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Data Presenting I
Dr Tarekk Alazabee
2012
Qualitative Data:
Tabulation.
Graphs
Learning Objective
 Identify the different methods of
qualitative data presenting.
Data
Presentation
Tables Graphs Mapping
45 11.7
340 88.3
385 100.0
GENDER
MALE
FEMALE
Total
Frequency Percent
The way in which data presented
depends on the type of variable used.
悋惠愃惘悋愕惠惺 惺 惺 惠惺惠惆 悋惡悋悋惠 惺惘惷 愀惘悸 悒
i. Tabulation:
a. A simple Table.
b. Cross-tabulation.
ii. Graphs:
a. Simple bars.
b. Clustered Bars.
c. Pie Chart.
I. Qualitative Data
i. Tabulation
悖惆悽385悋愕惠愆悋惠 悒忰惆 悒 悋愕惘 惡悋惆悋悄 惘惷悋
340悗悋悄悋惘惷悒悋惓悋 悋悋愕 悴惺 悋惡惠
88.3%悋惘惷 惺惆惆 悋 忰  悋惘惷 悴 
愕悋 悋悵惘45惘惷悋惓悋惡悋惠悋11.7%悴 
悋惘惷.
惓悋
悋愀惡:悴惆  悋愕惘 悋惆悋悄 惘惷 惡悴愕 悋惠惺悸 悋惡悋悋惠 惓
a. A simple Table.
悋悒悋惓 惘惷 悋悧悸 悋愕惡悸:
悋悵惘 惘惷 悋悧悸 悋愕惡悸:
340
385
x100=% 88.3
45
385
x100=% 11.7
a. A simple Table.
Table (X): The distribution of Gender 
45 11.7
340 88.3
385 100.0
GENDER
MALE
FEMALE
Total
Frequency Percent
Category
Category
(悋惺 悋惠愃惘) Variable
(悋悧悸)
(悋惠惘悋惘) (悋悧悸 悋悋愕惡悸)
a. A simple Table.
The basic rule for displaying qualitative
data is to:
 Classify them into categories.
 Count the number of observations in
each category of the variable.
 Present the numbers and percentages in
the table.
Tabulation
Cross Tabulation
 In many situations; it is very useful to
present two or more variables at a time
in one table
QualitativeDatapresentation
惓悋
悋惆惘悋愕悋惠 悒忰惆 悖悽惷惺惠悋惠惆悽 惡惺悋惆悸 悋惠惺悸20愆悽惶悋,
悋惠 悋惠悋悧悴 悋惠悋:
-悋惆惘悋愕悸  愆悋惘12 悵惘悋8悒悋惓.
-悋惆悽 悒悴悋 悋10悋 悴  悖愆悽悋惶20
愆悋惘悋
-悵惘 惡悋愕惡悸:悋惆悽 惺惆惆 悋812愆悋惘悋.
-悒悋惓 惡悋愕惡悸:悋惆悽悋惠 惺惆惆 悋28愆悋惘悋惠.
悋愀惡:悋惠惺悸 悋惡悋悋惠 惓惡惺 悋愆悋惘
惺悋惆悸 悋 悋惆惘悋愕悸悴惆  悋惠惆悽
Cross Tabulation
悵惘 惡悋愕惡悸:
悋惆悽 愃惘 悋悧悸 悋愕惡悸=
悋惆悽 悵惘 悋悧悸 悋愕惡悸:
悒悋惓 惡悋愕惡悸:
悋惆悽悋惠 愃惘 悋悧悸 悋愕惡悸=
惆悽悋惠 悋悧悸 悋愕惡悸=
12
4x100=% 33.3
8
12
x100=% 66.7
x
8
6
= 100% 75.0
8
2x100% 25.0 =
悋悧悸 悋愕惡 忰愕悋惡惺悋惠惆悽 惺悋惆悸 悋 悋愆惠惘
Cross Tabulation
4 6 10
33.3% 75.0% 50.0%
8 2 10
66.7% 25.0% 50.0%
12 8 20
100.0% 100.0% 100.0%
Frequency
%
Frequency
%
Frequency
%
Smoking
NO
YES
Total
Male Female
Sex
Total
悋惠愃惘(Variable)
悋惠愃惘(Variable)
Cross Tabulation
ii. Graphical Forms
A. Bars Chart
- Simple Bars
- Clustered Bars
悖惆悽385悋愕惠愆悋惠 悒忰惆 悒 悋愕惘 惡悋惆悋悄 惘惷悋
340悗悋悄悋惘惷悒悋惓悋 悋悋愕惡惠 悴惺 悋
88.3%悋惘惷 惺惆惆 悋 忰  悋惘惷 悴 
悋愕惠愆 愕 悒 悖惆悽悋 悋悵 悋悵惘45惘惷悋惓悋
惡悋惠悋11.7%悋惘惷 悴 .
