Sampling refers to taking a representative subsection of the population. Contacting, questioning, and obtaining information from a large population, such as the 370,000 households residing in Antipolo City, is extremely expensive, difficult, and time consuming. A properly designed probability sample, however, provides a reliable means of inferring information about a population without examining every member or element
Example: If you wanted the opinions of an HRM students a probability sample would mean that every HRM students would have an equal chance of participating in the research.
Non-probability sampling comes in various shapes and sizes, but the essence of it is that a bias exists in the group of people you are surveying. Let’s think about it in the context of our fictional color preference survey. If I asked the question to all of my friends, the results are not representative of anything other than the opinion of my friends and, specifically, those friends to whom I decided to send the survey. Another example of non-probability sampling would occur if I were to send you the survey and then ask you to pass the survey onto a friend. This effect, called snowballing, creates a biased sample wherein not everyone has an equal chance of being sampled.
QUOTA - For example, an interviewer may be told to sample 200 females and 300 males between the age of 45 and 60. This means that individuals can put a demand on who they want to sample (targeting).
Determining sample size is a very important issue because samples that are too large may waste time, resources and money, while samples that are too small may lead to inaccurate results. There is no general rule regarding the sample size. However, we can say that the higher the percentage, the higher the validity. It is natural to say that the bigger the population, the lesser percentage of the sample is taken.
N = 1545 n= 1545 E = (.03)2 = .0009 ---------- 1+1545 (.0009) 1545 1545 ------------------ n = ---------------- 1+ 1.3905 2.3905 n= 646
Chapter 4 sampling procedure
Sampling Procedure A.M.Somoray
Two General Types of Sampling:Probability sampling - is taking a sample from the population.• It ensures that there is a possibility for each person in a sample population to be selected
Types of Probability Sampling• Random Sampling – This is similar to lottery method that provides everyone in the population the equal chance to be picked as sample.• Systematic Sampling – This is used if a high density of a population is at stake.
• Stratified Random Sampling - dividing up the population into smaller groups, and randomly sampling from each group.• Cluster Sampling - is similar to stratified sampling because the population to be sampled is subdivided into mutually exclusive groups. However, in cluster sampling the groups are defined so as to maintain the heterogeneity of the population. Example: Female members of Baranggay San Isidro
Non-Probability Sampling• Non-probability sampling represents a group of sampling techniques that help researchers to select units from a population that they are interested in studying. Collectively, these units form the sample that the researcher studies
Types of Non-Probability SamplingNetwork sampling – “referral sampling” that stems from one or few identified samples who after being involved in the study will lead the researcher to other samples who possess the same attributes.“word of mouth" approach of acquiring participants.
• Accidental Sampling - A sampling by opportunity in which the researcher takes the respondents from those he meets unexpectedly.• Purposive Sampling – “Judgmental sampling”. A deliberate selection of individuals by the researcher based on predefined criteria
• Convenience Sampling – Selecting respondents in the easiest way. The respondents may be the nearest people, friends, relatives, accessible organization, available person.• Quota Sampling - A sampling method of gathering representative data from a group.
Determining the Sampling Size Slovin formula n = N 1+N(e)2Where:n=no.of sampleN= no. populatione = margin of error**The margin of error may be .01 to .05. But the lower the margin of error, the higher the accuracy of the result.
Activity:Let’s say, you want to get a sample population of all HRM students. 1st yr. – 440 2nd yr. – 400 3rd yr. – 330 4th yr – 275 Irregular – 100Margin or error is 3%
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