The advantage of using the probit model versus the linear probability model for estimating regressions for binary dependent variables is: A. probit model yields more precise estimates (i. e. lower standard errors of the estimated coefficients) B. regression coefficients in the probit model are easier to interpret C. probit model yields predicted probabilities that lie between 0 and 1 D. all of the above

given that triangle abc is transformed two times to get triangle

a"b"c"

first abc is transformed in to a'b'c' as follows:

the coordinates of a are (1,-1) and transformed into a'(-1,1)

similarly b (4,-2) became b'(-4,2) and

c(7,-2) became c'(-7,2)

i.e. (x,y) becomes (-x,-y)

this is nothing but reflection about a point here origin.

thus first transformation is reflection on the origin.

next is exactly shifting 3 units down

source:

set each factor equal to 0

4x-3 = 0

2x-1 = 0

solve for x.

4x-3=0

4x=3

x= 3/4

solve for x. 

2x-1= 0

2x= 1

x= 1/2

eventually after a few more steps, your answer should be 1/2 is less than or equal to x and 3/4 is greater than or equal to x

h/o/e/s mad

step-by-step explanation:

si si si