Case 1:It is the beginning of the COVID-19 pandemic, and the U.S. government wants to determine whether immigrants should be tested for COVID-19 disease. This decision can be made based on financial considerations. Assume that each immigrant who is allowed to enter the United States and has the disease costs the country $100,000. Also, assume that each immigrant who is allowed to enter the United States and does not have the disease will contribute $10,000 to the national economy. Finally, assume that 5 percent of all potential immigrants have the disease. The U.S. government can choose to admit all immigrants, admit no immigrants, or test immigrants for the illness before determining whether they should be admitted. It costsT dollars to test a person for the disease, and the test result is either positive or negative. A person who does not have the disease always tests negative. However, 10% of all people who do have the disease test negative. The government aims to maximize the expected net financial benefits per potential immigrant. Design a decision tree for this model and answer the following questions here:

1. What is the largest value ofT at which the U.S. government will choose to test potential immigrants for the disease?
2. How many decision nodes does your decision tree have?
3. How many probability nodes does your decision tree have?
4. How much is the Expected Value of Information (EVI)?