惓悋
悋愀惡:悋愕惘 悋惆悋悄 惘惷 惡悴愕 悋惠惺悸 悋惡悋悋惠 惓
悋悖惺惆悸 愆 
Simple Bars
悋悒悋惓 惘惷 悋悧悸 悋愕惡悸:
悋悵惘 惘惷 悋悧悸 悋愕惡悸:
340
385
x100=% 88.3
45
385
x100=% 11.7
Simple Bars
GENDER
FEMALEMALE
%
100.0
80.0
60.0
40.0
20.0
0.0
88.3
11.7
% 88.3
% 11.7
SEX
Clustered Bars
惓悋
悋惆惘悋愕悋惠 悒忰惆 悖悽惷惺惠悋惠惆悽 惡惺悋惆悸 悋惠惺悸20愆悽惶悋,
悋惠 悋惠悋悧悴 悋惠悋:
-悋惆惘悋愕悸  愆悋惘12 悵惘悋8悒悋惓.
-悋惆悽 悒悴悋 悋10悋 悴  悖愆悽悋惶20
愆悋惘悋
-悵惘 惡悋愕惡悸:悋惆悽 惺惆惆 悋812愆悋惘悋.
-悒悋惓 惡悋愕惡悸:悋惆悽悋惠 惺惆惆 悋28愆悋惘悋惠.
悋愀惡:悋惠惺悸 悋惡悋悋惠 惓惡惺 悋愆悋惘
悖惺惆悸 愆 惺 悋惠惆悽 惺悋惆悸 悋惆惘悋愕悸
Clustered Bars
悵惘 惡悋愕惡悸:
悋惆悽 愃惘 悋悧悸 悋愕惡悸=
悋惆悽 悵惘 悋悧悸 悋愕惡悸:
悒悋惓 惡悋愕惡悸:
悋惆悽悋惠 愃惘 悋悧悸 悋愕惡悸=
惆悽悋惠 悋悧悸 悋愕惡悸=
12
4x100=% 33.3
8
12
x100=% 66.7
x
8
6
= 100% 75.0
8
2x100% 25.0 =
Clustered Bars
33.3
75.0
66.7
25.0
Male
Female
Clustered Bars
 Is most commonly used.
 Count or percentages of the
characteristics in different categories
are shown as bars.
 The Bars are equal in width, and the
height of the bars is proportion to
frequencies
Regarding to bar Chart
B. Pie Chart
悖惆悽385悋愕惠愆悋惠 悒忰惆 悒 悋愕惘 惡悋惆悋悄 惘惷悋
340悗悋悄悋惘惷悒悋惓悋 悋悋愕惡惠 悴惺 悋
88.3%悋惘惷 惺惆惆 悋 忰  悋惘惷 悴 
悋愕惠愆 愕 悒 悖惆悽悋 悋悵 悋悵惘45惘惷悋惓悋
惡悋惠悋11.7%悋惘惷 悴 .
惓悋B. Pie Chart
88.3%
11.7%
FEMALE
MALE
C
C
340
45
45 11.7
340 88.3
385 100.0
GENDER
MALE
FEMALE
Total
Frequency Percent
B. Pie Chart
~ It is circle divided into sectors with
areas proportional to the frequencies
of the categories of the variable.
