Population And Samples In Educational, Psichology, Social And Scientific Research

Population And Samples Research

Populations

A population is a group of people who have one or more characteristics and are of interest to the researcher. As described below, there are several ways to configure a population depending on the characteristics of interest.

The main objective of this study is to find principles that can be applied universally, but examining the entire population to arrive at generalizations would be impractical, if not impossible. The population is defined as a group of people who have at least one common characteristic that differentiates this group from others. For example, we may want to examine people with learning difficulties.

It are a large population and the people in it differ in many other characteristics such as age, level of education, etc. Therefore, it is not possible to study this population because of its size and not very useful because of its diversity.

To solve this second problem, which is too diverse, we need to narrow the population and perhaps only study third graders with learning disabilities who also, attend the large public school system. This will generate a target audience consisting of a specific group for which we want to summarize the results.

journalpapers.org To solve other size problems, we will select a sample which we will study. The process of moving from a large general population to a target population to a sample is common in educational research.

 Sampling

The sample is a fraction of the population selected for observation and analysis. By considering the characteristics of the sample, certain conclusions can be drawn about the characteristics of the population from which the sample comes. The observed results in the sample can also be derived for possible changes in the population (using the statistics described in Chapter 11).

Contrary to popular belief, the samples are not randomly selected. Instead, they are selected systematically at random to take advantage of odds or probability operations. If random selection is not possible, other systematic means are used.

The concept of sampling is discussed in more detail in Chapter 6, which discusses threats to external validity and summarizes. Currently, we are concentrating on sampling.

Randomness

The concept of chance is very important for scientific observation and research. This is based on the assumption that although individual events cannot be predicted accurately, combined events can. For example, although a person's academic performance may not be predicted accurately, it accurately predicts a group's average academic performance.

Randomization has two important applications in research:

  1. Select a group of observers who represent the population that the researcher wants to group, or
  2. The equation of the test group and the control group in one test. Designating people with a random distribution (everyone in the sample has an equal and independent chance of being assigned to each group) is the best way to ensure their equality.

It is important to note that random samples are not necessarily identical representations of the population. The characteristics of consecutive random samples from the same population may differ to some extent, but it is possible to assess deviations from population characteristics and from one another.

These changes, known as experimental failures, do not mean that the sampling process failed. In contrast, sampling error refers to the random variations that occur during the sample. With randomization, these variations can be predicted and accounted for in data analysis techniques.

The topic of sampling error is discussed in more detail in Chapter 11 when the center boundary theorem, mean standard error, and level of significance are discussed.

 The Simple Random Sample

Individual or individual observations are selected so that everyone has an equal and independent opportunity to be selected. If the researcher wants to interview 50 people out of 600 students at a school, they can enter 600 names into the container and draw the names blindfolded until a sample of 50 is selected. This procedure is complicated and rarely used. Rather, it is a more general table of random numbers or a computer-generated list.

 Random Numbers

An easier way to select a random sample or assign people to trial and control groups so that they are equated is to use a random number table. Many such tables are created by computers that produce any sequence of numbers. Rand Corporation (1965) and Fisher and Yates (1963) statistical tables from the Rand Corporation (1965) and Fisher and Yates (1963) statistical tables, one million random numbers with 100,000 normal deviations are widely used in biology, agriculture, and medical research.

When tables are used, sequence numbers must be assigned to each member of the population from which the sample will be selected. By entering a table on any page, row, or column, the researcher can select a sample from 001 to 999, three digits and from 0001 to

9999, four digits. If a duplicate number or a number greater than the population size is found, it is skipped and the process continues until the desired sample size is selected.

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