If p = 0.06 represents the probability that a customer will suffer an accident, and each accident costs the insurance company an average of $ 16,586.05. Then, the expected value of the cost that the insurance company must pay for each driver is:
$ 16,586.05 * 0.06 = 995,163. This plus the general cost of an insurance company per insured driver that is $ 100 gives a total of $ 1095,163. The answer is option B. The insurance company must request a premium of $ 1095.16
Answer: men = 15 , women = 12
Step-by-step explanation:
Ratio of men to women = 5:4
Total ratio = 9
number of people = 27
number of men = ration of men / total ratio x total number of people
That is :
number of men = 5/9 x 27
number of men = 3
Number of women = ratio of women / total ratio x number of people
That is :
number of women = 4/9 x 27
number of women = 12
Answer:
the probability that a randomly selected U.S. adult weighs less than the overweight(but not obese) is 0.394
Step-by-step explanation:
Given the data in the question;
Underweight Healthy Weight Overweight (not Obese) Obese
Probability 0.017 0.377 0.343 0.263
so
P( underweight) = 0.017
P( Healthy Weight) = 0.377
P( Overweight (not Obese) ) = 0.343
P( Obese ) = 0.263
now, the probability that a randomly selected U.S. adult weighs less than the overweight(but not obese) range will be;
P( weigh less than overweight(but not obese) = P( underweight) + P( Healthy Weight)
P( weigh less than overweight(but not obese) = 0.017 + 0.377
P( weigh less than overweight(but not obese) = 0.394
Therefore, the probability that a randomly selected U.S. adult weighs less than the overweight(but not obese) is 0.394
Answer:
3.2
Step-by-step explanation:
Here we are told that a population has a standard deviation of 32 and that we have a sample of size 100 from this population that are asked for the standard error of the sampling distribution. Now it would be important to know what statistic we are taking from these samples. Now we would need to know what what statistic we're taking from these samples. Um I'm assuming that we're talking about sample averages in this case the standard error is well, let's sample averages are just distributed like this. They are so we have anna's big, which means that our sample averages are going to be approximately normally distributed. The mean of the sample averages will be equal to the mean of the population, and the standard air of the sample averages will be equal to the population. Standard deviation divided by the square root of the sample size. So this is our standard error of the sampling distribution, And so this is equal to 3.2. So that is your answer.
- Hope this helps! -
