Uppgiftsinlämning 3

Ludvig Londos och Kalle Palm (laddy_ludde@msn.com, kalle.palm@gmail.com)

4.03

(a)

mean(time ~ sex, data = swim)

##     F     M 
## 65.19 54.66

min(time ~ sex, data = swim)

##     F     M 
## 53.52 47.84

Svar: 65.2 och 53.5

(b)

early = subset(swim, year < 1920)
mean(early$time)

## [1] 73.84

min(early$time)

## [1] 61.4

Svar: 73.8 och 61.4

(c)

slow = subset(swim, time > 60)
mean(slow$time)

## [1] 69.62

min(slow$time)

## [1] 60.2

Svar: 69.6 och 60.2

4.04

mod = mm(wage ~ sector, data = CPS85)
mod

## 
## Groupwise Model Call:
## wage ~ sector
## 
## Coefficients:
## clerical     const     manag     manuf     other      prof     sales  
##     7.42      9.50     12.70      8.04      8.50     11.95      7.59  
##  service  
##     6.54

(a)

9.5

(b)

12.7

(c)

Service

(d)

sd(fitted(mod))

## [1] 2.197

Svar: 2.20

(e)

sd(resid(mod))

## [1] 4.646

Svar: 4.65

4.05

mod1 = mm(wage ~ 1, data = CPS85)
mod2 = mm(wage ~ sector, data = CPS85)

(a)

var(fitted(mod1))

## [1] 0

var(fitted(mod2))

## [1] 4.825

Svar: mod2

(b)

var(resid(mod1))

## [1] 26.41

var(resid(mod2))

## [1] 21.59

Svar: mod1

(c)

4.06

(a)

mean(w$wage)

## [1] 9.024

Svar: 9.02

(b)

wageSex = mm(wage ~ sex, data = w)
wageSex

## 
## Groupwise Model Call:
## wage ~ sex
## 
## Coefficients:
##    F     M  
## 7.88  9.99

Svar: 7.88

(c)

gift = subset(w, married == "Married")
mean(gift$wage)

## [1] 9.398

Svar: 9.40

(d))

ogiftaKvinnor = subset(w, (married == "Single" & sex == "F"))
mean(ogiftaKvinnor$wage)

## [1] 8.26

Svar: 8.26

4.07

(a)

sd(g$height)

## [1] 3.583

Svar: 3.58

(b)

mod3 = mm(height ~ 1, data = g)
res = resid(mod3)
sd(res)

## [1] 3.583

Svar: 3.58

(c)

mod4 = mm(height ~ sex, data = g)
res1 = resid(mod4)
sd(res1)

## [1] 2.508

Svar: 2.51

(d)

Svar: Den andra modellen (kallad mod1 i uppgifterna)