Abe creates a scatter plot showing students’ ages on the x-axis and their heights on the y axis. Which type of trend will the scatter plot show?
POSITIVE TREND
To determine the type of trend shown in a scatter plot, we need to analyze the relationship between the two variables, in this case, students' ages and their heights.
To do this, Abe can visually examine the scatter plot. Here's how Abe can identify the type of trend:
1. Look at the general pattern: Abe should observe if there is an overall direction or shape in the plotted points. Specifically, he should check if the points have a general tendency to move in a certain direction or form a specific pattern.
2. Consider the dispersion of points: Abe should examine how closely the data points cluster together. If the points are closely clustered around a line or curve, it suggests a stronger relationship.
Based on these observations, Abe can categorize the type of trend in a scatter plot as one of the following:
1. Positive Trend: If, on average, the height of students increases as their age increases, Abe can observe an upward sloping pattern in the scatter plot. This indicates a positive trend, suggesting that older students tend to be taller.
2. Negative Trend: Conversely, if the height of students decreases as their age increases, Abe can observe a downward sloping pattern in the scatter plot. This indicates a negative trend, suggesting that older students tend to be shorter.
3. No Trend: If there is no clear pattern or relationship between ages and heights, and the points are randomly scattered across the plot, there is no trend. This implies that there is no significant relationship between the two variables.
By examining these characteristics, Abe can identify the type of trend displayed in the scatter plot of students' ages and heights.