How does a bivariate regression model differ from a multiple regression model?

Multiple Choice

A bivariate regression has only one dependent and independent variable but a multiple regression has more than one dependent variable and may have many independent variables.

A bivariate regression has more than one dependent variable and only one independent variable where a multiple regression has one dependent variable and may have many independent variables.

A bivariate regression has only one dependent and many independent variables but a multiple regression has one dependent variable, but may have many independent variables.

A bivariate regression has only one dependent and independent variable but a multiple regression has one dependent variable and may have many independent variables.

According to the partial regression analysis output below, what is the t-statistic to test whether the regression slope is significant? Regression Analysis: Tourism ($bill) versus Visitors (mill) The regression equation is: Tourism ($bill) = 21.5 + 0.295 Visitors (mill) Predictor Coef SE Coef Constant 21 . 464 3. 462 Visitors (mill) 0. 29497 0.07917 S = 2 . 58307 6.20 '13.88 0.07917 2.58307 3.73public class RightTriangle ( public int hypotenuse () [ private int base: return this -hypotenuse; private int height; private int hypotenuse; public void metBase (int newBans) public RightTriangle thin baco - nowBang [int bane; int height) get Hypotenuse ( ) this baoo - babe; this, height . height, getHypotempo () : public void setlleight (int newileig this. height . nowHeight ; set Hypotenuse ( ) public int base () { return chin , baser private void notHypotenuse () this. hypotenuse = (int) Math rou public int height ( Math. Dact (bage *base + height whoi return this . haight, and RightTriangle.1. Consider the Markov chain with three states S-[1,2,3), that has the following transition probability matric P= 0 NI-WIHNI O Draw the state transition diagram for this chain. Write the transition probability matrix for three steps. 2. Write Markov transition matrix for following state transition diagram: Classify of states of the Markov chain. 3. Find eigenvalues and eigenvectors of the transition probability matrix for following system 0.4 0.6 0.8 rain no rain 0 7