To interpret the scatterplot of average attendance at a petting zoo over a 100-day period graphed every 10 days, you would typically look for the following characteristics:
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Direction: Determine if the data points trend upward, downward, or remain constant.
- Positive Association: If the points trend upwards as you move from left to right, it indicates that attendance tends to increase over time.
- Negative Association: If the points trend downwards, it suggests that attendance decreases over time.
- No Association: If the points are scattered randomly without any clear upward or downward trend, it shows minimal or no correlation.
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Form: Observe the shape of the data points.
- Linear Pattern: If the points roughly form a straight line (either upward or downward), it indicates a linear association.
- Non-linear Pattern: If the points create a curve, it suggests a non-linear relationship.
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Strength: Assess how closely the data points fit the identified trend.
- Strong Association: If the points are close to a line or curve, it indicates a strong relationship.
- Weak Association: If the points are more spread out but still follow a general trend, it is a weaker relationship.
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Outliers: Look for any points that fall significantly outside the general trend, as these can indicate anomalies in attendance.
Based on this description, here’s how you might summarize the associations:
- If attendance increases over the first 100 days, it may indicate growing popularity or seasonality in attendance.
- If attendance fluctuates widely without a clear trend, it might suggest factors such as weather or events affecting visitors.
- If attendance consistently decreases, it may warrant further investigation into operational or external factors impacting patron interest.
To provide a definitive interpretative analysis, specific visual data from the scatterplot would be necessary. However, with the guidelines above, you can analyze your scatterplot type effectively.