The 5-point moving average for Wednesday was calculated using the 5 days centered on it (Mon–Fri). Similarly, the average for Friday uses the 5 days centered on Friday (Wed–Sun): $\frac{24.6 + 25.2 + 25.6 + 25.7 + 25.9}{5} = \frac{127.0}{5} = 25.4$.

This is incorrect. The sum of the temperatures from Wednesday to Sunday is $127.0$, which results in an average of $25.4$, not $25.5$.

This is the actual temperature recorded on Friday ($25.6^\circ\text{C}$), rather than the calculated 5-point moving average.

This value is incorrect. It is significantly higher than the actual average of the temperatures from Wednesday to Sunday.

The sum of seasonal indices for four quarters must equal 4. The Q4 index is $4 - (0.6 + 0.8 + 1.0) = 1.6$. Seasonally adjusted sales are calculated by dividing actual sales by the index: $\frac{7200}{1.6} = 4500$.

This assumes the seasonal index follows a linear pattern (0.6, 0.8, 1.0, 1.2) and divides sales by 1.2. However, seasonal indices must sum to the number of periods (4), making the correct Q4 index 1.6.

This result likely comes from estimating the index incorrectly as 1.2 (based on a pattern) and multiplying it by the sales, rather than dividing by the correct index.

This is the result of multiplying the actual sales by the seasonal index ($7200 \times 1.6$). To deseasonalize data (find seasonally adjusted sales), you must divide the actual sales by the seasonal index.