Is there a difference between the means of occupancy rates in May and August? Answer your question by calculating an approximate and appropriate symmetric 95% confidence interval using a Z statistic. Explain your findings

Taussig Technologies Corporation (TTC) has been growing at a rate of 12% per year in recent years. This same growth rate is expected to last for another 2 years, then decline to g_n = 7%.

1. If D₀ = $2.00 and r_s = 12%, what is TTC's stock worth today? Do not round intermediate calculations. Round your answer to the nearest cent.
   $  
   
   What is its expected dividend yield at this time, that is, during Year 1? Do not round intermediate calculations. Round your answer to two decimal places.
     %
   
   What is its capital gains yields at this time, that is, during Year 1? Do not round intermediate calculations. Round your answer to two decimal places

1. What will TTC's dividend and capital gains yields be once its period of supernormal growth ends? (Hint: These values will be the same regardless of whether you examine the case of 2 or 5 years of supernormal growth; the calculations are very easy.) Round your answers to two decimal places.
   
   Dividend yield:   %
   
   Capital gains yield:   %

7. A study of youth video-game culture was conducted in schools throughout British Columbia, Canada. Part of the study focused on the differences in academic performance between "heavy" players and "light" players of video games: heavy players defined as spending more than 7 hours per week on the games; light players defined as spending less than 3 hours per week gaming.

• A sample of 240 "heavy" users had an average GPA of 2.7, with a standard deviation of 0.7.
• A sample of 320 "light" users had an average GPA of 3.2, with a standard deviation of 0.6.

a. Build a 90% confidence interval estimate of the difference in average GPA for the two populations of "heavy" and "light" gamers.

b. Test the hypothesis that mean GPA between heavy and light game players are equal at the a = 5% significance level. What do you find?

8. Two proposed advertising campaigns themes for a new product are being evaluated for effectiveness. A random sample of 120 consumers is exposed to theme A, and another sample of 100 consumers is exposed to theme B. The study asks each customer whether they have a positive opinion of the product.

• 78% of the theme A participants said, yes, they have a positive opinion about the product.
• 64% of the theme B participants said, yes, they have a positive opinion about the product.

Is there enough evidence to support the claim that theme A is a more effective campaign than theme B, with an a = 5% level of significance?

9. In a test of running shoes, German sporting goods manufacturer, Derrunningzmitdershoessenhoffer, randomly selected 8 amateur runners to test two of its new shoe designs. The table shows how long the test shoes lasted before they were no longer usable.

Wear Time in Weeks

Runner

1

2

3

4

5

6

7

8

Design 1

15.6

17.6

10.3

9.4

13.4

13.5

14.7

20.6

Design 2

14.7

16.1

8.0

9.0

15.3

10.2

15.2

18.3

Test the null hypothesis that there is no difference in average life for the two shoes, using a = 5%.

For the following, Use the five-step approach to hypothesis testing found on page 8-16. It states. You can use excel to compute the data or you can do it by hand. The youtube videos provided in the links will walk you through the steps to complete the following problems.

1. State the hypothesis and identify the claim.

H0:

H1:

2. Use a Pearson Correlation
3. Compute the test Value It will be a correlation
4. Make a decision to reject or fail to reject the null hypothesis.
5. Summarize the results

Problem #3 You are a researcher who wants to know if there is a relationship between variable Y and variable X. You hypothesize that there will be a strong positive relationship between variable Y GPA and Variable X hours of sleep. After one semester, you select five students at random out of 200 students who have taken a survey and found that they do not get more than 5 hours of sleep per night. You select five more students at random from the same survey that indicates students getting at least seven hours of sleep per night. You want to see if there is a relationship between GPA and hours of sleep. Using a Pearson Product Correlation Coefficient statistic, determine the strength and direction of the relationship and determine if you can reject or fail to reject the HO:

Variable Y        Variable X    

2.5                      5               

3.4                      8                

2.0                      4               

2.3                     4.5              

1.6                     3     

3.2                     6

2.8                     7

3.5                     7.5

4.0                     6.5

3.8                     7

solve it with exact data given not an example or other illustration.

implement a Message Authentication Code program in either C/C++ or Python.

See the following steps.

1. Accept a message as keyboard input to your program.

2. Accept a secret key for the sender/recipient as keyboard input to your program.

3. Your hash function H() is simply the checksum. To compute the checksum, you add all the characters of the string in ASCII codes. For example, the checksum of a string "TAMUC" would be 84 + 65 + 77 + 85 + 67 = 378.

