Chapter- 4 statistical table and charts
Statistical table and statistical charts
Statistical table and statistical charts are major
descriptive tools, such as the frequency
distribution table and frequency distribution
graph in chapter two, which are more intuitionistic
and also useful to present summary information.
So it is widely used when we present the reports
or papers.
Tables in reports
Although tables are simple to understand
and to produce, careful thought regarding
layout is essential to draw attention to the most
useful and interesting features of the data. For
ease of reference, recommendations are given
here in note form.
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Structure of tables
sequence number of table
Title
headings
Line
Numbers
Footnote
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sequence number of table
Title
Table 3.1 the distribution of undergraduate majors
college
Number of majors
agriculture
1500
Arts and sciences
3200
education
1200
Engineering
4100
Row heading
lines
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Column
heading
numbers
sequence number of table
NOTICE
It appear in sequence in a report or
papers.
For example, table 1, table 2……
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Title
NOTICE
To summarize the contents that table
include.
For example, from the title “the
distribution of undergraduate majors”,
we can know the table want to describe
the undergraduate majors
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heading
NOTICE
It includes row heading and column
heading. The row heading or label is
used to describe the meaning of raw
number, and the column heading is
used to describe the meaning of column
number
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Line
NOTICE
Vertical or italic lines should be avoided
because these cluttter the presentation.
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Numbers
NOTICE
The decimal digits should be identical in
the same column.
The data in one column should arrange
trim in the decimal point.
When the measurement is 0, we should
not omit it but record it.
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recommendations
Each table should be self-explanatory . That
is to say, the reader should be able to
understand it without reference to the text in
the body of the report. This can be achieved
by using complete, meaningful labels for the
rows and columns and giving a complete,
meaningful title. Footnotes should be used to
enhance the explanation when necessary.
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recommendations
Each table should have an attractive
appearance. Sensible use of white
space helps enormously. Different
typefaces or fronts may be used to
provide discrimination, for example, use
of bold type or italics.
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recommendations
The rows and columns of each table
should be arranged in a natural order.
This is a great help in interpretation.
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Table 3.2 occupational social class in the SHHS
Social class
（%）
Ⅰ
Nonmanual， professional
592
7
Ⅱ
Nonmanual，intermediate
2254
26
Ⅲn
Nonmanual ， skilled
1017
12
Ⅳm
manual ， skilled
3150
36
Ⅳ
manual ，partially skilled
1253
14
Ⅴ
manual ， unskilled
415
5
Total
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number
8681
Table 3.3 Study participant characteristics by diabetic status
Gender
Men
Women
Age (years)
Education*
Less than High School
High School or Higher
Occupation*
Professional
Laborer
Other
Marital status*
Not Married
Married
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NFG
(n=13129)
IFG (n=1121)
DM
(n=986)
Total
(n=15236)
52.14(0.44)
49.76(0.09)
49.76(0.09)
46.92(1.49)
53.38(0.32)
53.38(0.32)
50.41(1.59)
55.10(0.33)
55.10(0.33)
51.64(0.40)
50.37(0.09)
50.37(0.09)
67.10(0.41)
32.90(0.41)
70.27(1.37)
29.73(1.37)
71.40(1.44)
28.60(1.44)
67.61(0.38)
32.39(0.38)
29.51(0.40)
65.63(0.41)
4.86(0.19)
31.43(1.39)
65.00(1.42)
3.57(0.55)
31.60(1.48)
63.61(1.53)
4.79(0.68)
29.79(0.37)
65.45(0.39)
4.76(0.17)
8.40(0.24)
91.60(0.24)
10.27(0.91)
89.73(0.91)
11.16(1.00)
88.84(1.00)
8.72(0.23)
91.28(0.23)
Typical Case
Table 3.4 Average increase of concentration of Hb in two groups ( x  s )
i.
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groups
n
the increase of concentration of Hb（g/L）
new drug group
10
27.99±34.56
routine drug group
10
20.21±3.82
Cases resolution
Table 3.4 Average increase of concentration of Hb in two groups ( x  s)
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groups
n
the increase of concentration of Hb（g/L）
new drug group
10
27.99±34.56
routine drug group
10
20.21±3.82
charts in reports
Scatter
graph
Statistical charts
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Bar chart
Scatter graph
histogram
Pie chart
Line chart
map
bar chart
[Usage] the independent data or categorical data
In the bar chart, the bars are drawn of
equal width, but the heights are
proportional to the percentages. Other
possible scales for the vertical axis are the
frequencies or relative frequencies, both of
which leave the shape of the bar chart
unaltered.
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[example 1]
The following table is the average heights
of adult male in 3 countries. Please choose
the applicable graph to describe them.
