use the data table to answer questions 1 - 4. the city of racine, wi can have unpredictable weather in the…

use the data table to answer questions 1 - 4. the city of racine, wi can have unpredictable weather in the summer time. here are some temperatures that were reported last summer and the number of people that came to the public pool.\n\n| temperature | number of people that visited the pool | temperature | number of people that visited the pool |\n| ---- | ---- | ---- | ---- |\n| 65°f | 32 | 91°f | 127 |\n| 54°f | 21 | 77°f | 74 |\n| 75°f | 87 | 93°f | 32 |\n| 88°f | 112 | 63°f | 11 |\n| 92°f | 148 | 76°f | 96 |\n| 90°f | 135 | 68°f | 71 |\n\n1) create a scatter plot using the data in the table.\n2) what type of association do the two variables seem to have? (positive linear association, negative linear association, non - linear association, no association.)\n3) does there appear to be an outlier? if so, what could be the reason it is an outlier?\n4) if you were hired as the new pool manager, when would you schedule the most lifeguards and pool staff?

use the data table to answer questions 1 - 4. the city of racine, wi can have unpredictable weather in the summer time. here are some temperatures that were reported last summer and the number of people that came to the public pool.\n\n| temperature | number of people that visited the pool | temperature | number of people that visited the pool |\n| ---- | ---- | ---- | ---- |\n| 65°f | 32 | 91°f | 127 |\n| 54°f | 21 | 77°f | 74 |\n| 75°f | 87 | 93°f | 32 |\n| 88°f | 112 | 63°f | 11 |\n| 92°f | 148 | 76°f | 96 |\n| 90°f | 135 | 68°f | 71 |\n\n1) create a scatter plot using the data in the table.\n2) what type of association do the two variables seem to have? (positive linear association, negative linear association, non - linear association, no association.)\n3) does there appear to be an outlier? if so, what could be the reason it is an outlier?\n4) if you were hired as the new pool manager, when would you schedule the most lifeguards and pool staff?

Answer

Explanation:

Step1: Analyze the association

As the temperature increases, generally the number of people visiting the pool increases. So, there is a positive linear association.

Step2: Identify the outlier

The point (93°F, 32 people) seems to be an outlier. Possible reasons could be a special event in the city on that day that drew people away from the pool, or bad - publicity about the pool on that day, or some unforeseen local circumstances.

Step3: Determine staffing

Since there is a positive linear association between temperature and number of visitors, schedule the most lifeguards and pool staff on days with the highest predicted temperatures.

Answer:

  1. Positive linear association
  2. Yes, the outlier is (32, 93). Possible reasons include special events in the city, bad - publicity about the pool, or unforeseen local circumstances.
  3. On days with the highest predicted temperatures.