Final answer:
To forecast the number of accidents that will occur in May using least-squares regression, historical data on the number of accidents over a period of time is needed. Using a linear equation derived from the least-squares regression, the value of May (the corresponding x-value) can be plugged in to predict the number of accidents in May.
Step-by-step explanation:
To forecast the number of accidents that will occur in May using least-squares regression, you would need historical data on the number of accidents over a period of time. Let's assume you have data on the number of accidents for each month for the past year. You can use least-squares regression to find a linear equation that best fits the pattern of the data. Once you have the equation, you can input the value of May (the corresponding x-value) to predict the number of accidents in May.
Here's an example:
Let's say the number of accidents for each month of the past year are as follows:
- January: 25 accidents
- February: 28 accidents
- March: 26 accidents
- April: 30 accidents
- May: ?? (to be predicted)
The x-values would be the month numbers, starting from 1 for January. The y-values would be the number of accidents for each month. You can use a calculator or software to perform the least-squares regression. Once you have the equation, you can substitute the x-value for May (5 in this case) to predict the number of accidents.