In an article in the Journal of Advertising, Weinberger and Spotts compare the use of humor in television ads in the United States and in the United Kingdom. Suppose that independent random samples of television ads are taken in the two countries. A random sample of 400 television ads in the United Kingdom reveals that 141 use humor, while a random sample of 500 television ads in the United States reveals that 119 use humor.

(a) Set up the null and alternative hypotheses needed to determine whether the proportion of ads using humor in the United Kingdom differs from the proportion of ads using humor in the United States.

H₀: p₁ − p₂ (Click to select)≠= 0 versus H_a: p₁ − p₂ (Click to select)=≠ 0.

(b) Test the hypotheses you set up in part a by using critical values and by setting α equal to .10, .05, .01, and .001. How much evidence is there that the proportions of U.K. and U.S. ads using humor are different? (Round the proportion values to 3 decimal places. Round your answer to 2 decimal places.)

(Reject/Do not Reject) H₀ at each value of α; (Click to select)strongextremely strongnonesomevery strong evidence.

(c) Set up the hypotheses needed to attempt to establish that the difference between the proportions of U.K. and U.S. ads using humor is more than .05 (five percentage points). Test these hypotheses by using a p-value and by setting α equal to .10, .05, .01, and .001. How much evidence is there that the difference between the proportions exceeds .05? (Round the proportion values to 3 decimal places. Round your z value to 2 decimal places and p-value to 4 decimal places.)

(Do not reject/Reject)  H₀ at each value of α = .10 and α = .05; (Click to select)somestrongvery strongextremely strongnone evidence.

(d) Calculate a 95 percent confidence interval for the difference between the proportion of U.K. ads using humor and the proportion of U.S. ads using humor. Interpret this interval. Can we be 95 percent confident that the proportion of U.K. ads using humor is greater than the proportion of U.S. ads using humor? (Round the proportion values to 3 decimal places. Round your answers to 4 decimal places.)

95% of Confidence Interval                      [ , ]

(Yes/No) the entire interval is above zero.

A consulting firm submitted a bid for a large research project. The firm's management initially felt they had a 50-50 chance of getting the project. However, the agency to which the bid was submitted subsequently requested additional information on the bid. Past experience indicates that for 78% of the successful bids and 35% of the unsuccessful bids the agency requested additional information.

a. What is the prior probability of the bid being successful (that is, prior to the request for additional information) (to 1 decimal)?

b. What is the conditional probability of a request for additional information given that the bid will ultimately be successful (to 2 decimals)?

c. Compute the posterior probability that the bid will be successful given a request for additional information (to 2 decimals).

Alana consulted a local master beekeeper, Dr. Beekeeper, concerning the death of some of her beehives. He suggested adding a specific type of plant food, “Bee Empower” to the clover fields where the bees forage for nectar. The amount of Bee Empower (in kg) that should be added per acre of clover field is represented by:

f(x)= -9x² + 126x -45

x=kg of Bee Empower/acre

A. Find the critical value of Bee Empower for this function

B. In words, describe what this value means

C. Is this value the minimum or maximum amount of plant food needed per acre? Mathematically prove your answer.

This is for Geography Stats.

I have already found the weighted mean center of population. Which is (3.34,3.48)

and the unweighted mean center (2.94,2.48).

I need to find the Bachi's Weighted Standard Distance. I am completely lost with this part of the question. Any help would be much appreciated! Test tomorrow =(

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