They record the total weight loss of each individual after one month. Then, they use a computer program to randomly assign 50 of the male athletes to a control group and 50 to the treatment group. They recruit 100 males athletes to be in the study. Study: Researchers want to know whether a new diet leads to more weight loss than a standard diet in a certain community of 10,000 people. The internal validity of the study has been compromised because the difference in weight loss could actually just be due to gender, rather than the new diet. By doing this, they’re able to generalize the findings from the study to the overall population but they are not able to attribute any differences in average weight loss between the two groups to the new diet. Instead, they used a specific factor – gender – to decide which group to assign individuals to. Results: The researchers used random selection to obtain their sample, but they did not use random assignment when putting individuals in either a treatment or control group. Females are assigned to the control group and males are assigned to the treatment group. However, they decide to assign individuals to groups based solely on gender. They recruit 100 individuals to be in the study by using a computer to randomly select 100 names from a database. By doing so, they’re able to generalize the findings from the study to the overall population and they’re able to attribute any differences in average weight loss between the two groups to the new diet. Results: The researchers used random selection to obtain their sample and random assignment when putting individuals in either a treatment or control group. stick with their standard diet) and 50 individuals to a treatment group (e.g. Once they have the 100 individuals, they once again use a computer to randomly assign 50 of the individuals to a control group (e.g. Example 1: Using both Random Selection and Random Assignment The following examples show how a study could use both, one, or neither of these techniques, along with the effects of doing so. A strong study is one that uses both techniques. It’s possible for a study to use both random selection and random assignment, or just one of these techniques, or neither technique. Examples of Random Selection and Random Assignment This means the study has internal validity – it’s valid to attribute any differences between the groups to the treatment itself as opposed to differences between the individuals in the groups. For example, if we have 100 individuals in a study then we might use a random number generator to randomly assign 50 individuals to a control group and 50 individuals to a treatment group.īy using random assignment, we increase the chances that the two groups will have roughly similar characteristics, which means that any difference we observe between the two groups can be attributed to the treatment. When a study uses random assignment, it randomly assigns individuals to either a treatment group or a control group. In statistical terms, this is referred to as having external validity – it’s valid to externalize our findings to the overall population. This means that each individual is equally likely to be selected to be part of the study, which increases the chances that we will obtain a representative sample – a sample that has similar characteristics to the overall population.īy using a representative sample in our study, we’re able to generalize the findings of our study to the population. For example, if some population has 1,000 individuals then we might use a computer to randomly select 100 of those individuals from a database. When a study uses random selection, it selects individuals from a population using some random process. The Importance of Random Selection and Random Assignment You can think of random selection as the process you use to “get” the individuals in a study and you can think of random assignment as what you “do” with those individuals once they’re selected to be part of the study. Random assignment refers to the process of randomly assigning the individuals in a study to either a treatment group or a control group. Random selection refers to the process of randomly selecting individuals from a population to be involved in a study. Random selection and random assignment are two techniques in statistics that are commonly used, but are commonly confused.
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