Make a scatter plot of the data in the table:

I can't create visual content directly, but I can guide you on how to make a scatter plot using the data you provided and help you analyze the relationship between temperature and chirps.

Steps to Create a Scatter Plot:

1. Data Preparation: Your data consists of two columns:

   • X-axis: Temperature (°F)
   • Y-axis: Chirps per minute

   Here's the data in a more structured format:

   | Temperature (°F) | Chirps/min | |-------------------|------------| | 71 | 138 | | 68 | 97 | | 75 | 152 | | 80 | 158 | | 60 | 81 | | 75 | 155 | | 84 | 165 |

2. Plotting:

   • On graph paper or using software like Excel, Google Sheets, or Python (with libraries like Matplotlib or Seaborn), plot the temperature on the X-axis and chirps per minute on the Y-axis.
   • Each data point should correspond to a (Temperature, Chirps/min) pair.

Explanation of the Relationship:

Once you've plotted the data points, observe the following:

1. Trend: Look for a pattern (i.e., do the chirps/min tend to increase as the temperature increases?).
2. Correlation: Check if the points generally form an upward trend. If they do, it indicates a positive correlation, where higher temperatures are associated with a higher number of chirps.
3. Strength: Consider how tightly the points cluster around a line. A strong relationship would show points closely following a line, while a weak relationship would show points more spread out.

Conclusion:

Based on the data you've provided, we can likely infer that as the temperature increases, the number of chirps per minute also tends to increase, suggesting a positive correlation. For more rigorous analysis, you could calculate the correlation coefficient (e.g., Pearson's r) to quantify the relationship.

If you would like further assistance on how to calculate that or use any specific software or programming language, let me know!