A poll conducted between February and April of 2006 surveyed 2822 Internet users and found that 198 of them had downloaded a podcast to listen to it or view it later at least once. A similar poll in May of the same year found that 295 of 1553 Internet users had downloaded a podcast at least once. Test the null hypothesis that the two proportions are equal.

The accompanying data set provides the closing prices for four stocks and the stock exchange over 12 days:

With the help of the Excel Exponential Smoothing tool, I was able to forecast each of the stock prices using simple exponential smoothing with a smoothing constant of 0.3 (ie, damping factor of 0.7).

I was also able to calculate the Mean Absolute Deviation (MAD) of each of the stocks: MAD of Stock A = 1.32 MAD of Stock B = 0.37 MAD of Stock C = 0.41 MAD of Stock D = 0.26 MAD of Stock Exchange = 83.85.

The Mean Square Error (MSE) of the stocks: MSE of Stock A = 2.22, MSE of Stock B = 0.17, MSE of Stock C = 0.21, MSE of Stock D = 0.08, MSE of Stock Exchange = 7963.44.

Help me to understand the concept of Mean Absolute Percentage Error (MAPE). I realize that MAPE is the average of absolute errors divided by actual observation values. I'm wondering if this is just the MAD divided by the total observation values for a particular stock. For example, for Stock A, If my understanding is correct (which I don't think it is), the MAPE of Stock A would be 1.32 / each of the observation values individually. Or, would it be [(127.15 - 127.37) / 127.15]. Or, do I need to add up all the absolute errors for Stock A and all the actual observation values for Stock A and divide the former by the latter and then multiply by 100. As you can see, I'm confused. Please help.

Sally’s Toyota Corolla is an old car but it served her well. She is planning to take a trip to the Grand Canyon from the east coast. Before starting the trip she checks the car to determine if the car is in good mechanical condition. She is knowledgeable about cars but no expert. The null and alternative hypotheses are given below.

H0: the Corolla is in good mechanical condition

Ha: the Corolla is not in good mechanical condition

(a) What would a Type-I error be in this situation?

(b) What would a type-II error be in this situation?

(c) Which error is more consequential in this situation and why?

(d) If Sally took the Corolla out to a certified mechanic for a checkout, what would be the likely impact on the magnitude of the Type-I and Type-II errors and why?

The 4M company has a work center with a single turret lathe. Jobs arrive at this work center according to a Poisson process at a mean rate of 2 jobs per day, The lathe processing time has an exponential distribution with a mean of 0.25 day per job.

a) On average, how many jobs are waiting.in the work center?

b) On average, how long will a job stay in the center?

c).Since each job takes a big space, the waiting jobs are currently waiting in the warehouse. The production manager is proposing to add a storage space near the lathe. If an arriving job will have at least 90% chance waiting near the lathe, how big should be the storage space near the lathe?

Why is it “harder” to find a significant outcome (all other things being equal) when the research hypothesis is being tested at the .01 rather than the .05 level of significance?

How can Chi Square test for independence be used to evaluate test re-test reliability?

The American Bar Association reports that the mean length of time for a hearing in juvenile court is 25 minutes. Assume that this this your population mean. As a lawyer who practices in the juvenile court, you think that the average hearing much shorter than this. You take a sample of 20 other lawyers who do juvenile work and ask them how long their last case in juvenile court was. The mean hearing length for this sample of 20 was 23 minutes., with a standard deviation of 6. Test the null hypotheses that the population mean is 25 minutes against the alternative that is less than 25. Set your alpha at .05.

A copier cost $200 for each repair call, after 3 calls they are free (For example 1 call= $200, 3 or more calls = $600). The following chart shows the probability of how many repair calls you will have in 1 year. Questions 36-37

pls show work

36. What is the expected repair call costs for 1 year?

1. $150.00

2. $200.00

3. $206.00

4. $220.00

5. $300.00

37. What is the probability that one repair call cost will be more than $200 for 1 year?

1. .70

2. .40

3. .30

4. .20

5. .10

38. The daily high temperature of Los Angeles in the month of December is normally distributed with a mean of 58 degrees Fahrenheit and a standard deviation of 2 degrees fahrenheit. What percent of high temperatures are between 60 and 64?

1. 68%

2. 84%

3. 15.85%

4. 16%

5. None of the above

39. If P(A) = 0.38, P(B) = 0.83, and P (A ∩ B) = 0.57; then P(A U B) =

1. 1.21

2. 0.64

3. 0.78

4. 1.78

5. None of the above

Consider the probability that at least 36 out of 298 cell phone calls will be disconnected. Choose the best description of the area under the normal curve that would be used to approximate binomial probability.

The option are

Area to the right of 35.5

Area to the right of 36.5

Area to the left of 35.5

Area to the left of 36.5

Area between 35.5 and 36.5

Must solve in R code

Question 2

The random variable X is a payout table of a casino slot machine. The probability mass function is given:

X   -5   0   2   10   20   40   60   1000
Probability   0.65   0.159   0.10   0.05   0.02   0.01   0.01   0.001
Please simulate the results for playing the slot machine 10,000,000 times. Find the mean of these 10,000,000 simulated payout outcomes .

When one uses an ANOVA, explain the difference between “main effects” and “interaction effects”. Give examples of each.

According to a survey in a​ country, 18​% of adults do not own a credit card. Suppose a simple random sample of 900 adults is obtained. ​(b) What is the probability that in a random sample of 900 ​adults, more than 22​% do not own a credit​ card? The probability is what.? ​(Round to four decimal places as​ needed.) Interpret this probability. If 100 different random samples of 900 adults were​ obtained, one would expect nothing to result in more than 22​% not owning a credit card. ​(Round to the nearest integer as​ needed.).  

(c) What is the probability that in a random sample of 900 ​adults, between 17​% and 22​% do not own a credit​ card?

Interpret this probability. If 100 different random samples of 900 adults were​ obtained, one would expect ? to result in between 17​% and 22​% not owning a credit card.

​(Round to the nearest integer as​ needed.)

Would it be unusual for a random sample of 900 adults to result in 153 or fewer who do not own a credit​ card? Why? Select the correct choice below and fill in the answer box to complete your choice

The result

is notis not

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which is

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B.The result

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nothing​,

which is

lessless

than​ 5%.

C.The result

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unusual because the probability that

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is less than or equal to the sample proportion is

nothing​,

which is

lessless

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D.The result

isis

unusual because the probability that

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nothing​,

which is

greatergreater

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