The birthday paradox says that the probability (chance) that two people in a room will have the same birthday is more than half as long as n, the number of people in the room, is more than or equal to 23. This property is not really a paradox, but many people find it surprising. Write a Java program that generates 10 sets of 23 valid birthdays (ignore leap years). Check how many times the Birthday Paradox occurs and keep count of it. ONLY using arraylist please in java

list of vehicles and their horsepower. These are:

211    230    182    155   320   310   320   140

177    138    306    310   171   169   150

a) Find the mean and standard deviation of the horsepower data.

b) Draw a normal probability plot (QQ plot) for the horsepower data

c) Draw a histogram of the horsepower data.

d) Using the actual data, find the number of cars with horsepower higher than the first car listed (211 hp). Then divide by 15 to get a percent

e) Using normalcdf, find the percent of cars with more horsepower than the first car listed (211 hp).

f) Compare your results of parts d and e. Are they close?

g) Do the data appear normal? Explain using parts b ,e and f

please answer only e, f, and g questions  !! thanks

here is A to D answers

Answers B

A) If the observations are

X1,X2,X3,X4,X5…………X15

Mean= 219.3

Std=72.9

B) A normal probability plot is created using Minitab

C) The Histogram of the horsepower data is created using Minitab

X represent horsepower

D) Number of cars with horsepower higher than first car listed(2011hp)=6

Percent=6/15*100=40%

Steinberg Corporation and Dietrich Corporation are identical companies except that Dietrich is more levered. Both companies will remain in business for one more year. The companies' economists agree that the probability of the continuation of the current expansion is 70 percent for the next year, and the probability of a recession is 30 percent. If the expansion continues, each company will generate earnings before interest and taxes (EBIT) of $3.4 million. If a recession occurs, each company will generate earnings before interest and taxes (EBIT) of $1.8 million. Steinberg's debt obligation requires the company to pay $970,000 at the end of the year. Dietrich's debt obligation requires the company to pay $1.9 million at the end of the year. Neither company pays taxes. Assume a discount rate of 12 percent.

A particular area in a town suffers a high burglary rate. A sample of 100 streets is taken,
and in each of the sampled streets, a sample of six similar houses is taken. The table below
shows the number of sampled houses, which have had burglaries during the last six months.

(i) (a) State any assumptions needed to justify the use of a binomial model for the number of
houses per street which have been burgled during the last six months.
(b) Derive the maximum likelihood estimator of X bar, the probability that a house of the
type sampled has been burgled during the last six months.
(c) Determine the probabilities for the binomial model using your estimate of X bar, and,
without doing a formal test, comment on the fit.

(ii) An insurance company works on the basis that the probability of a house being burgled
over a six-month period is 0.18. Carry out a test to investigate whether the binomial
model with this value of p provides a good fit for the data.

NOTE:THERE WAS A MISTAKE ON (b) IT IS ESTIMATOR OF X BAR NOT ESTIMATOR OF P but i have corrected it

An article in Information Security Technical Report [“Malicious Software—Past, Present and Future” (2004, Vol. 9, pp. 6–18)] provided the following data on the top 10 malicious software instances for 2002. The clear leader in the number of registered incidences for the year 2002 was the Internet worm “Klez,” and it is still one of the most widespread threats. This virus was first detected on 26 October 2001, and it has held the top spot among malicious software for the longest period in the history of virology.

The 10 most widespread malicious programs for 2002

(Source: Kaspersky Labs).

Suppose that 20 malicious software instances are reported. Assume that the malicious sources can be assumed to be independent. (a) What is the probability that at least one instance is “Klez?” (b) What is the probability that three or more instances are “Klez?” (c) What are the mean and standard deviation of the number of “Klez” instances among the 20 reported?

Overproduction of uric acid in the body can be an indication of cell breakdown. This may be an advance indication of illness such as gout, leukemia, or lymphoma.† Over a period of months, an adult male patient has taken six blood tests for uric acid. The mean concentration was x = 5.35 mg/dl. The distribution of uric acid in healthy adult males can be assumed to be normal, with σ = 1.93 mg/dl.

(a) Find a 95% confidence interval for the population mean concentration of uric acid in this patient's blood. What is the margin of error? (Round your answers to two decimal places.

(d) Find the sample size necessary for a 95% confidence level with maximal margin of error E = 1.02 for the mean concentration of uric acid in this patient's blood. (Round your answer up to the nearest whole number blood tests.

Let x be a random variable that represents the weights in kilograms (kg) of healthy adult female deer (does) in December in a national park. Then x has a distribution that is approximately normal with mean μ = 52.0 kg and standard deviation σ = 8.5 kg. Suppose a doe that weighs less than 43 kg is considered undernourished.

(a) What is the probability that a single doe captured (weighed and released) at random in December is undernourished? (Round your answer to four decimal places.)


