To find the expected value for the number of subjects who are not vaccinated and are diseased, we can use the formula for expected values in a contingency table:

$E = \frac{(\text{Row Total} \times \text{Column Total})}{\text{Grand Total}}$

In this case:

• Row Total for "Not Vaccinated" = 173
• Column Total for "Diseased" = 125
• Grand Total = 277

Plugging these values into the formula:

$E = \frac{173 \times 125}{277}$

Let's calculate this.

$E = \frac{173 \times 125}{277} \approx 78.0$

So, the expected value for the number of subjects who are not vaccinated and are diseased is 78.0.

Would you like more detailed explanations or have any questions?

Here are some related questions that might interest you:

1. How are expected values calculated for different cells in a contingency table?
2. What are the steps to conduct a chi-square test to assess association between variables?
3. Why is it necessary to calculate expected values when evaluating statistical independence?
4. What are the conditions required for a chi-square test of independence?
5. How would you interpret the results if the observed and expected values significantly differ?

Tip: The chi-square test of independence is often used in these cases to determine if there is a significant association between two categorical variables.