When conducting research in psychology, you'll find that researchers need to choose a sample based on the population samples the researcher intends to make conclusions/ inferences about. In this explanation, we'll explore the differences between population and samples and understand their purposes in research.
- We will start by learning about sampling psychology population.
- Moving along to learn about sampling psychology populations, you will notice population and sample examples.
- To finish off, we will uncover the difference between population and sample.
Population samples are the people on the planet that the researcher is investigating, freepik.com/gstdioimagen
Population and Sample Examples
In psychological research, you'll encounter two important terms: population and sample.
The population is basically everyone or organism on the planet that the researcher is interested in investigating. Meanwhile, a sample is the group of people who participate in the experiment and whom the researcher collects the data from.
It is next to impossible for a researcher to collect data from the entire population. Therefore, researchers need to recruit a sample representative of the population. When a sample is found to be representative, then the findings of the study can be considered to be generalisable. This means that the inferences made in the research are likely to be applicable to the target population.
As we have mentioned previously, sampling refers to the process of selecting a group which will represent the population for the research project. In psychological research, we will usually look to learn about large groups of people who will share some common characteristics, which is defined as the target population.
- Population: all residents of a nation represent the population.
- Target population: people under the age of 16
- Sample: the study recruited 100 people under the age of 16 across ten countries.
When carrying out research in psychology, researchers need to recruit a sample that is representative of the target population, freepik.com/studiogstock
Sampling Psychology Population
When recruiting participants for research, the researcher needs to consider different types of populations. These will affect the sample recruited.
From the population (humans on the planet), researchers will determine a target population based on the hypothesis/ research question that they are investigating (such as people over the age of 65 with dementia). The researcher may then advertise their research to see who is available to participate in the experiment (this is known as the accessible population). A sampling method, such as a random sample, will be used to recruit a representative sample.
Random Sampling Definition in Psychology
Random sampling is a type of probability sampling where every individual of the entire target population owns an equal chance to be selected. When choosing random sampling, there's a requirement of naming or numbering the target population and potentially using a raffle method to choose and select individuals that will be part of the sample.
Other methods apart from raffles such as number generators, as long as participants have an equal chance to be selected in the study.
Random sampling is considered the best method to select a sample for research from the population of interest. In terms of advantages, any form of sampling bias will be eliminated, considering that your sample represents the target population. On the other hand, the disadvantage of random sampling is that it is hard to achieve due to the time, effort and money spent on this type of sampling method.
If you think about the national lottery, for example, if the population represents everyone who has a lottery ticket, then everyone in the population has an equal chance of winning the prize.
Difference Between Population and Sample Psychology
Population and samples have different uses in research, and the type used is determined by whether it is possible to investigate the entire population or not.
Collecting data from the population
Populations are used when the research questions need data from every single individual part of the population. It is straightforwards to gather data from the entire population when it's of small size, data/ participants are readily available and able to cooperate.
A high school administrator would like to analyse the scores of final exams for all graduating seniors to check for a trend. Considering that they want to apply their results only to graduating seniors in that high school, they can use the entire population dataset.
For larger populations, it is usually challenging to gather data from every single individual. An example is the US government and the US census every ten years. Historically, groups of people with a low income or minorities have been challenging to get in touch with. Therefore, the results have not always been accurate due to a lack of or incomplete responses. In these instances, sampling seems more appropriate to make accurate inferences about the population.
Collecting data from a sample
In the case of a large population, as we mentioned, it is more appropriate to use a sample. Through statistical analyses, the researcher can use sample data to test hypotheses.
A researcher investigating the target population of 200,000 university students in France would need to select a representative sample as it is not practical to study all of these individuals. The researcher may recruit 200 students from three French universities - this sample will complete the tasks of the research project.
Population samples - Key takeaways
- In psychological research, you'll encounter two important terms: population and sample.
- The population is basically everyone or organism on the planet that the researcher is interested in investigating. Meanwhile, a sample is the group of people who participate in the experiment and whom the researcher collects the data from.
- When conducting research, it is important that the sample is representative so that the study's results can be generalised to the target population.
- Random sampling is a type of probability sampling where every individual of the entire target population owns an equal chance to be selected.
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