The probability that one stock index rises on any given day is 45%. The probability that another stock index rises is 52%. It can be assumed that the activities of one index are not affected by the other. What is the probability both stock indexes rise on the same day?

The market and stock A have the following probability distributions:

Q1. Calculate the expected rates of return for the market and stock A.

Q2. Calculate the standard deviation for the market and stock A.

Q3. Calculate the coefficient of variation for the market and stock a.

What is a good example of probability in everyday life? Summarize the situation and how probability is relevant. Please be detailed in the response.

What is the difference between semiclassical probability density and classical probability density?

Note: This is for a quantum physics 2 course.

The market and Stock A have the following probability distributions:

a. Calculate the expected rates of return for the market and Stock A.

b. Calculate the standard deviations for the market and Stock A.

c. Calculate the coefficient of variation for the market and Stock A.

The following require calculating the probability of the specified event based on an assumed probability distribution. Remember to consider whether the event involves discrete or continuous variables.

You are measuring height of vegetation in a grassland using a Robel pole and a 5 m. radius. Based on 100 random samples from the grassland, you obtain a mean height of 0.6 m with a standard deviation of 0.04 m2.

a) What distribution is the appropriate reference for this problem?

b) Ninety percent of the samples are expected to be under what height? Use you will need to use the appropriate command in R of d<dist>, p<dist>, q<dist>, or r<dist> and use the appropriate values as arguments. Use help(command) to find out what these arguments are for your distribution, e.g., help(qbinom) will give you the help for this command.

Consider the following probability distribution for stocks A and B: State probability return on stock A return on stock B 1 0.10 10% 8% 2 0.20 13% 7% 3 0.20 12% 6% 4 0.30 14% 9% 5 0.20 15% 8% 1)

1. Let G be the global minimum variance portfolio. The weights of A and B in G are __________ and __________, respectively.

Poisson

1. Passengers of the areas lines arrive at random and independently to the documentation section at the airport, the average frequency of arrivals is 1.0 passenger per minute.

to. What is the probability of non-arrivals in a one minute interval?

b. What is the probability that three or fewer passengers arrive at an interval of one minute?

C. What is the probability not arrived in a 30 second interval?

d. What is the probability that three or fewer passengers arrive in an interval of 30 seconds?

2. The average number of spots per yard of fabric follows a Poisson distribution. If λ = 0.2 spot per square yard.

to. Determine the probability of finding 3 spots in 2 square yards.

b. What is the probability of finding more than two spots in 4 square yards?

C. What is the average stain in 10 square yards?

Hypergeometric

1. It is known that of 1000 units of ACME cars of a lot of 8000, they are red. If 400 cars were sent to a wholesaler, what is the probability that you will receive a hundred or less red cars. (Assume X = red auto)

a) P (X <= 100) =? (Hypergeometric)

b) P (X> 50) =?

c) E (x) = expected value red cars

I. Continuous Distribution: Normal

1. Long distance telephone calls have a normal distribution with µ x = 8 minutes and σx = 2 minutes. Taking a unit up.

to. What is the probability that a call will last between 4 minutes and 10 minutes?

b. What is the probability that a call will last less than 9 minutes?

C. What is the value of X so that 12% of the experiment values ​​are greater than it?

d. If samples of size 64 are taken:

i. What proportion or probability of the sample means of the calls will be between 7 minutes and 9 minutes?

ii. What proportion or probability of the sample means of the calls is greater than 5 minutes?

iii. Between that two values ​​from the sample mean are 90% of the data.

Exponential

1. The time to fail in hours of a laser beam in a cytometric machina can be modeled by an exponential distribution with λ = .0005

to. What is the probability that a laser will fail more than 10000 hours?

b. What is the probability that a laser will fail less than 20,000 hours?

C. What is the probability that a laser will fail between 10,000 and 20,000 hours?

1. An ardent fan of television game shows has observed that, in general, the more educated the contestant, the less money he or she wins. To test her belief she gathers data about the last eight winners of her favorite game show. She records their winnings in dollars and the number of years of education. The results are as follows.

a) Determine the estimated regression line and standard error of estimate/regression line.

b) Determine the coefficient of determination and discuss what its value tells you about the two variables.

c) Calculate and interpret the Pearson correlation coefficient.

d) Conduct a test of the population coefficient of correlation to determine at the 5% significance level whether a negative linear relationship exists between years of education and TV game shows' winnings.

e) Conduct a test of the population slop to determine at the 5% significance level whether a negative linear relationship exists between years of education and TV game shows' winnings.