(b) If the park has about 2450 does, what number do you expect to be undernourished in December? (Round your answer to the nearest whole number.)
does

(c) To estimate the health of the December doe population, park rangers use the rule that the average weight of n = 45 does should be more than 49 kg. If the average weight is less than 49 kg, it is thought that the entire population of does might be undernourished. What is the probability that the average weight x for a random sample of 45 does is less than 49 kg (assuming a healthy population)? (Round your answer to four decimal places.)


(d) Compute the probability that x< 53.4 kg for 45 does (assume a healthy population). (Round your answer to four decimal places.)

1. Suppose you own a fish restaurant and you believe that the demand for sea bass is distributed normally (that is, follows the bell-shaped curve) with a mean of 12 pounds and a standard deviation of 3.2. In summary, we express this as N(12,3.2).

   1a. The notation N(12,3.2) means that

   		The mean (average) is 3.2 and the standard deviation is 12
   		The mean is 12 and the standard deviation is 3.2 and the data follows a bell shape curve
   		The mean is 12 and the standard deviation is 3.2 and the data does not follow a bell shape curve

10 points

Question 2

1. What is the z-score for 20 pounds of sea bass? You find the z-score by calculating (x-mean)/standard deviation

   		0.0062
   		2.50
   		0.9938
   		0.25

10 points

Question 3

1. The number inside Table A associated with 2.50 is

   		2.50
   		0.0062
   		0.9938
   		0.25

10 points

Question 4

1. The number in the table represents that area to the

   		Right
   		Left

10 points

Question 5

1. So 0.9938 is the area associated with a Z score of

   		2.50 or more
   		2.50 or less

10 points

Question 6

1. The probability that you will need 20 pounds or more of sea bass is

   		0.25
   		0.0062
   		0.9938
   		2.50

10 points

Question 7

1. What is the z-score for 15 pounds of sea bass

   		0.94
   		0.8264
   		0.06
   		-0.94

10 points

Question 8

1. What is the number inside table A associated with 0.94

   		0.8264
   		0.1736
   		0.94

10 points

Question 9

1. So 0.8264 is the area associated with a Z score of

   		0.94 or less
   		0.94 or more

10 points

Question 10

1. The probability that you will need 15 pounds of sea bass or less is

   		0.1736
   		0.94
   		0.8264

10 points

Question 11

1. What is the probability that you will need between 15 and 20 pounds of sea bass

   		0.94
   		0.8264
   		0.1674

10 points

Question 12

1. What is the z-score associated with the 95th percentile of the standard normal curve

   		0.95
   		1.65
   		1.28

10 points

Question 13

1. How many pounds of sea bass are needed for the 95th percentile of sea bass demand

   		1.65
   		7.28
   		17.28

Upload Cars04-1 data and use cylinder numbers to predict the car’s horse power. Answer the questions.

I) For an additional 2.0 cylinders how much the car’s horse power will change? (10 points) a. It will increase by 150 units. b. It will increase by 36.5 units. c. It will increase by 73.2 units. d. It will decrease by 2.01 units. e. Not applicable.

II) After performing the regression analysis you are asked to pick one number that would best answer the question: Are these two variables, number of cylinders and horse power, related or not? What is this number and why? (10 points) a. The number is the slope and it clearly indicates the relation: For each additional cylinder the horse power increases. b. This number is R-square and since it is not close to 1 we cannot claim that these two variables are related. c. The number is the P-value, which in this case is very low indicating a strong probability that the two variables are related. d. None of these.

III) Given a car that has engine size of 4.0 cylinders use regression analysis and all available information in there, in order to predict this car’s horse power. What is your interval prediction? (10 points) a. [109.5, 179.1] b. 170.6 ± 34.7 c. 144.3 d. [178.6, 185.4] e. Not applicable

Let the following be the supply and demand for coconuts.

P            2            3            4            5            6            7            8            9            10            11            12

Q_s         100       200      300        400       500       600    700       800      900     1000    1100

Q_D        550       500      450        400       350       300    250       200      150     100    50

Now imagine that there is a price ceiling on coconuts at $3 but in order to prevent wasting peoples' time by making them wait in line, the government hands out ration coupons to people. In order to buy a coconut you need a coupon. Assume that the number of coupons is the appropriate number to clear the market with the price ceiling (you should know what that is). Now notice that the government probably doesn't know who has the highest marginal value for coconuts so, while this will eliminate the waste from the line it will most likely not allocate the coconuts efficiently. However, we can solve this problem by allowing people to trade the coupons! So imagine that there is such a market and it is perfectly competitive.

a. What will the price of a coupon be in this market?

b. Draw the price ceiling graph and identify the consumer and producer surplus, and the dead weight loss. There should be an area in there which would have been the cost of the line had there been a line. Label this area "A." Who gets this surplus now?