The document discusses concepts related to data, samples, and populations in research. It aims to help students understand and distinguish between these key terms. Specifically, it defines data as measurements, counts or observations; population as the total collection of similar elements; and sample as a subset of a population. The document also outlines different types of data, sampling techniques, and methods for data collection including questionnaires and interviews.

1. DATA, SAMPLE,
POPULATION
Sugama Maskar,
M.PMat.
FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

2. GOALS
1.Students can understand about
data, sample, and population;
2.Students can distinguish about
data, sample, and population;
FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

3. DATA
Measurment,
counting, or
observation result.
FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

4. GOOD DATA REQUIREMENT
1.Objective (based on fact);
2.Reflect (reflect of the
object that observed);
3.Minimize of sampling
error;
4.Up to date.FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

5. TYPE OF DATA
Quantitative data
Ex.
•I have 3 motorcycle (discrete);
•Distance from Bandung to
Jakarta is 60 km (continuous).
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6. TYPE DATA
Qualitative Data
Ex.
1.That poetry is good;
2.The price of that novel is
expensive.
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7. OTHERS
Internal Data
External Data
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8. OTHERS
Primary Data
Secondary Data
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9. OTHERS
Cross section Data
Time Series Data
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10. POPULATION
Colletion of all similar
elements
The elements can be distinguished
based on its characteristics
Ex. Female or male, age,
educational level, genre, etc.
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11. SAMPLE
A subsets of
population
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12. SAMPLE
http://keydifferences.com/wp-content/uploads/2016/04/census-vs-sample.jpg
FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

13. QUESTION
Why we use
sample?
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14. POPULATION AND SAMPLE
http://www.six-sigma-material.com/images/PopSamples.GIF
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15. RESEARCH CYCLE
http://images.slideplayer.com/13/3999595/slides/slide_4.jpg
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16. SAMPLING
How to collect sample
data?
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17. SAMPLING ADVANTAGES
1.Cheaper;
2.Faster;
3.Easier;
4.Can be generalized.
FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

18. SAMPLING TYPES
Random Sample
http://images.slideplayer.com/13/3999595/slides/slide_4.jpg
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19. RANDOM SAMPLING
Every element have same
chances to selected.
more Objective, Neutral,
equal chance.
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20. NON RANDOM SAMPLING
Every element have not
same chances to
selected.
more Subjective, not
Neutral, not equal
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21. RANDOM SAMPLING TYPES
1.Simple Random Sampling;
2.Proportionate Stratified Random
Sampling;
3.Area Sampling;
4.Cluster Random Sampling;
5.Systematic Random Sampling.
FAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

22. SIMPLE RANDOM SAMPLING
Collete data sample without
see level of data.
Can be used when the data is
homogeneous.
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23. PROPORTIONATE STRATIFIED
RANDOM SAMPLING
Random with seeing
level of data
propotionally
Can be used when the data is
heterogeneous
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24. AREA SAMPLING;
take a representative from each
region
𝑋𝑖1,𝑖2,𝑖3,…
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25. CLUSTER RANDOM SAMPLING
Sample with Sample
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26. SYSTEMATIC RANDOM SAMPLING
1.Get 𝑘,
𝑘=Population/sample;
2.Choose number from 1 to
k;
3.Choose data from 1st dataFAKULTAS SASTRA DAN ILMU PENDIDIKAN– UNIVERSITAS TEKNOKRAT INDONESIA

27. METHODS AND INSTRUMENTS OF
DATA COLLECTION
1.Questionnaire;
2.Interview;
3.Observation;
4.Test;
5.Documentation.
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28. SAMPLE QUESTIONNAIRE
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29. SAMPLE QUESTIONNAIRE
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