -.0666398 exper -.521161 .0157156 -33.16 0.000 -.5519933 -.4903286 _cons 18.63905 .1757961 106.03 0.000 18.29415 18.98394 Is the assumption of instrument relevance satisfied? Why yes, or why not?
3. Suppose that the following import function for Turkey is estimated for Turkey between 1980-2015. Import, a, + a,GDP; + ażER¸ + ut In order to measure the impact of 2001 crisis the regression is estimated based on the whole and two subsamples and the following RSS are obtained. Time period: 1980-2000 , RSS1= 69 Time period: 2001-2015, RSS2 =35 Time period: 1980-2015 , RSS = 160 Carry out the Chow test whether the regressions for the two periods are different at 5% significance level. (35 P)
The following data on x maternal age in years of the young birth mothers and y = weight of baby born in grams summarizes the result of a study. Assume that a simple linear regression model y = Bo + B1x + e is an appropriate model for the study. x-bar = 17 (avg of x's) y-bar = 3004.1 (avg of y's) SSx = 20 SSxy %3D 4903 SSw 1539182.9 n 10 Calculate the value of s-(standard error of regression) and enter the answer to the nearest tenth (1 decimal place).
Question 38. You have performed a linear regression analysis to explore sunflowers' growth (in meters per month) depending on the watering (in litres per day). You have estimated the regression coefficient to be ß = 1.6. What can you conclude? a) There is a signifleant correlation between watering and growth. b) An average sunflower growths 1.6 meters per month. c) If you give it an additional litre of water per day, there will be an additional average growth of 1.6 meters per month. d) According to the model assumptions, an additional litre of water per day will result in additional 19.2 meters of growth after one year. e) You should consider further influencing quantities.
Question 10. What is the expected value of the elasticity of education on wages for a person ith 15 years of education at its expected wage? (a) 1.5 (b) 150 160 15.15 (c) 150 (d) 1 (e) 160 150

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Consider a 1-dimensional logistic regression problem with parameters (w, b) where w and b are scalars. Consider a data sample x = 2, with label y = 0. If the output of the logistic neuron is 0.6. What is the value of gradient dL dw where L(.) is the logistic loss. O 1.2 O -1.2 -0.8 0.8