Consider the standard set of Gaussian Naïve Bayes assumptions used in thederivation of the logistic regression expression, but with one modification- the classconditional density for each class has unique values for both the mean and variance,rather than a common value for the variance, i.e P(X/Y=yk)=N(µic,Gix). Findthe expression for P(Y=1/X1 ,X2, ... Xm)boundary.in this case and find the decision

Answered: Image /qna-images/answer/355960b3-89a0-4b22-8bc5-63d1b069b883.jpg

Answered: Consider the standard set of Gaussian…

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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Consider a regression with two variables, in which X1i is the variable of interest and X2i is the control variable. The zero conditional mean assumption requires Group of answer choices E(ui|X1i) = E(ui|X2i) E(ui|X1i, X2i) = E(ui|X1i) E(ui|X1i, X2i) = 0 E(ui) = E(ui|X2i)
Table 4 above is displaying odds ratios for each predictor estimated by a multivariablelogistic regression model with all 6 predictors included at the same time. Based onthis model, what is the minimum number of in-hospital deaths they should have intheir dataset? A) 30 B) 50 C) 60 D) 70
A recent Gallup survey of a random sample of Americans (18 and older) found that the average number of alcoholic drinks consumed per week (drinks) by males was 4.2 and by females was 1.4.[1] Suppose we use the underlying survey data to estimate a least-squares regression of the average number of drinks a person reports consuming per week (Drinks;) on a dummy variable equal to 1 if i is female and O otherwise (Female;). (Assume all respondents identify as either male or female.) The estimated regression line equation can be written as: Drinks = a +bFemale Alcohol Consumption by Gender Because Female is a dummy variable, the problem provides us with enough information to figure out the exact regression line equation. What is the numerical value of a?
Solve the second question in regression analysis
A recent Gallup survey of a random sample of Americans (18 and older) found that the average number of alcoholic drinks consumed per week (drinks) by males was 4.2 and by females was 1.4.[¹] Suppose we use the underlying survey data to estimate a least-squares regression of the average number of drinks a person reports consuming per week (Drinks;) on a dummy variable equal to 1 if i is female and 0 otherwise (Female;). (Assume all respondents identify as either male or female.) The estimated regression line equation can be written as: Drinks = a +bFemale Alcohol Consumption by Gender What is the numerical value of b?
Bxi + €i, where €; are independently and Consider a simple linear regression model Y; = identically distributed with mean 0 and variance o?, and i = 1,..., n. Note: this model does not have a intercept term. Derive the Best Linear Unbiased Estimator (BLUE) for B. Denote this by BBLUE. Make sure to state why this is the BLUE.
ruan Use wage1.txt data set for this question. Consider the following regression: logtwage)-Bo-Beduc-3.exper+u. Suppose we want to test whether the return of an additional year in school will pay more than spending an additional year in the labor market Which of the following is the correct set of hypotheses for this test? Ho: 1-2 HA: 1-20 31 Ho: 1-2 HA: 1-8 270 Ho: 1-220HA: 1-³ 20 Ho: 1-2 HA: 1-820 0.91
Suppose x1 ans x2 are predictor variables for a response variable y. a. The distribution of all possible values of the response variable corresponding to particular values of the two predictor variables is called a distribution of the response variable. b. State the four assumptions for multiple linear regression inferences.
Suppose that you have estimated coefficients for the regression model Y = B₁ + B₁X₁ + ß2X2 + ß3X3. Test the hypothesis that all three of the predictor variables are equal to 0, given the analysis of variance shown on the right. Use α = 0.05. Click here to view page 1 of a table of critical values of F. Click here to view page 2 of a table of critical values of F. Choose the correct null and alternartive hypotheses below. A. Ho: B₁ B₂ =B3 = 0 H₁: at least one ß; #0 C. Ho: B₁ B₂ = 3 = 0 H₁: B₁0, B₂0, B3 > 0 Find the critical value. The critical value is (Round to two decimal places as needed.) Source Regression Residual Error DF SS 3 9,654 23 2,400 B. Hō: at least one ß; ‡0 H₁: B₁ =B₂ =B3 = 0 D. H₁: B₁ = P₂ = ³3 = 0 H₁: B₁ B₂ B3 0 MS
According to the nutrition research, recommendation on the consumption of fiber for children and teenagers is the following (y is the amount of fiber per day (in grams), x is the age): y 20 22 26 29 31 33 37 40 41 2 4 6 8 10 12 14 16 18 ४ = (a) Test for the significance of regression using the analysis of variance with a useful linear relationship between these two variables? We (b) Estimate ². Round your answer to three decimal places (e.g. 98.765). (c) Estimate the standard error of the slope and intercept in this model. Round your answers to three decimal places (e.g. 98.765). (B₁) se (Bo) se B = = conclude that the model specifies a useful linear relationship at a = 0.05. Mo 0.05. Can you conclude that the model specifies a
You are interested in the effect of school spending (measured in dollars per student) on test scores (in points) for elementary school students. In a large random sample of data, you find for every additional $100 spent per student test scores increase by 10 points, on average holding other factors constant. Furthermore, the covariance between spending and test scores is 250.00 and the variance of test scores is 49.00. What is the R2 from the OLS regression of test scores on spending? I was not given a regression equation or any other data.
Below are bivariate data O each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is ing birthrate and life expectancy information for y = 81.87 – 0.46x. Birthrate, x (number of births per 1000 pop.) Female life expectancy, y (in years) 85- 35.7 67.7 80- 41.5 63.9 75 31.9 63.3 19.9 73.0 70 50.5 60.4 65. 24.4 72.7 60- 50.1 63.2 55 13.8 72.5 50 50.3 54.6 45.6 57.9 15.9 76.2 Figure 1 26.6 71.9 Send data to Excel

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