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Consider the following time series data:

$\backslash$table$[[$Month$,1,2,3,4,5,6,7],[$Value$,25,12,20,12,19,23,14]]$

$($a$)$ Compute MSE using the most recent value as the forecast for the next period.

If required, round your answer to one decimal place.

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What is the forecast for month $8?$

If required, round your answer to one decimal place. Do not round intermediate calculation.

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$($b$)$ Compute MSE using the average of all the data available as the forecast for the next period. If required, round your answer to one decimal place. Do not round intermediate calculation.

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What is the forecast for month $8?$

If required, round your answer to one decimal place.

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$($c$)$ Which method appears to provide the better forecast?

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Consider the following time series data.

$\backslash$table$[[$Week$,1,2,3,4,5,6],[$Value$,18,13,16,11,17,14]]$

Using the naive method, $($most recent value$)$ as the forecast for the next week, compute the following measures of forecast accuracy.

$($a$)$ Mean absolute error

If required, round your answer to one decimal place.

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$($b$)$ Mean squared error

If required, round your answer to one decimal place.

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$($c$)$ Mean absolute percentage error

If required, round your intermediate calculations and final answer to two decimal places.

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$($d$)$ What is the forecast for week $7?$

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