Question

An insurance agent is looking at records to determine if there is a relationship between a driver's age and

percentage of accidents caused by speeding. The table below shows his data

State the linear regression equation that models the relationship between the driver's age, and the percentage of
accidents caused by speeding. Round all values to the nearest hundreddy
State the value of the correlation coefficient to the nearest hundredth. Explain what this means in the context of
the problem.

Answer 1

To determine the linear regression equation and the correlation coefficient, we need the data provided in the table. Unfortunately, the table you mentioned is missing from your question. Without the data, it is not possible to calculate the linear regression equation or the correlation coefficient.

In a scenario where an insurance agent is examining the relationship between a driver's age and the percentage of accidents caused by speeding, the linear regression equation would allow us to predict the percentage of accidents caused by speeding based on the driver's age. The correlation coefficient would indicate the strength and direction of the relationship between these two variables. A correlation coefficient of 1 would indicate a perfect positive relationship, -1 would indicate a perfect negative relationship, and 0 would indicate no linear relationship.

If you can provide the data from the table, I'll be able to assist you further in determining the linear regression equation and the correlation coefficient.