4) Discuss briefly the General linear Hypothesis (CLH) and one of its applications.

General linear hypothesis: It is usually formed for testing a null hypothesis against an…

Answered: <) Discuss briefly the General linear…

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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1. Suppose I am building a model where I have a linear relationship with more than one continuous dependent variables and one continuous independent variable and one categorical independent variable. Which type of regression model do I have? Polynomial Linear Regression Simple Linear Regression Multiple Linear Regression Multivariate Linear Regression 2. Suppose I want to build a model in which I want to predict whether or not a patient has entered remission (i.e., yes or no) given information from one or more variables. What type of regression model do I need to build? Poisson Regression Model Polynomial Regression Model Beta Regression Model Logistic Regression Model None of the above.
Note:- Please need all (a, b, c) answers to this question.
Consider the model Y = ß0 + B₁X1 + ß₂X2 + B3X³ + B4X4 + €. If it is suggested to you that the two variables Z₁ = X₁ + X3 and Z2 = X₂ + X4 might be adequate to represent the data, what hypothesis, in the form C3 = 0, would you need to test? (Give the form of C.)
Find the best-fitting least-squares linear and quadratic approximations to the data set{(1,2),(3,4),(5,7),(7,9),(9,12)}.
Which of the following represents the underlying linear model for hypothesis testing? Y = b0 + b1 X + ε Y = b0 + b1 X Y = β0 + β1 X + ε Y = β0 + β1 X
Consider the multiple regression model Y a + B1 X1 + ß2 X2 + u . When omitting X2 from the regression, then there will be omitted variable bias for B Only if X1 and X2 are correlated, and ß1 # 0 Only if X1 and X2 are correlated, and B2 + 0 Only if X1 and X2 are correlated, ß1 # 0 and B2 # 0 O Only if ß1 + 0 and ß2 # 0
In a simple linear regression analysis (where y is a dependent and x an independent variable), if the y-intercept is positive, then a) there is a positive correlation between x and y. b) if y is increased, x must also increase. c) if x is increased, y must also increase. d) the estimated regression line intercepts the positive y-axis.
Answer for question A) (A) is there an interaction between the type of course and the length of the course? Answer: Since F =24.2560 > Fcrit, then we_____________ the null hypothesis.
2. Consider the regression model given by: B1B2X2i+B3X3i +B4X4i+ B5X5i + Ui Y (a) Suppose that a researcher believes neither X2 nor X4 are needed to explain Y and wants to formally test this conjecture. Show how to conduct the test in each of the following steps: Describe the null and alternative hypotheses. What regressions do you need to run? What test statistic do you need to calculate? (i) (ii) (iii) 1 (iv) (v) (vi) What is the distribution of the test statistic under the null hypothesis? What is the critical value of the test statistic? What is the decision rule you would follow? (b) Suppose that the researcher tested the relevance of X2 and X4, separately, and found neither coefficients are significant. What is the implication of this result on the test result of (a)?
1. Derive the least squares estimators (LSES) of the parameters in the simple linear regression model. 2. Derive the estimators of 30 and ß1 using maximum likelihood estimation procedures.
How would you test the restrictions using both a t-test and an f-test. Regression A: yi = Bo + B1x1 + B2x2 + B3x3 + u Where B is beta. A.) B1 - B2 = 1 B.) B1 + aB2 = 0 (where a is a constant) С.) В2 - ВЗ %3 1 (I am looking for an answer defining the hypothesis, for example: Ho: B1 = 0 Ha: B2 does not = 0)

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<) Discuss briefly the General linear Hypothesis (CLH) and one of its applications.