To analyze the statements based on Beth's recorded data, you'll need to plot the data points on a scatter plot and then assess the trends and associations. Here’s how to proceed:
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Input the Data:
- First, gather the data from your provided table. You will generally have one column for age (x-axis) and another for weight (y-axis).
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Create a Scatter Plot:
- Use the graphing calculator DESMOS to plot the data points. You can simply enter the data in two lists, and DESMOS will allow you to create a scatter plot.
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Evaluate the Statements:
- Check for a linear association by observing how the points are distributed. If they closely align along a straight line, this suggests a linear relationship.
- To verify the claim about a line of best fit (y = 5x + 15), you can use DESMOS to find the line that fits the data best. You might use the regression feature to get a more accurate equation.
- Look at the overall pattern: if the points show a clear trend (increasing or decreasing), then there is a correlation; if they are scattered randomly with no discernible pattern, then there is no correlation.
Evaluating Each Statement:
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The data suggests a linear association between the recorded age and weight.
- True or False: If the scatter plot shows the points close to a straight line, this statement is True.
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The data can be represented with a line of best fit y = 5x + 15.
- True or False: Check the slope and intercept of the line obtained from regression analysis. If it matches y = 5x + 15, this statement is True; otherwise, it is False.
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There is no correlation between the recorded age and weight.
- True or False: If there is a clear pattern in the scatter plot, then this statement is False.
Conclusion:
After you create the scatter plot and analyze the correlation visually and mathematically, you can confidently determine the truth values of each statement based on your observations.
If you provide actual data points, I can help guide you through evaluating the results in detail!
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