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The image you've shared includes a problem related to matrices and vehicle sales data. Here’s a breakdown of the tasks based on the image:

### Part (a)
You are asked to organize the vehicle sales data for 2015 and 2016 into two matrices.

From the table:
- **2015 Matrix** (Company A & B):
\[
\begin{bmatrix}
249 & 14 & 91 & 295 \\
164 & 9 & 60 & 189
\end{bmatrix}
\]

- **2016 Matrix** (Company A & B):
\[
\begin{bmatrix}
241 & 15 & 103 & 286 \\
159 & 10 & 68 & 195
\end{bmatrix}
\]

### Part (b)
You are asked to find the matrix of average sales for each vehicle type across the two years. To find the average, we calculate:

\[
\text{Average} = \frac{2015 \text{ sales} + 2016 \text{ sales}}{2}
\]

For Company A:
- Car: \(\frac{249 + 241}{2} = 245\)
- Motorcycle: \(\frac{14 + 15}{2} = 14.5\)
- Truck: \(\frac{91 + 103}{2} = 97\)
- Utility: \(\frac{295 + 286}{2} = 290.5\)

For Company B:
- Car: \(\frac{164 + 159}{2} = 161.5\)
- Motorcycle: \(\frac{9 + 10}{2} = 9.5\)
- Truck: \(\frac{60 + 68}{2} = 64\)
- Utility: \(\frac{189 + 195}{2} = 192\)

So, the matrix of average sales is:
\[
\begin{bmatrix}
245 & 14.5 & 97 & 290.5 \\
161.5 & 9.5 & 64 & 192
\end{bmatrix}
\]

### Part (c)
In part (c), you're asked to interpret the matrix from part (b). The matrix shows the **average number of vehicles sold** by **type** for **Company A and Company B** over the two years, 2015 and 2016. Each entry represents the average sales of that vehicle type for the respective company.

Would you like more details on any of these steps?

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Here are 5 related questions:
1. How are matrices typically used to organize large datasets like sales figures?
2. What would happen if we calculated the average of more than two years' worth of data?
3. How could we represent sales as a percentage of the total in matrix form?
4. How does matrix addition or subtraction work for data like this?
5. Can matrix multiplication be applied to sales data, and how would the interpretation change?

### Tip:
When working with matrices, always ensure that the dimensions are aligned correctly for any operation (addition, subtraction, multiplication).

The table shows the numbers (in thousands) of vehicles sold by type and company in 2015 and 2016. Organize the information into matrices representing the numbers of vehicles sold by type and company for these years, find the average sales matrix, and interpret it.

Analyze the vehicle sales data for 2015 and 2016 with matrices. Learn how to organize data into matrices, find the average sales for each vehicle type, and interpret the results. This problem covers matrix operations and data interpretation, suitable for Grades 9-12.

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