Table 3.5 the average heights
of adult male in 3 countries
area
China
American
Japan
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Average heights
175
177
171
Average heights
180
175
177
China
Amerian
160
171
140
120
100
80
60
40
20
0
Japan
area
Fig 1 the average heights
of adult male in 3 countries
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attention
When drawing the bar chart, the
vertical scale must begin from 0.
Leave some space between two bar.
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175
177
160
140
180
Average heights
180
171
177
175
171
170
120
100
80
160
60
40
20
0
China
Amerian
150
Japan
China
area
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Amerian
Japan
area
[example 2]
The following table is the average heights of
adult male and female in 3 countries. Please
choose the applicable graph to describe them.
Table 3.6 the average heights
of adult male and female in 3 countries
area
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Average heights
of adult male
Average heights
of adult female
China
Amer ican
175
177
159
166
Japan
171
155
Average heights
180
175
177
160
171
159
166
155
140
120
100
80
60
40
China
20
Amerian
0
Japan
MALE
FEMALE
gender
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Pie chart
[usage] constitutional data
In a pie chart, the area of the slices are
drawn in proportional to the frequencies by
simply dividing the entire 3600 of the circle
into separate angles of the correct relative
size.
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Pie chart
Table 3.7 The antibody level of HBeAb
of 182 people after injecting the vaccine
outcome
+
++
+++
total
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n
percentile（%）
37
71
60
14
20.3
39.0
33.0
7.7
182
100.0
Pie chart
Attention
While drawing a pie chart, one circle has
3600, so 1% should include 3.60 . Usually we
bigin to draw the circle from the position of
12 o’clock. We can use the protractor to
measure the angle.
Percentile
outcome
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（%）
angle
+
20.3
39.0
73.1
140.4
++
+++
33.0
7.7
118.8
27.7
total
100.0
360.0
Pie chart
+++
7.7%
++
33.0%
20.3%
+
39.0%
Fig 3 The antibody level proportionof
HBeAb of 182 people
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Histogram
[usage] the continuous data
such as height, weight, RBC.
In the histogram, the rectangle are
drawn of equal width because the interval
width is same, but areas are proportional
to the percentages or frequence.
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Table 3.8 Serum total cholesterol (mmol/L) of 50
subjects from the Scottish Heart Health Study
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5.75
6.29
6.13
6.78
6.46
6.76
5.98
6.25
6.31
5.99
6.47
5.71
5.19
4.35
5.35
7.11
6.89
6.05
7.01
5.86
5.42
4.92
7.12
5.85
5.64
7.04
6.23
5.71
6.74
6.36
5.75
7.71
6.19
7.55
6.76
7.14
5.73
6.73
7.86
5.51
6.02
6.54
5.34
6.92
7.15
6.55
7.16
4.79
6.64
6.83
12
11
11
11
10
8
7
6
4
4
3
2
0
Std. Dev = . 76
2
Mean = 6.29
1
4. 25
N = 50.00
4. 75
5. 25
5. 75
6. 25
6. 75
7. 25
7. 75
Serum Cholesterol
Fig4 frequency distribution graph for serum total cholesterol
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Histogram
frequence
Height(cm)
Fig5 frequency distribution graph for heights
of 100 students with 8 year old
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attention
When drawing the histogram, the
vertical scale must begin from 0.
Leave no space between two rectangles.
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line
[usage] the continuous data
It is used to describe the deveploment
trend that one thing changes with the
other thing (usually time).
For example, the incidence rate of
HIV/AIDS in the past years.
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line
attention
Whether the scale of vertical axis may
begin from zero or not, it is right.
The near two point should be linked
with breaking line. That is to say, we
can not choose smooth line while
drawing the line.
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line
the death rate of infants
（1/thousand）
140
120
100
80
60
40
20
0
1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 year
FIG6
The death rate of infants in canda in 1949-1958
line
the death rate of infants
（1/thousand）
140
120
100
80
60
40
20
0
1949 1950 1951 1952 1953 1954 1955 1956 1957 1958
year
FIG6
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The death rate of infants in canda in 1949-1958
Scatter graph
[usage] the biovariate data
If we want to learn the trend before
describing the relationship between two
variables, we can choose scatter graph.
For example, the relationship between
height and weight.
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Scatter graph
If we want to learn
the relationship
between the
concentration of
thrombin (y) and
thrombin time (x),
we can choose
scatter graph
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Y
Scatter graph
18
17
16
15
14
13
12
.5
.6
.7
.8
.9
1.0
1.1
1.2
1.3
X
Fig 7 the scatter graph between the
concentration of thrombin and thrombin time
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Scatter graph
0.2
Y
0.15
0.1
0.05
0
1000
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1200
1400
X
1600
1800
map
FIG 1 the incidence rate of AIDS in China in 2010
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