A group of students at a high school took a standardized test. The number of students who passed or failed the exam is broken down by those who did or did not eat breakfast in the following table. Determine whether eating breakfast and passing the test are independent or dependent. Passed Failed Did Eat Breakfast 122 10 Did NOT Eat Breakfast 58 15

1 answer

To determine whether eating breakfast and passing the test are independent or dependent events, we can look at the probabilities of passing the test given whether or not a student ate breakfast.

First, we need to calculate the total number of students in each category.

  • Total number of students who ate breakfast:

    • Passed: 122
    • Failed: 10
    • Total who ate breakfast = 122 + 10 = 132
  • Total number of students who did not eat breakfast:

    • Passed: 58
    • Failed: 15
    • Total who did not eat breakfast = 58 + 15 = 73

Now we can calculate the overall totals:

  • Total students:
    • Total = 132 + 73 = 205

Next, let's calculate the probability of passing the test for both groups (those who ate breakfast and those who did not):

  1. Probability of passing given that a student ate breakfast (P(Pass | Eat Breakfast)): \[ P(Pass | Eat Breakfast) = \frac{\text{Number who passed and ate breakfast}}{\text{Total who ate breakfast}} = \frac{122}{132} \]

  2. Probability of passing given that a student did not eat breakfast (P(Pass | Did Not Eat Breakfast)): \[ P(Pass | Did Not Eat Breakfast) = \frac{\text{Number who passed and did not eat breakfast}}{\text{Total who did not eat breakfast}} = \frac{58}{73} \]

  3. Total probability of passing (P(Pass)): \[ P(Pass) = \frac{\text{Total students who passed}}{\text{Total students}} = \frac{122 + 58}{205} = \frac{180}{205} \]

To check for independence, we need to see if: \[ P(Pass | Eat Breakfast) = P(Pass) \quad \text{and} \quad P(Pass | Did Not Eat Breakfast) = P(Pass) \]

Calculating the probabilities for passing when eating breakfast and not eating breakfast:

  • \( P(Pass | Eat Breakfast) = \frac{122}{132} \approx 0.9242 \)
  • \( P(Pass | Did Not Eat Breakfast) = \frac{58}{73} \approx 0.7959 \)
  • \( P(Pass) = \frac{180}{205} \approx 0.8780 \)

Since:

  • \( P(Pass | Eat Breakfast) \approx 0.9242 \) is not equal to \( P(Pass) \approx 0.8780 \)
  • \( P(Pass | Did Not Eat Breakfast) \approx 0.7959 \) is also not equal to \( P(Pass) \approx 0.8780 \)

Conclusion

Because the probabilities differ depending on whether or not the students ate breakfast, we conclude that eating breakfast and passing the test are dependent events.