Part 1: The regression equation is:

$y = 196 - 0.098x$ (Rounding the y-intercept to the nearest integer and the slope to three decimal places.)

Part 2: The best predicted height of an opponent, given that the president had a height of 185 cm, is:

$178.5 \, \text{cm}$ (Rounded to one decimal place.)

How close is the prediction to the actual height?

The predicted height of 178.5 cm is approximately 1.5 cm greater than the actual height of 177 cm.

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Do you want more details or have any questions?

Here are 5 related questions to explore further:

1. What does the slope of a regression equation represent in this context?
2. How can we interpret the significance level in this regression analysis?
3. What would happen if we included more data points in the regression?
4. How do you calculate the confidence interval for a predicted value in regression?
5. How do residuals influence the accuracy of a regression model?

Tip: The slope in regression shows the average change in the dependent variable (opponent height) for each unit change in the independent variable (president height).