Understanding Karim's Cholesterol Test Method

Understanding Karim's Cholesterol Test Method

Assessment

Interactive Video

Mathematics, Science

9th - 12th Grade

Hard

Created by

Aiden Montgomery

FREE Resource

Karim developed a non-invasive method to measure cholesterol levels, aiming for 99% accuracy. Initial tests showed 95% accuracy compared to blood tests. To validate his method, Karim conducted 100 computer simulations assuming 99% accuracy. The simulations showed a low probability of achieving only 95% accuracy, suggesting his method might not meet the 99% standard. The analysis led to questioning the hypothesis that the test is 99% accurate.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main advantage of Karim's new method for measuring cholesterol levels?

It is faster than traditional methods.

It does not require drawing blood.

It is less expensive.

It is more accurate than blood tests.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What percentage of accuracy is required by regulations for cholesterol tests?

99%

95%

100%

90%

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the accuracy of Karim's method when tested on a sample of 100 people?

100%

99%

95%

90%

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why did Karim perform computer-generated simulations?

To reduce the cost of testing.

To compare his method with other non-invasive methods.

To test the hypothesis that his method is 99% accurate.

To improve the accuracy of his method.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How many simulations did Karim perform to test his hypothesis?

10

50

100

200

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What was the purpose of using a computer to simulate the test results?

To ensure the test is faster.

To assume the test is 99% accurate.

To reduce human error.

To increase the sample size.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a low probability of observing Karim's results suggest about his hypothesis?

The hypothesis is likely incorrect.

The hypothesis is likely correct.

The test needs more samples.

The test is too expensive.

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