Statistics

Running head: STATISTICS 1
Statistics
By (Author’s Name)
(Institutional Affiliation)
(Date of Submission)

STATISTICS 2Section A
1. Consider the data set below, for the variable
mobility. These are % measures
of the movement of people in and out of cities.
15 20 13 14 17 17 14 23 19 31 18 34
35 42 15 24 21
49 12 27 22 19 31 32 38 34 23 25 35
24 36 36 47 27 25 25 37 19 27 26 44
41 32
a) Specify if the variable
mobility is Quantitative or Categorical. Explain your
answer. (1)
HINT: Think about the variable!
The variable is categorical. This is because the data is one of the two type’s i.e.
movement of people in and out of cities.
b) The data is collected for the survey by analyzing 43 cities. Give an example
of one categorical variable that could be collected from the survey.
(1)
i. Sex
c) Make a split-stemplot of the
mobility data. Remember to include a Key.
(4)
1 2344 Key: 1|2
represent 12 n:43
1. 55778999 left unit 1
2 0123344
2. 556777
3 112244
3. 556678
4 124
4. 79
2

STATISTICS 3
d) Describe the shape of this distribution.
(2)
Based on the split-stemplot above, the plot is skewed to the left since majority
of the data are located on the high side. With this, it can be asserted that the
data is not normally distributed and hence shows failure time data.
e) Calculate the following statistics:
do not use R
(10)
Range = Maximum-Minimum value
Median = Middle value after arranging
= 25
Lower quartile, Q1 = 25% percentile of the data
= which is the 11th value
= 19.00
Upper quartile, Q3 = 75% percentile
= which is 33rd value
= 34.50
Mean = [15+20+13+14 +17+...+ 41+32]
43
= 27.093
Standard deviation = 1.484066
20th percentile = 9th value in the rank
= 14.50
Interquartile range = Upper quartile –lower quartile
= 2.
f) Give the five-number summary of the
mobility data.
(3)
Put your results in the table:
g) Draw a horizontal box and whisker plot of the
mobility data.
(3)
3
Minimu
m
Maximu
m
Mean Lower
Quartile
(Q1)
Upper
Quartile
(Q3)
12 49 27.0930
2