STATISTICAL METHODS IN PSYCHOLOGY
Sampling and Population
You will often hear psychologists talking about samples and populations in relation to statistical analysis of research. What do they mean by these terms? A population is a set of people, things or events that we are interested in because we wish to draw some conclusion about them. The population could consist of all people, or all people with schizophrenia, or all right-handed people, or even just a single person. A sample is a set selected from the population of interest and used to make an inference about the population as a whole. This kind of inference is called a generalization. [generalization related to the concept of external validity, this is the process of making statements about the general population on the basis of research] A sample would normally be a group of people selected from a larger group, but it could also be a sample of behaviour from one person, or even a sample of neurons from a region of the brain (see chapter 3). If we wish to generalize to a population, we need to make sure that the sample is truly representative of the population as a whole. This means that the sample should be similar to the population in terms of relevant characteristics. For example, if we are doing research on the human visual system, then members of our sample group need to have eyesight that is similar to the rest of the human population (as opposed to being, for example, noticeably worse). The easiest and fastest way to achieve this is to draw a random sample (of a reasonable size) from the population [random sample a sample of participants in which each has the same chance of being included, ensured by using random participant selection methods (e.g. drawing lots)].
Sampling and Population
You will often hear psychologists talking about samples and populations in relation to statistical analysis of research. What do they mean by these terms? A population is a set of people, things or events that we are interested in because we wish to draw some conclusion about them. The population could consist of all people, or all people with schizophrenia, or all right-handed people, or even just a single person. A sample is a set selected from the population of interest and used to make an inference about the population as a whole. This kind of inference is called a generalization. [generalization related to the concept of external validity, this is the process of making statements about the general population on the basis of research] A sample would normally be a group of people selected from a larger group, but it could also be a sample of behaviour from one person, or even a sample of neurons from a region of the brain (see chapter 3). If we wish to generalize to a population, we need to make sure that the sample is truly representative of the population as a whole. This means that the sample should be similar to the population in terms of relevant characteristics. For example, if we are doing research on the human visual system, then members of our sample group need to have eyesight that is similar to the rest of the human population (as opposed to being, for example, noticeably worse). The easiest and fastest way to achieve this is to draw a random sample (of a reasonable size) from the population [random sample a sample of participants in which each has the same chance of being included, ensured by using random participant selection methods (e.g. drawing lots)].
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