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 = 
= =
Im not sure but you cam try adding 15+9 which is 24
Answer: C. 30.47
Step-by-step explanation:
The mean of discrete random variable i.e. the expected value of X is given by :-
Now by using the given table, the expected value of X is given by :-
Hence, the mean of discrete random variable= 30.47
Answer:
a. There's a 95% chance that the true proportion is in the confidence interval.
Step-by-step explanation:
When we want to estimate a property of a population (a population's parameter), without surveying the population, we use samples.
Then, with the information of the samples we can calculate the statistics and infere properties about a population. This inferences obviously came with some uncertainty, depending on the properties of the sample and specially the sample size.
When we talk about confidence intervals, we use the statistic of the sample (in this case, the mean) to estimate a range of values it is expected to find the true mean of the population. The width of this interval depends on the sample standard deviation and the sample size.
The value of the confidence interval (95%, 99%, etc) represent the probabilty that the true mean is within this interval.
Stretched by 3, right 2, up 1
