School

Harrisburg University of Science and Technology **We aren't endorsed by this school

Course

ANLY 502-51

Subject

Statistics

Date

Aug 27, 2023

Pages

4

Uploaded by yorkchen97 on coursehero.com

Lecture 4
2023-08-24
download.file
(
"http://www.openintro.org/stat/data/bdims.RData"
,
destfile =
"bdims.RData"
)
load
(
"bdims.RData"
)
mdims
<-
subset
(bdims, sex
==
1
)
fdims
<-
subset
(bdims, sex
==
0
)
1. The histogram for female biiliac (pelvic) diameter ( bii.di ) belongs to normal probability
plot letter B.
2. The histogram for female elbow diameter ( elb.di ) belongs to normal probability plot letter
C.
3. The histogram for general age ( age ) belongs to normal probability plot letter D.
4. The histogram for female chest depth ( che.de ) belongs to normal probability plot letter A.
#A
qqnorm
(fdims
$
che.de)
qqline
(fdims
$
che.de)

#B
qqnorm
(fdims
$
bii.di)
qqline
(fdims
$
bii.di)
#C
qqnorm
(fdims
$
elb.di)
qqline
(fdims
$
elb.di)

#D
qqnorm
(fdims
$
age)
qqline
(fdims
$
age)
Note that normal probability plots C and D have a slight stepwise pattern. Why
do you think this is the case?
-> Stepwise pattern is common among discrete data. In this case, Age is a whole number,
which normally falls in the range of 0-100. Elbow diameter is rounded to 1 decimal, and the
differences between each sample is small.
As you can see, normal probability plots can be used both to assess normality
and visualize skewness. Make a normal probability plot for female knee
diameter ( kne.di ). Based on this normal probability plot, is this variable left
skewed, symmetric, or right skewed? Use a histogram to confirm your findings.
-> It's right skewed.
qqnorm
(fdims
$
kne.di)
qqline
(fdims
$
kne.di)

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