To analyze the data represented in the scatterplot where the x-axis represents a student's age in years and the y-axis represents the average number of times the student cried each month, we can assess the vocabulary words provided:
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Univariate - This term describes a single variable. Since the data involves two variables (age and crying frequency), this does not apply.
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Bivariate - This term describes data involving two variables. In this case, it is applicable because we are looking at age and crying frequency together.
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Decreasing - If the trend in the scatterplot shows that as age increases, the number of times a student cries decreases, this term would apply. Without seeing the plot, we cannot definitively state if this applies.
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Increasing - If the trend shows that as age increases, the number of times a student cries increases, this term would apply. Again, this is dependent on the actual scatterplot.
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Proportional - This term typically refers to a consistent ratio between two variables. The scatterplot may or may not exhibit a proportional relationship depending on its pattern. Without the graph, we can't definitively conclude this.
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Linear trend - If the points form a straight line trend (either increasing or decreasing), this term would apply.
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Positive trend - This would apply if the points show an upward trend (more crying as age increases).
Based on this analysis, the applicable vocabulary words are:
- Bivariate
- Decreasing (if the trend shows this)
- Increasing (if the trend shows this)
- Linear trend (if the trend follows a straight line)
- Positive trend (if the trend is upward)
If we know the direction of the trend from the scatterplot, we can accurately choose between "Decreasing," "Increasing," or "Positive trend." As it stands, we can definitively state "Bivariate" applies.