Lecture two i p

More Related Content

Lecture two i p

  • 1. Data Presenting I Dr Tarekk Alazabee 2012 Qualitative Data: Tabulation. Graphs
  • 2. Learning Objective Identify the different methods of qualitative data presenting.
  • 3. Data Presentation Tables Graphs Mapping 45 11.7 340 88.3 385 100.0 GENDER MALE FEMALE Total Frequency Percent
  • 4. The way in which data presented depends on the type of variable used. 悋惠愃惘悋愕惠惺 惺 惺 惠惺惠惆 悋惡悋悋惠 惺惘惷 愀惘悸 悒
  • 5. i. Tabulation: a. A simple Table. b. Cross-tabulation. ii. Graphs: a. Simple bars. b. Clustered Bars. c. Pie Chart.
  • 7. 悖惆悽385悋愕惠愆悋惠 悒忰惆 悒 悋愕惘 惡悋惆悋悄 惘惷悋 340悗悋悄悋惘惷悒悋惓悋 悋悋愕 悴惺 悋惡惠 88.3%悋惘惷 惺惆惆 悋 忰 悋惘惷 悴 愕悋 悋悵惘45惘惷悋惓悋惡悋惠悋11.7%悴 悋惘惷. 惓悋 悋愀惡:悴惆 悋愕惘 悋惆悋悄 惘惷 惡悴愕 悋惠惺悸 悋惡悋悋惠 惓 a. A simple Table.
  • 8. 悋悒悋惓 惘惷 悋悧悸 悋愕惡悸: 悋悵惘 惘惷 悋悧悸 悋愕惡悸: 340 385 x100=% 88.3 45 385 x100=% 11.7 a. A simple Table.
  • 9. Table (X): The distribution of Gender 45 11.7 340 88.3 385 100.0 GENDER MALE FEMALE Total Frequency Percent Category Category (悋惺 悋惠愃惘) Variable (悋悧悸) (悋惠惘悋惘) (悋悧悸 悋悋愕惡悸) a. A simple Table.
  • 10. The basic rule for displaying qualitative data is to: Classify them into categories. Count the number of observations in each category of the variable. Present the numbers and percentages in the table. Tabulation
  • 11. Cross Tabulation In many situations; it is very useful to present two or more variables at a time in one table QualitativeDatapresentation
  • 12. 惓悋 悋惆惘悋愕悋惠 悒忰惆 悖悽惷惺惠悋惠惆悽 惡惺悋惆悸 悋惠惺悸20愆悽惶悋, 悋惠 悋惠悋悧悴 悋惠悋: -悋惆惘悋愕悸 愆悋惘12 悵惘悋8悒悋惓. -悋惆悽 悒悴悋 悋10悋 悴 悖愆悽悋惶20 愆悋惘悋 -悵惘 惡悋愕惡悸:悋惆悽 惺惆惆 悋812愆悋惘悋. -悒悋惓 惡悋愕惡悸:悋惆悽悋惠 惺惆惆 悋28愆悋惘悋惠. 悋愀惡:悋惠惺悸 悋惡悋悋惠 惓惡惺 悋愆悋惘 惺悋惆悸 悋 悋惆惘悋愕悸悴惆 悋惠惆悽 Cross Tabulation
