Not if they are all members of the same team!
That is known as a simple random sample, or SRS.
A simple random sample is a method of selecting a sample where the probability of any particular member of the population being part of the sample is the same for all members of the population.
at random to represent the population
A random sample is a sample (subset of the population) where each member of the population has an equal chance of being sampled. See related links.
Random assignment: assigning participants to experimental and control conditions by chance Vs. Random sample: a sample that fairly represents a population because each member has an equal chance of being included You decide :-D
A random sample should be taken from an entire population.
A larger random sample will always give a better estimate of a population parameter than a smaller random sample.
To determine if a sample accurately represents a population, you can evaluate its size, randomness, and diversity. A larger sample size generally increases reliability, while random sampling helps minimize bias. Additionally, assessing whether the sample reflects key characteristics of the population, such as demographics and relevant traits, is crucial. Statistical tests can also be employed to analyze the representativeness of the sample compared to the population.
Sometimes a population consists of a number of subsets (strata) such that members within any particular strata are alike while difference between strata are more than simply random variations. In such a case, the population can be split up into strata. Then a stratified random sample consists of simple random samples, with the same sampling proportion, taken within each stratum.
A synonym for "random sample" is "probability sample," as both refer to a selection method that ensures each member of a population has an equal chance of being chosen. An antonym could be "non-random sample" or "biased sample," which indicates a selection process that does not provide equal opportunity for all members of the population. These terms highlight the contrast between systematic, unbiased selection and arbitrary or selective methods.
In statistics it is a random sample
random sample or probability sample