$2.$ Block Commodities has gathered the following information concerning rock salt deliveries $($tons$)$ to its clients, which it believes are highly seasonal:

Month Year $1$ Year $2$ Year $3$ Year $4$ Average Monthly

January $825988142512871131\mathrm{.}25$

February $528442510572513$

March $385624180616451\mathrm{.}25$

April $242442525275371$

May $22781801172\mathrm{.}75$

June $33653011059\mathrm{.}5$

July $308429525308392\mathrm{.}5$

August $15951274163513201456$

September $19912561243015952144\mathrm{.}25$

October $20902613330019802495\mathrm{.}75$

November $11001313165010781285\mathrm{.}25$

December $89191013059681018\mathrm{.}5$

Total $10010117391369510120$

a$.$ Suppose Block Commodities calculated a set of seasonal relatives to express this monthly variation in rock salt deliveries, using this set of data. Calculate the value of the seasonal relative for each month. And answer what would the value of the seasonal relative for October?

b$.$ Block Commodities believes that this year will be a busy year for rock salt deliveries, forecasting a total of $13000$ tons to be delivered during the year. Using this annual forecast and Block$$s set of seasonal relatives, what would be a logical forecast for May of next year?