Question

Car Mazda3 Buick Encore Toyota Corolla Chrevolet Tahoe Chrevolet Equinox Ford Fiesta BMW 528i Mitsubishi Mirage GMC Yukon Dodge Dart Honda Accord Hybrid Audi Q5 Hyundai Elantra Kia Sedona Dodge Grand Caravan Lexus CT Lincoln MKZ Hybrid Mercedez-Benz E-Class Scion tC MINI Countryman New Used Depreciation 17956 15326 2363321498 16091 4548943463 2159619149 14246 46227 44582 14013 4729545635 16139 27124 25008 3752135579 16807 14876 2571022178 21337 17390 30743 33522 30892 4717842956 1974818697 25130 23513 2630 2135 1330 2026 2447 2026 1645 2410 1660 2259 2116 1942 1931 3532 3947 3561 2630 4222 1051 1617 14761 12220 11603 13880 27182

Answer 1

Maam 23 55. 85 Standard error=g 132.134 2397.975 ),96 x17 2 ,134 233. 3333 2 드 2000,5922675-358 ) 27.358

# Using R

> x=c(2630,2135,1330,2026,2447,2026,1645,2410,1660,2259,2116,1942,1931,3532,
+ 3947,3561,2630,4222,1051,1617)
>
> ### Part a)
> mean(x)
[1] 2355.85
> sd(x)
[1] 857.9969
>
>
> #### Part b)
>
> boot.mean=function(data, nsim)
+ {
+ n=length(data)
+ BOOT=list()
+ x.mean=list()
+
+ for(i in 1:nsim)
+ {
+ BOOT[[i]]=sample(data, size=n, replace = TRUE)
+ x.mean[[i]]=mean(BOOT[[i]])
+ }
+ return(x.mean)
+ }
>
>
> ## Run
>
> Boot.mean=boot.mean(data=x, nsim=200)
>
> Boot.mean=unlist(Boot.mean)
>
>
> Center=quantile(Boot.mean, c(0.50))
> Center
50%
2337.975
>
> sd(Boot.mean)
[1] 172.134