Consider the regression ln yi = β0 + β1xi + i . (a) how would you derive the formulas to estimate β0 and β1? [note: no need to derive the formulas] (b) suppose you estimated βˆ 0 = 0, βˆ 1 = 1. suppose the standar error of βˆ 0 is 1 and the standard error of βˆ 1 is 2. how would you go about computing the standard error of the prediction of y at x = 1?

a 4/6 = 9/12   not proportional

step-by-step explanation:

to find which are not proportional, we can use cross products

if it is true, they are proportional.   if it is not true, they are not proportional.

a 4/6 = 9/12

4* 12 = 6*9

48 = 54

not this is not proportional  

b 2/3 = 12/18  

2* 18 = 3 * 12

36 = 36

this is proportional

c 5/4 = 10/8  

5*8 = 4*10

40 = 40

this is proportional

d 7/5 = 35/25

7*25 = 5 * 35

175 = 175

is proportional

14.3

step-by-step explanation:

add all the numbers together.

9 + 12 + 15 + 16 + 17 + 17 = 86

now, divide 86 by how many numbers we have: 6.

86 / 6 = 14.3

1. supplementary angles

2. acd and bcd

step-by-step explanation: