Lesson: Random Sampling
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Definition of Terms
Population – The entire group you
want to study – Sample portion The of the population you select to study either by Random or
Non-random Sampling Techniques
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Random Sampling? 4
Random Sampling
-a selection of elements derived from a population , which is the subject of investigation where each sample point has equal chance of being selected.
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Types of Random Sampling 6
Types of Random Sampling ▰
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1. Lottery Sampling (Simple Random) 2. Systematic Sampling 3. Stratified Random Sampling 4. Cluster Sampling (Area Sampling) 5. Multi-stage Sampling
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1. Lottery Sampling (Simple Random) ▰
is a method of probability sampling in which every unit or member of the population has an equal non zero chance of being selected for the sample. 8
1. Lottery Sampling (Simple Random)
Methods of selecting random sample: ▰
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Lottery Method Tables of Random Numbers
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Example
Suppose, we have 500 units in population and we wish to select 50 units out of them. So assign the numbers 1 to 500 units of population. Prepare slips bearing numbers 1 to 500. The slips should be homogeneous in shape,, size, colour shape colour etc. These These slips slips are shuffled shuffled and put in box. 50 slips are selected. The units with the numbers on the slips selected will constitute a random
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sample.
2. Systematic Sampling ▰
sampling technique in which members of the population are listed and samples are selected in intervals called sample intervals.
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In this technique, every element from the list is selected from a randomly selected starting point.
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2. Systematic Sampling ▰
For example, if we wish to draw a sample of 2,000 from a population of 6,000, we can select every 3rd person in the list. In practice, numbers between 1 and 30 will
be randomly selected to act as the starting point.
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3. Stratified Random Sampling ▰
- sam sampli pling ng proce procedure dure wher wherein ein the the members of the population are grouped based on their homogeneity. This technique is used when there are a number of distinct subgroups in the population, within each of which is required that there is full representation.
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3. Stratified Random Sampling ▰
The sample is constructed by classifying the population into subpopulations or strata, based some characteristics of the population such as on as age, gender, or socio-economic status. The selection of elements is then made separately from within each stratum, usually by random or systematic sampling methods.
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3. Stratified Random Sampling
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Example
Select a sample of 387 students from the population which are grouped according to the cities they come from. The table below shows the 17
number of students per city.
3. Stratified Random Sampling
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4. Cluster Sampling (Area Sampling) ▰
It is applied on a geographical basis. It is generally done by first sampling at the higher levels before going down to lower levels. E.g. samples taken from
provinces, cities, municipalities or
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barangay, then household.
4. Cluster Sampling (Area Sampling)
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5. Multi-stage Sampling ▰
Done using a combination of different sampling techniques. 22
5. Multi-stage Sampling ▰
For instance, when selecting respondents for a national election survey, we can make use of lottery method first for regions and cities. Then we utilize stratified sampling to determine the number for respondents from chosen areas and clusters
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the
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Checking your understanding
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Activity
Identify what type of Random sampling technique are the following: 1. DepEd’s survey on drug use in high schools used ▰
2 stagefollowed sampling sampling forthose geographic areas, by: Cluster high schools within areas,
followed by lottery sampling senior students in those schools.
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Activity
2. 2,000 respondents nationwide, from regions down to barangays, are
selected for a national election survey. 3. Every five files out of 500 files will
be chosen.
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Activity
4. 10 names of students were picked out from a box containing 1,000 names written
in rolled papers. 5. Selected vehicles are Classified according to the last number of their
plates as odd or even.
Let us check!
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Activity
1. Multi-stage Sampling 2. Cluster Sampling or Are Sampling 3. Systematic Sampling 4. Lottery or Simple Random Sampling
5. Stratified Random Sampling
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