Concatenate the secret key of the sender/recipient (from step 2) and the message (from step 1) and compute the checksum of the concatenated string. For ASCII codes, refer to the following website:

http://www.asciitable.com

4. Accept a secret key for the attacker as keyboard input to your program.

5. The attacker modifies the message from step 1. The original message can be modified any way you want.

6. Concatenate the secret key of the attacker (from step 4) and the modified message (from step 5) and compute the checksum of the concatenated string.

7. Concatenate the secret key of the sender/recipient (from step 2) and the modified message (from step 5) and compute the checksum of the concatenated string.

8. Compare the checksum from step 7 and the checksum from step 6. See if they match or not.

9. Compare the checksum from step 3 and the checksum from step 6. See if they match or not.

NOTE: your program should have separate functions for the checksum and the message modification by the attacker.

Implement a Message Authentication Code program in either C/C++ or Python.

1. Accept a message as keyboard input to your program.

2. Accept a secret key for the sender/recipient as keyboard input to your program.

3. Your hash function H() is simply the checksum. To compute the checksum, you add all the characters of the string in ASCII codes. For example, the checksum of a string "TAMUC" would be 84 + 65 + 77 + 85 + 67 = 378.

Concatenate the secret key of the sender/recipient (from step 2) and the message (from step 1) and compute the checksum of the concatenated string. For ASCII codes, refer to the following website:

http://www.asciitable.com

4. Accept a secret key for the attacker as keyboard input to your program.

5. The attacker modifies the message from step 1. The original message can be modified any way you want.

6. Concatenate the secret key of the attacker (from step 4) and the modified message (from step 5) and compute the checksum of the concatenated string.

7. Concatenate the secret key of the sender/recipient (from step 2) and the modified message (from step 5) and compute the checksum of the concatenated string.

8. Compare the checksum from step 7 and the checksum from step 6. See if they match or not.

9. Compare the checksum from step 3 and the checksum from step 6. See if they match or not.

NOTE: your program should have separate functions for the checksum and the message modification by the attacker.

A.

An investor can design a risky portfolio based on two stocks, A and B. Stock A has an expected return of 17% and a standard deviation of return of 18.0%. Stock B has an expected return of 13% and a standard deviation of return of 5%. The correlation coefficient between the returns of A and B is 0.50. The risk-free rate of return is 8%. The proportion of the optimal risky portfolio that should be invested in stock A is _________.

B.

If there are two companies making the same model of cellphones. Assuming the demand for the cellphones produced by Company 1 is D1, and the demand for the cellphones produced by Comp nay 2 is D2, are described by the following two functions:
D1=200-P1-(P1-P)
D2=170-P2-(P2-P)
where P is the average price over the prices of the two companies, i.e., P=[P1+P2]/2. Each company has the cost of C1=C2=10 for producing one cellphone. Suppose each company can only choose one of the three prices {40, 70, 90} for sale.

(1] Compute the profits of each company under all sale price combinations and make the payoff matrix for the two companies. [Hint: the total profits = the demand for the cellphones * the profit of one cellphone after sale. You can type the pay off table for each company as a matrix in the ansering box such that the first row and first column present strategies.]

(2] Find the Nash equilibrium of this game. What are the profits at this equilibrium? Explain your reason clearly.

(3) If the cost for Company 2 changed as C2=20, would the Nash equilibrium change? Why?

Calculate F Test for given 10, 20, 30, 40, 50 and 5,10,15, 20, 25.
For 10, 20, 30, 40, 50:

Minimizing missing data: Here are some types of missing data that you might encounter when implementing a clinical trial. Pick two, and briefly describe a study procedure you could use to minimize the chance of that type of missing data occurring.

1. A participant does not show up for a study visit.

2. A participant does not bring important information (for example, a list of current medications or a pain diary that was supposed to be filled out).

3. Inadequate physical exam done by study staff (for example, pulse not taken).

4. Lab mishap (for example, serum sample lost by lab or in transit to lab).

5. Careless form completion by study staff (for example, a few questions not answered).

6. Careless data entry (for example, the data collection form recorded a diastolic blood pressure of 84, but the study database shows no value was recorded).

7. Participant has an in-office survey to fill out but doesn't complete all questions.