Answer: (a) 
(b) 
Step-by-step explanation:
(a) P( Bill hitting the target) = 0.7 P( Bill not hitting the target) = 0.3
P( George hitting the target) = 0.4 P(George not hitting the target) = 0.6
Now the chances that exactly one shot hit the target is = 0.7 x 0.6 + 0.4 x 0.3
= 0.54
Chances that George hit the target is = 0.4 x 0.3 = 0.12
So given that exactly one shot hit the target, probability that it was George's shot = 
= .
(b) The numerator in the second part would be the same as of (a) part which is 0.12.
The change in the denominator will be that now we know that the target is hit so now in denominator we include the chance of both hitting the target at same time that is 0.4 x 0.7 and the rest of the equation is same as above i.e.
Given that the target is hit,probability that George hit it = 
= =
It is not reasonable because 53.85 x 5 is 269.25 which isnt close to 350
Answer:
The rate change between these points is 3.
Step-by-step explanation:
Step-by-step explanation:
The regression equation is correctly written as:
log(rent) = β₀+β₁log(pop)+β₂log(avginc)+β₃pctstu+μ
1. this question requires us to State the null hypothesis that size of the student body relative to the population has no ceteris paribus effect on monthly rents.
<u>null hypothesis</u>
H₀ : β₃ = 0 (no effect exists)
<u>alternative that there is an effect.</u>
H₁ : β ≠ 0
2.
Due to increased demand when population is increased, the higher the number of people living in the city then there is a great likelihood that rent would increase. β1 will therefore be positive, all things being equal.
as average income rises, so also would rent as the people would have more money and therefore there would be increased demand for housing. This increase in demand would then cause a surge in the price of rent. β₂ would therefore be positive .
the last question you posted is incomplete so i was unable to go ahead with it.
