The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Month Jan Number of Accidents 25 Feb 48 Mar 64 Apr 100 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): ŷ=0+0x 11

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### Accident Data Analysis Using Least-Squares Regression

**Accident Data on Florida State Highway 101**

The table below shows the number of accidents that occurred on Florida State Highway 101 over the last four months:

| Month | Number of Accidents |
|-------|---------------------|
| Jan   | 25                  |
| Feb   | 48                  |
| Mar   | 64                  |
| Apr   | 100                 |

**Trend Analysis**

To analyze this data, we'll use the least-squares regression method. This statistical technique helps in finding the best-fitting line through the data points to forecast future values.

**Trend Equation for Forecasting**

The trend equation is expressed in the form:

\[
\hat{y} = a + bx
\]

where \( \hat{y} \) is the predicted number of accidents, \( a \) is the y-intercept, \( b \) is the slope of the line, and \( x \) is the time variable (e.g., months in this case).

**Diagram or Graph Information**

If a graph were present, it would typically show:
- A plotted line representing the regression trend.
- Data points for each month depicting the number of accidents.
- The x-axis representing time (months) and the y-axis representing the number of accidents.

This visual representation would help in understanding the trend and how well the line fits the data points.
Transcribed Image Text:### Accident Data Analysis Using Least-Squares Regression **Accident Data on Florida State Highway 101** The table below shows the number of accidents that occurred on Florida State Highway 101 over the last four months: | Month | Number of Accidents | |-------|---------------------| | Jan | 25 | | Feb | 48 | | Mar | 64 | | Apr | 100 | **Trend Analysis** To analyze this data, we'll use the least-squares regression method. This statistical technique helps in finding the best-fitting line through the data points to forecast future values. **Trend Equation for Forecasting** The trend equation is expressed in the form: \[ \hat{y} = a + bx \] where \( \hat{y} \) is the predicted number of accidents, \( a \) is the y-intercept, \( b \) is the slope of the line, and \( x \) is the time variable (e.g., months in this case). **Diagram or Graph Information** If a graph were present, it would typically show: - A plotted line representing the regression trend. - Data points for each month depicting the number of accidents. - The x-axis representing time (months) and the y-axis representing the number of accidents. This visual representation would help in understanding the trend and how well the line fits the data points.
Expert Solution
Step 1: Understanding the given data

Here, the question is for linear regression using the least square method. We have to find the trend equation based on the data given. The data given is in the form of months and corresponding accidents. 

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