To assess the statements regarding Beth's son's weight over the years, we can analyze the data as follows:
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Scatter Plot: You can input the data into Desmos to create a scatter plot. The points are:
- (1, 21)
- (2, 28)
- (3, 31)
- (4, 35)
- (5, 40)
- (6, 46)
- (7, 51)
- (8, 57)
- (9, 64)
- (10, 71)
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Line of Best Fit: To determine if the line of best fit (y = 5x + 15) adequately represents the data, you can check the fit visually on the scatter plot or calculate the correlation coefficient. For a line of best fit to be accurate, it should closely follow the trend of the data points.
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Correlation: The correlation between age and weight appears to be positive, meaning that as age increases, weight also increases. A strong positive correlation indicates a linear relationship.
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Analysis of Statements:
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"The data can be represented with a line of best fit y=5x+15.":
- False. The slope seems inconsistent with the actual data. You can check this by observing that the weight does not consistently increase by 5 pounds for each additional year. The increase in weight appears to be larger as age increases.
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"There is no correlation between the recorded age and weight.":
- False. There is a clear positive correlation based on the observed data, as weight increases with age.
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"The data suggests a linear association between the recorded age and weight.":
- True. The scatter plot will show a linear trend, indicating a strong association between age and weight.
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In summary:
- The first statement is False.
- The second statement is False.
- The third statement is True.