Sample and Sampling Techniques PDF

# Sample and Sampling Techniques ## The Population - Consists of the totality or aggregate of the observations with which the researcher is concerned. - Population is an accessible group of people who meets a well-defined set of eligibility criteria. - The utmost importance in selecting a populatio...

# Sample and Sampling Techniques ## The Population - Consists of the totality or aggregate of the observations with which the researcher is concerned. - Population is an accessible group of people who meets a well-defined set of eligibility criteria. - The utmost importance in selecting a population is that "the population should be clearly defined so that the sample can be accurately identified." - The Specific Population types are: - **Target population**: is a group of individuals who meets the criteria. - **Subject or respondent population**: refers to a group of individuals participating in the study. - **Strata or stratum**: is described as a mutually exclusive segment of a population established by one or more characteristics. ## The Sampling - **Sample**: subset of the population that is selected for a study - Also called subjects or respondents of the study. - **Sampling**: Process of choosing a representative portion of the entire population. - an integral part of research methodology. - involves selecting a group of people, events, behaviors, or other elements with which to conduct a study. - **Element**: most basic unit about which information is collected. - **Representativeness**: means that the sample must be like the population in as many ways as possible. - The accessible population must be representative of the target population. - **Example of a sample**: The population of BSN students is 600, only 200 BSN students are included as the target population, and only 100 students are chosen as samples for the actual study. ## Eligibility Criteria - A description chosen by the researcher to define which elements should be included in or excluded from the population. - Such criteria may include sex, age, marital status, education level, and diagnosis. ## Sampling Theory - is developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. - Key concepts of sampling theory includes: - **Sampling unit**: refers to a specific place or location which can be used during the sampling process. - **Sampling frame**: describes the complete list of sampling units from which the sample is drawn. ## Sampling Criteria - refers to the essential characteristics of a subject or respondent such as ability to read and write responses on the data collection instruments. ## The steps involved in sampling include: - Identify the target population. - Identify the subject or respondent population. - Specify the criteria for subject or respondent selection. - Specify the sampling design. - Recruit the subjects. ## Sample Size - Prior to the selection of sampling technique, the nurse-researcher must first determine the size of the sample. - A sample size can be determined using the Slovin's (1960) formula, which is as follows: $n = \frac{N}{1 + Ne^2}$. Where: - n is the sample size - N is the population size - e is the margin of error - 1 is a constant value - **Example**: From the population of 10,000 clients with tuberculosis, a nurse-researcher selected a sample size with a margin of error of 5%. The desired sample size is computed to be 385. ## Types of Sampling Techniques - two basic sampling techniques used in nursing research: - **probability (random) sampling** - **nonprobability (nonrandom) sampling** - **SAMPLING TECHNIQUES** - **NON-PROBABILITY** - CONVENIENCE - QUOTA - *PURPOSIVE* - **PROBABILITY** - SIMPLE RANDOM - SYSTEMATIC - STRATIFIED - CLUSTER - MULTI-STAGE ## Probability Sampling - Involves the selection of elements from the population using random in which each element of the population has an equal and independent chance of being chosen. ## Four Classification of Probability Sampling ### 1. Simple Random Sampling - Each member of the population has an equal chance of being included in the samples. - Most commonly used method is the **lottery or Fish Bowl technique**. - In using the lottery method, there is a need for a complete listing of the members of the population. - The names or codes of all members are written on pieces of paper cards and placed in a container. - The researcher draws the desired number of samples from the container. - The process is relatively easy for a small population but relatively difficult and time-consuming for a large population. ### 2. Systematic Sampling Technique - Type of probability sampling which selects samples by following some rules set by the researcher which involves selecting the Kth member where the random start is determined. - A system is a plan for selecting members after a starting point or random start has been determined. - Then every nth member of the population will be determined by the system in drawing or selecting the members of the sample. ### 3. Stratified Random Sampling - Type of probability sampling which selects members of the sample proportionally from each subpopulation or stratum. - Used when the population is too large to handle and is divided into subgroups (called strata). - Samples per stratum are then randomly selected, but considerations must be given to the sizes of the random samples to be drawn from the subgroups. - An example of a procedure to use is proportional allocation which selects the sample sizes proportional to the sizes of the different subgroups. ### 4. Cluster Sampling - Used when the population is divided into groups or clusters. - Samples are selected in groups rather than individuals which is employed into a large-scale survey. ### 5. Multi-Stage Sampling - Selects samples using more than two sampling techniques. - Rarely used because of the complexity of its application. - Requires a lot of effort, time, and cost. ## 2. Non-Probability Sampling - Involves the selection of elements from a population using nonrandom procedures. - Characteristics of Non-Probability Sampling: - The members of the sample are drawn or selected based on the judgment of the researcher. - The results of these techniques are relatively biased. - The techniques lack objectivity in terms of the selection of samples. - The samples are not so reliable. - The techniques are convenient and economical to use. ## Types of Non-Probability Sampling ### 1. Convenience or Accidental Sampling - Involves a nonrandom selection of subjects based on their availability or convenient accessibility. ### 2. Quota Sampling - Involves a nonrandom selection of elements based on the identification of specific characteristics to increase the sample's representativeness. ### 3. Purposive of Judgmental Sampling - Involves a nonrandom selection of elements based on the researcher's judgment and knowledge about the population. - This is useful when a group of subjects is needed to participate in a pretest of newly developed instruments or when a group of experts is desirable to validate research information.