Refer to the sample data for pre-employment drug screening shown below. If one of the subjects is randomly selected, what is the probability that the test result is a false positive? Who would suffer from a false positive result? Why? Pre-Employment Drug Screening Results Positive test result Negative test result Drug Use Is Indicated Drug Use Is Not Indicated 42 12 Subject Uses Drugs Subject Is Not a Drug User 20 28 The probability of a false positive test result is (Round to three decimal places as needed.)

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**Pre-Employment Drug Screening Analysis**

This section covers the interpretation of pre-employment drug screening data. 

**Scenario:**
A drug screening test is administered, and the results are categorized as follows:

|                           | Positive Test Result | Negative Test Result |
|---------------------------|----------------------|----------------------|
| **Subject Uses Drugs**    | 42                   | 12                   |
| **Subject Is Not a Drug User** | 20               | 28                   |

**Key Points:**

1. **Understanding False Positives:**
   - A false positive occurs when a test indicates drug use for a person who does not use drugs.
   - In this context, the number of false positives is represented by subjects who do not use drugs but have a positive test result, which is 20.

2. **Probability Calculation:**
   - To find the probability of a false positive, consider the total number of tests administered and the number of false positives.
   - The total number of tests = 42 (True Positive) + 12 (False Negative) + 20 (False Positive) + 28 (True Negative) = 102.
   - Probability of a false positive = Number of false positives / Total number of tests = 20 / 102.

3. **Conclusion:**
   - Calculate the probability and round it to three decimal places as needed.

Understanding how to interpret these results is crucial for accurate decision-making regarding employment and the implications of drug use testing.
Transcribed Image Text:**Pre-Employment Drug Screening Analysis** This section covers the interpretation of pre-employment drug screening data. **Scenario:** A drug screening test is administered, and the results are categorized as follows: | | Positive Test Result | Negative Test Result | |---------------------------|----------------------|----------------------| | **Subject Uses Drugs** | 42 | 12 | | **Subject Is Not a Drug User** | 20 | 28 | **Key Points:** 1. **Understanding False Positives:** - A false positive occurs when a test indicates drug use for a person who does not use drugs. - In this context, the number of false positives is represented by subjects who do not use drugs but have a positive test result, which is 20. 2. **Probability Calculation:** - To find the probability of a false positive, consider the total number of tests administered and the number of false positives. - The total number of tests = 42 (True Positive) + 12 (False Negative) + 20 (False Positive) + 28 (True Negative) = 102. - Probability of a false positive = Number of false positives / Total number of tests = 20 / 102. 3. **Conclusion:** - Calculate the probability and round it to three decimal places as needed. Understanding how to interpret these results is crucial for accurate decision-making regarding employment and the implications of drug use testing.
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