> Use simple random sampling to select observations from a sampling frame To use the sampling tool, select a data set where each row in the data set is unique (i.e., no duplicates). A dataset that fits these requirements is bundled with Radiant and is available through the _Data > Manage_ tab (i.e., choose `Examples` from the `Load data of type` drop-down and press `Load`). Select `rndnames` from the `Datasets` dropdown. `Names` is a unique identifier in this dataset. If we select this variable and choose the desired sample size, e.g., 10, list of names of the desired length will be created. How does this work? Each person in the data is assigned a random number between 0 and 1 from a uniform distribution. Rows are then sorted on that random number and the $n$ people from the list with the highest score are selected for the sample. By using a random number, every respondent has the same probability of being in the sample. For example, if we need a sample of 10 people from the 100 included in the `rndnames` dataset, each individual has a 10% chances of being included in the sample. By default, the random seed is set to `1234` to ensure the sampling results are reproducible. If there is no input in `Rnd. seed`, the selected rows will change every time we generate a sample.
