Suppose that a test for a certain disease has a specificity of 95%. If 2,000 people...

Suppose that a test for a certain disease has a specificity of 95%. If 2,000 people without the disease take the test, how many should you expect to test negative?

100 1,000 1,500 1,900

Expert Solution

Since our test for a certain disease has 95% specificity.

Specificity is similar to Confidence Coefficient. It means a true negative rate.

Specificity talks about the proportion of people who don't have the disease and are tested negative.

So, here we have to tell, if 2000 people without the disease take the test , how many people should we expect to test negative.

ANSWER :- No. Of people that are expected to test negative = (Total People) × (Specificity)

= 2000×0.95 = 1900.

Hence, D) 1900 people are expected to test negative.

This answers your question.

If you understood the answer please rate Positively.

orchestra answered 2 years ago

Suppose a test for a disease has a sensitivity of 80% and a specificity of 95%....

Suppose a test for a disease has a sensitivity of 80% and a specificity of 95%. Further suppose that in a certain country with a population of 1,000,000, 21% of the population has the disease. Fill in the accompanying table. -------------------Has disease |Does not have disease| Totals Test positive Test negative Totals

Suppose that a medical test for a certain disease has a sensitivity and specificity of 93%....

Suppose that a medical test for a certain disease has a sensitivity and specificity of 93%. The test is applied to a population of which 11% are actually infected by the disease. 1. Calculate the NPV and the PPV. 2. What percent of the total population will test positive who are disease-free? 3. What percent of the total population will test negative who have the disease?

A test for a certain disease is found to be 95% accurate, meaning that it will...

A test for a certain disease is found to be 95% accurate, meaning that it will correctly diagnose the disease in 95 out of 100 people who have the ailment. The test is also 95% accurate for a negative result, meaning that it will correctly exclude the disease in 95 out of 100 people who do not have the ailment. For a certain segment of the population, the incidence of the disease is 4%. (1) If a person tests positive,...

BAYES' FORMULA A test for a certain disease gives a positive result 95% of the time...

BAYES' FORMULA A test for a certain disease gives a positive result 95% of the time if the person actually carries the disease. However, the test also gives a positive result 3% of the time when the individual is not carrying the disease. It is known that 10% of the population carries the disease. If a person tests positive, what is the probability that he or she has the disease?

A medical test has been designed to detect the presence of a certain disease. Among people...

A medical test has been designed to detect the presence of a certain disease. Among people who have the disease, the probability that the disease will be detected by the test is 0.93. However, the probability that the test will erroneously indicate the presence of the disease in those who do not actually have it is 0.03. It is estimated that 3% of the population who take this test have the disease. (Round your answers to three decimal places.) (a)...

How to calculate 95% CI with sensitivity and specificity That is sensitivity, specificity, prevalence has been...

How to calculate 95% CI with sensitivity and specificity That is sensitivity, specificity, prevalence has been given and 95%CI needs to be calculated, but how???

Suppose that, in an urban population, 50% of people have no exposure to a certain disease,...

Suppose that, in an urban population, 50% of people have no exposure to a certain disease, 40% are asymptomatic carriers, and 10% have the disease with symptoms. In a sample of 20 people, we are interested in the probability that the sample contains a number of asymptomatic carriers that is exactly thrice the number that have the disease with symptoms. While the final numerical answer is important, the setup of the solution is moreso.

The disease D has two symptoms, pain and fever. Pain occurs in 95% of the people...

The disease D has two symptoms, pain and fever. Pain occurs in 95% of the people with D, but also in 10% of the people without D. Fever occurs in 90% of the people with D, but also in 5 % of the people without D. D affects 1% of people. Which of pain or fever is a better indicator of D?

A hospital administers a test to see if a patient has a certain disease. 2 %...

A hospital administers a test to see if a patient has a certain disease. 2 % of the overall population has the disease. The test is 90% accurate. (a)If a patient tests positive, what is the probability that they actually have the disease? (b) If we instead perform two successive tests on each person, what is the probability that a person who tests positive both times actually has the disease? (Hint: drawing a probability tree might help)

Suppose a novel respiratory disease has a 2% mortality rate. If 1,000 people catch the disease,...

Suppose a novel respiratory disease has a 2% mortality rate. If 1,000 people catch the disease, how many would you expect to die from it? Give the distribution of the r.v. you’re using to model this situation, including parameter values. How many people would have to catch the disease for the number of expected deaths to rise to 100,000? To rise to 1,000,000?

Question