To determine which value (1 or 48) is a better prediction for $y$ when $x = 73$ based on the scatter plot, we can follow these steps:

1. Examine the scatter plot: Observe the pattern or trend of the data points as $x$ increases.
2. Estimate the value of $y$ at $x = 73$: Identify the $y$-value that corresponds to $x = 73$ by looking at the points near $x = 73$.

Analysis:

• The scatter plot shows data points that are somewhat scattered, but generally, $y$ values are centered around 50 to 70.
• When $x = 73$, most data points around that $x$-value are clustered near a $y$-value of approximately 50.

Conclusion:

Given the distribution of the points around $x = 73$, a $y$ value of 48 is much closer to the general trend of the data. Therefore, 48 is a better prediction for $y$ when $x = 73$.

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Would you like more details or have any further questions? Here are some related questions:

1. How can we calculate the line of best fit for the given scatter plot?
2. What methods are available to determine if a scatter plot shows a strong correlation?
3. How do we calculate the correlation coefficient for the data points in the scatter plot?
4. What is the importance of outliers in scatter plots, and how do they affect predictions?
5. How can we use a scatter plot to make predictions for other $x$ values not explicitly shown?

Tip: When analyzing scatter plots, always look for trends or patterns in the data to make informed predictions.