The squared differences for each expression in the image have been calculated as follows:

1. For $(10 - 19.7143)^2$, the result is 94.3676
2. For $(19 - 19.7143)^2$, the result is 0.5102
3. For $(11 - 19.7143)^2$, the result is 75.9390
4. For $(19 - 19.7143)^2$, the result is 0.5102 (same as the previous 19)
5. For $(26 - 19.7143)^2$, the result is 39.5100
6. For $(28 - 19.7143)^2$, the result is 68.6528
7. For $(25 - 19.7143)^2$, the result is 27.9386

Would you like further details or explanations on any of these calculations?

Here are 5 related questions to explore:

1. What is the general formula for calculating squared differences?
2. How are squared differences used in statistics or other fields?
3. Can you calculate the sum of these squared differences?
4. What role does rounding precision play in calculations like this?
5. How would the results change if the target value (19.7143) were different?

Tip: Squared differences are often used in variance and standard deviation calculations to measure how much values deviate from a mean.