I don’t know if that’s what you wanted but I hope I helped ;D (sorry for my bad english)
Answer:
a) 
b) 334,858 bacteria
c) 4.67 hours
d) 2 hours
Step-by-step explanation:
a) Initial number of bacteria is the coefficient, that is, 250. And the growth rate is the coefficient besides “t”: 0.15. It’s rate of growth because of its positive sign; when it’s negative, it’s taken as rate of decay.
Another way to see that is the following:
Initial number of bacteria is N(0), which implies 
. And 
. The process is:
b) After 2 days means 
. So, we just replace and operate:
c) 
d) 
we have
p (a) =2/5 p(b)=1/4 ( a and b=1/25
Remember that
we know that for two independent events A,B.
⇒ P(A∩B)=P(A)*P(B)
we have
P(A)=2/5 and P(B)=1/4
so
P(A∩B)=(2/5)*(1/4)=2/20=1/10
that means
<h2>events are dependent</h2>
Answer:
Step-by-step explanation:
Given are 3 data sets with values as:
(i) 8 9 10 11 12 ... Mean =10
(ii) 7 9 10 11 13 ... Mean =10
(iii) 7 8 10 12 13 ... Mean =10
We see that data set shows mean deviations as
(i) -2 -1 0 1 2
(ii) -3 -1 0 1 3
(iii) -3 -2 0 2 3
Since variance is the square of std deviation, we find that std deviation is larger when variance is larger.
Variance is the sum of squares of (x-mean). Whenever x-mean increases variance increases and also std deviation.
Hence we find that without calculations also (i) has least std dev followed by (ii) and then (iii)
(i) (ii) (iii) is the order.
b) Between (i) and (ii) we find that 3 entries are the same and 2 entries differ thus increasing square by 9-4 twice. But between (ii) and (iii) we find that
increase in square value would be 4-1 twice. Obviously the latter is less.