  • 13. 悵惘 惡悋愕惡悸: 悋惆悽 愃惘 悋悧悸 悋愕惡悸= 悋惆悽 悵惘 悋悧悸 悋愕惡悸: 悒悋惓 惡悋愕惡悸: 悋惆悽悋惠 愃惘 悋悧悸 悋愕惡悸= 惆悽悋惠 悋悧悸 悋愕惡悸= 12 4x100=% 33.3 8 12 x100=% 66.7 x 8 6 = 100% 75.0 8 2x100% 25.0 = 悋悧悸 悋愕惡 忰愕悋惡惺悋惠惆悽 惺悋惆悸 悋 悋愆惠惘 Cross Tabulation
  • 14. 4 6 10 33.3% 75.0% 50.0% 8 2 10 66.7% 25.0% 50.0% 12 8 20 100.0% 100.0% 100.0% Frequency % Frequency % Frequency % Smoking NO YES Total Male Female Sex Total 悋惠愃惘(Variable) 悋惠愃惘(Variable) Cross Tabulation
  • 16. A. Bars Chart - Simple Bars - Clustered Bars
  • 17. 悖惆悽385悋愕惠愆悋惠 悒忰惆 悒 悋愕惘 惡悋惆悋悄 惘惷悋 340悗悋悄悋惘惷悒悋惓悋 悋悋愕惡惠 悴惺 悋 88.3%悋惘惷 惺惆惆 悋 忰 悋惘惷 悴 悋愕惠愆 愕 悒 悖惆悽悋 悋悵 悋悵惘45惘惷悋惓悋 惡悋惠悋11.7%悋惘惷 悴 . 惓悋 悋愀惡:悋愕惘 悋惆悋悄 惘惷 惡悴愕 悋惠惺悸 悋惡悋悋惠 惓 悋悖惺惆悸 愆 Simple Bars
  • 18. 悋悒悋惓 惘惷 悋悧悸 悋愕惡悸: 悋悵惘 惘惷 悋悧悸 悋愕惡悸: 340 385 x100=% 88.3 45 385 x100=% 11.7 Simple Bars
  • 21. 惓悋 悋惆惘悋愕悋惠 悒忰惆 悖悽惷惺惠悋惠惆悽 惡惺悋惆悸 悋惠惺悸20愆悽惶悋, 悋惠 悋惠悋悧悴 悋惠悋: -悋惆惘悋愕悸 愆悋惘12 悵惘悋8悒悋惓. -悋惆悽 悒悴悋 悋10悋 悴 悖愆悽悋惶20 愆悋惘悋 -悵惘 惡悋愕惡悸:悋惆悽 惺惆惆 悋812愆悋惘悋. -悒悋惓 惡悋愕惡悸:悋惆悽悋惠 惺惆惆 悋28愆悋惘悋惠. 悋愀惡:悋惠惺悸 悋惡悋悋惠 惓惡惺 悋愆悋惘 悖惺惆悸 愆 惺 悋惠惆悽 惺悋惆悸 悋惆惘悋愕悸 Clustered Bars
  • 22. 悵惘 惡悋愕惡悸: 悋惆悽 愃惘 悋悧悸 悋愕惡悸= 悋惆悽 悵惘 悋悧悸 悋愕惡悸: 悒悋惓 惡悋愕惡悸: 悋惆悽悋惠 愃惘 悋悧悸 悋愕惡悸= 惆悽悋惠 悋悧悸 悋愕惡悸= 12 4x100=% 33.3 8 12 x100=% 66.7 x 8 6 = 100% 75.0 8 2x100% 25.0 = Clustered Bars
  • 24. Is most commonly used. Count or percentages of the characteristics in different categories are shown as bars. The Bars are equal in width, and the height of the bars is proportion to frequencies Regarding to bar Chart
  • 26. 悖惆悽385悋愕惠愆悋惠 悒忰惆 悒 悋愕惘 惡悋惆悋悄 惘惷悋 340悗悋悄悋惘惷悒悋惓悋 悋悋愕惡惠 悴惺 悋 88.3%悋惘惷 惺惆惆 悋 忰 悋惘惷 悴 悋愕惠愆 愕 悒 悖惆悽悋 悋悵 悋悵惘45惘惷悋惓悋 惡悋惠悋11.7%悋惘惷 悴 . 惓悋B. Pie Chart
  • 27. 88.3% 11.7% FEMALE MALE C C 340 45 45 11.7 340 88.3 385 100.0 GENDER MALE FEMALE Total Frequency Percent B. Pie Chart
  • 28. ~ It is circle divided into sectors with areas proportional to the frequencies of the categories of the variable.