Population and Sample
Population refers to the total population of individuals or things that exhibit the characteristic(s) of research interest. For example, if a researcher is interested in determining the average height of all humans globally, the population would consist of all humans.
A sample refers to a smaller section of the population chosen to participate in research. The goal of selecting a sample is to collect information that may be utilized to conclude the wider population. In the height example, measuring the height of every person on the planet may not be practicable or practical. So, the researcher would choose a smaller sample of individuals to measure and then use statistical techniques to estimate the height of the total population. The estimate’s precision depends on the sample’s representativeness, which necessitates that the sample reflects the characteristics of the wider population.
Simplifying a mathematical equation is another example of simplification. For example, if you had the phrase (2x + 4) + (3x — 1), you might simplify it by combining related terms to produce 5x + 3. Another example of simplification is simplifying a mathematical expression. For instance, if you had the expression (2x + 4) + (3x — 1), you could simplify it by combining like terms to get 5x + 3.
There are several methods that can be used to extract a sample from a population. Here are a few examples:
1. Simple random sampling — This involves selecting individuals from the population at random, with each individual having an equal chance of being selected. This method is often used when the population is homogeneous, and the goal is to get a representative sample.
2. Stratified sampling — This involves dividing the population into subgroups based on specific characteristics, and then selecting a sample from each subgroup. This method is often used when the population is heterogeneous, and the goal is to ensure that each subgroup is represented proportionally in the sample.
3. Cluster sampling — This involves selecting groups or clusters of individuals from the population, and then selecting a sample from within each cluster. This method is often used when the population is geographically dispersed, and it is more efficient to sample clusters rather than individuals.
4. Systematic sampling — This involves selecting individuals from the population at regular intervals. For example, if the population size is 1000 and the sample size is 100, then every 10th individual is selected. This method can be useful when the population is too large to use simple random sampling, but a representative sample is still needed.
5. Convenience sampling — This involves selecting individuals from the population who are easily accessible or available. This method is often used in situations where it is difficult or impractical to use other sampling methods, but it may result in a biased sample.
Observation unit
An observation unit is the entity or object that is being observed or measured in a study. It can be an individual, group, or object, depending on the research question and the design of the study.
For example, in a study on the effectiveness of a new medication, the observation unit might be individual patients. In a study on the academic performance of schools, the observation unit might be schools. In a study on the nutritional value of different foods, the observation unit might be individual food items. The choice of observation unit is important in defining the scope and relevance of the study, and it can affect the type of statistical analysis that is used to interpret the results. The observation unit should be carefully selected to ensure that it is appropriate for the research question and that it accurately reflects the phenomenon being studied.
