The answers for these two Suppose a govemment department would lke to investigat

Question

The answers for these two Suppose a govemment department would lke to investigate the relationship between the cost of heating a home during the month of February in the Norheast and the homes square footage. The accompanying data set shows a random sample of 10 harnes. Construct a 90% predetion rtervai to estman the oost in February to heat a Northeast home that ts 2,700 seat feet Cick the ioon to view the data table Determine the upper and lower limits of the prediction interval. UPL Round to bwo decimal places as needed) Heating Square HeatingSquare Cost (s) Footage Cost) Footage 440 2.020 330 2,220 330 2.420 300 2,420 290 2,030 200 2.240 300 2,330 2,540 2,930 370 Print Done

Explanation / Answer

R codes :

#problem-1
> cost=c(330,300,290,260,300,440,330,380,330,370)
> sqft=c(2420,2420,2030,2240,2330,2620,2220,3110,2540,2930)
> model=lm(cost~sqft) #fitting linear model to the data
> newdata=data.frame(sqft=2700) #new x
> predict(model,newdata,interval="predict",level=0.9) #predicted y
fit lwr upr
1 356.1161 275.907 436.3252

90% prediction interval : (275.907, 436.3252)

#problem-2
> cost=c(350,280,290,250,320,450,320,400,320,380)
> sqft=c(2430,2440,2020,2210,2340,2620,2220,3130,2540,2950)
> model=lm(cost~sqft)
> newdata=data.frame(sqft=3000)
> predict(model,newdata,interval="predict",level=0.9)
fit lwr upr
1 399.4684 301.3197 497.6171

90% prediction interval : (301.3197, 497.6171)

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