Data
Why Collect Data?
Obtain input to a research study (Memperoleh
suatu masukan tentang penelitian)
 Measure performance (mendapatkan
performance)
 Assist in formulating decision alternatives
(Membantu merumuskan alternatif keputusan)
 Satisfy curiosity (Menjawab tentang keraguan)


Knowledge for the sake of knowledge (mendapatkan
suatu pengetahuan yang baru)
Data Types
Data
Numerical
Categorical
(Quantitative)
(Qualitative)
Discrete
Continuous
Data Type Examples

Numerical
 Discrete
 To
how many magazines do you subscribe
currently? ___ (Number)
 Continuous
 How

tall are you? ___ (Inches)
Categorical
 Do
you own savings bonds? __ Yes __ No
How Are Data Measured?
(Pengukuran data)

Nominal scale




Categories
 e.g., Male-female
Count
Ordinal scale


Categories
Ordering implied
 e.g., High-low

Count

Skala nominal hanya
bisa membedakan
sesuatu yang bersifat
kualitatif (misalnya:
jenis kelamin, agama,
warna kulit).
Skala ordinal selain
membedakan juga
menunjukkan tingkatan
(misalnya: pendidikan,
tingkat kepuasan).
How Are Data Measured?

Interval scale





Equal intervals
No true 0
e.g., Degrees Celsius
Measurement
Ratio scale




Equal intervals
True 0
Meaningful ratios
e.g., Height in inches
Skala interval berupa
angka kuantitatif
namun tidak memiliki
nilai nol mutlak
(misalnya: tahun,
suhu dalam Celcius).
 Sedangkan skala
rasio berupa angka
kuantitatif yang memiliki nilai nol mutlak

Data Sources
Data Sources
Data
Sources
Data Sources
Data
Sources
Primary
Data Sources
Data
Sources
Primary
Secondary
Data Sources
Data
Sources
Primary
Experiment
Secondary
Data Sources
Data
Sources
Primary
Experiment
Survey
Secondary
Data Sources
Data
Sources
Primary
Experiment
Survey
Secondary
Observation
Data Sources
Data
Sources
Primary
Experiment
Survey
Secondary
Observation
Published
(& On-Line)
Surveys
Survey Steps
Define purpose
 Design questionnaire
 Select sample design

Sample type
 Sample size

Survey Steps

Define purpose

Design
questionnaire

Select sample
design


Sample type
Sample size
Collect data
(field work)
 Prepare data



Edit
Code
Analyze data
 Interpret findings
 Report results

Questionnaire Design






Question content
Mode of response
Question wording
Question sequence
Layout
Pilot testing
© 1984-1994 T/Maker Co.
Samples
Why Sample?
Destruction of test
units
 Quality control
 Accurate &
reliable results
 Pragmatic reasons
 Time
 Cost

Types of Samples
Types of Samples
Type of
Sample
Types of Samples
Type of
Sample
Non
Probability
Types of Samples
Type of
Sample
Non
Probability
Probability
Types of Samples
Type of
Sample
Non
Probability
Judgment
Probability
Types of Samples
Type of
Sample
Non
Probability
Judgment
Quota
Probability
Types of Samples
Type of
Sample
Non
Probability
Judgment
Quota
Probability
Chunk
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Cluster
Simple Random Sample
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Cluster
Simple
Random Sample
Each population element
has an equal chance of
being selected
 Selecting 1 subject does not
affect selecting others
 May use random number
table, lottery, ‘fish bowl’

© 1984-1994
T/Maker Co.
Random Number Table
Column
Row
00000
12345
00001
67890
11111
12345
11111
67890
01
49280
88924
35779
00283
02
61870
41657
07468
08612
03
43898
65923
25078
86129
Systematic Sample
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Cluster
Systematic Sample
Every kth element Is
selected after a random
start within the first k
elements
 Skip interval, k, is
Population size
Sample size


Used in telephone
surveys
© 1984-1994 T/Maker Co.
Stratified Sample
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Cluster
Stratified Sample

Divide population into
subgroups




Mutually exclusive
Exhaustive
At least 1 common
characteristic of interest
All Students
Commuter
s
Residents
Select simple random
samples from subgroups
Sample
Cluster Sample
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Cluster
Cluster Sample

Divide population
into clusters

If managers
are elements then
companies are clusters
Select clusters randomly
 Survey all or a random
sample of elements in
cluster

Companies (Clusters)
Sample
Nonprobability Samples
Types of Samples
Type of
Sample
Non
Probability
Probability
Simple
Random
Judgment
Quota
Chunk
Systematic
Stratified
Cluster
Nonprobability Samples

Judgment
 Use
experience to select sample
 Example: Test markets

Quota
 Similar
to stratified sampling except no
random sampling

Chunk (convenience)
 Use
elements most available
Errors Due to Sampling
Errors Due to Sampling
Total Population
(Students)
Errors Due to Sampling
Total Population
(Students)
Sample Frame
(Students in
Phone Book)
Errors Due to Sampling
Coverage (Frame) Error
Total Population
(Students)
Sample Frame
(Students in
Phone Book)
Errors Due to Sampling
Coverage (Frame) Error
Total Population
(Students)
Sample Frame
(Students in
Phone Book)
Planned Sample
(Selected Students)
Errors Due to Sampling
Coverage (Frame) Error
Sampling Error
Total Population
(Students)
Sample Frame
(Students in
Phone Book)
Planned Sample
(Selected Students)
Errors Due to Sampling
Coverage (Frame) Error
Sampling Error
Total Population
(Students)
Sample Frame
(Students in
Phone Book)
Planned Sample
(Selected Students)
Actual
Sample
Errors Due to Sampling
Coverage (Frame) Error
Sampling Error
Nonresponse &
Measurement Error
Total Population
(Students)
Sample Frame
(Students in
Phone Book)
Planned Sample
(Selected Students)
Actual
Sample
Conclusion
Defined statistics
 Distinguished descriptive & inferential
statistics
 Summarized the sources of data
 Described the types of data & scales
 Explained the types of samples
 Described survey process & errors

This Class...
Please take a moment to answer the
following questions in writing:
What was the most important thing you
learned in class today?
 What do you still have questions about?
 How can today’s class be improved?

End of Chapter
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