5% of males 36 months of age weigh 12kg or less. 95% of males 36 months of age weigh more than 12kg.
95% of newborn females are 53.8cm or less. 5% of newborn females are longer than 53.8cm.
25% of the states have a violent-crime rate that is 252.4 crimes per 100,000 population or less and 75% of the states have a violent-crime rate more than 252.4. 50% of the states have a violent that is 333.8 crimes per 100,000 populaiton or less while 50% of the states have a violent-crime rate more than 333.8. 75% of the states have a violent-crime rate that is 454.5 crimes per 100,000 population or less, and 25% of the states have a violent-crime rate more than 454.5.
IQR=454.5-252.4= 202.1; The middle 50% of the observations have a violent-crime rate of 202.1 violent crimes per 100,000 population.
Upper Fence= 757.65 Lower Fence= -50.75
Yes, the violent crime rate of 1243.7 is an outlier because it is above the upper fence. 1243.7>757.65
skewed right
MIN=0, Q1=1, MEDIAN=3, Q3=6, MAX=16 or (0,1,3,6,16)
symmetric
MIN=-1, Q1=3, MEDIAN=5, Q3=8, MAX=11 or (-1,3,5,8,11)
MEDIAN= 40
Q3= 53
Variable y because the data is spread over more values than variable x. Variable y has a larger range than x.
Symmetric because the median is relatively centered and (median-Q1)=(Q3-median). Additionally, (Q1-min)=(max-Q3).
Skewed right because (max-Q3)>(Q1-min) and (Q3-median)>(median-Q1).
MEDIAN= 16
Q1= 24
Variable y has a larger range than variable x and therefore has more dispersion.
Yes, there is one outlier that is 29.
Skewed left because (Q1-min)>(max-Q3) and (Q3-med)<(med-Q1)
data <- c(.608,.608,.608,.610,.612,
.601,.610,.608,.607,.598,
.606,.610,.605,.611,.600,
.602,.607,.609,.608,.605,
.611,.600,.605,.610,.603)
boxplot(data,horizontal = T)