a petting zoo graphed the average attendance of patrons ever y10 days over a 100 day period of time. interpret the scatterplot to determine what type of association the scatterplot shows.

1 answer

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:

  1. 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.
  2. 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.
  3. 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.
  4. 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.