To determine which statements are true, let's analyze them based on the general context of correlation between happiness and income:
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The slope of the line of best fit could be around m = -1/2000.
- True: A very small negative slope suggests a weak negative correlation.
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The line of best fit should include the lowest and highest scores.
- False: The line of best fit does not need to pass through all data points, including extremes.
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There is no correlation between happiness and income.
- False: Generally, there is at least some correlation; it may be weak or moderate.
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The y-intercept of the line of best fit would show a happiness score of around 40 when there is $0 income.
- True/False: This could be true if given data supports it, but it is context-dependent.
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The line of best fit would have a positive slope representing as income goes up, happiness goes up.
- False: This suggests a positive correlation, which may not hold true universally.
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The line of best fit must show the middle score of the data as being on the line.
- False: The line of best fit does not need to pass through the median.
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As a person's income goes up, their happiness trends down.
- False: This suggests a negative correlation, which isn't generally supported.
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This is a moderate positive correlation.
- False/True: This may or may not be true depending on the specific data being analyzed.
Summary of True Statements
- The slope of the line of best fit could be around m = -1/2000.
- The y-intercept could show a happiness score around 40 at $0 income (depends on the data).
Therefore, only the first and possibly the fourth statements can be marked true based on the context provided.
1 answer