Biased sample
sample.
Population
A sample must be both random and sufficiently large to accurately represent a population. Randomness ensures that every individual in the population has an equal chance of being selected, minimizing bias. A sufficiently large sample size helps to capture the diversity and variability within the population, leading to more reliable and generalizable results.
differences between quantitative and qualitative data
Selecting individuals at random- *apex
You are studying the sample because you want to find out information about the whole population. If the sample you have drawn from the population does not represent the population, you will find out about the sample but will not find out about the population.
sample
at random to represent the population
A small number of people used to represent an entire population is called a sample. Typically the sample reflects characteristics of the larger population from which it is drawn.
A biased sample is a sample that is not random. A biased sample will skew the research because the sample does not represent the population.
A biased sample is a sample that is not random. A biased sample will skew the research because the sample does not represent the population.
The sample must be large and random.
A sample must be representative, meaning that it reflects the characteristics of the population it is drawn from. It must also be large enough to minimize sampling error and increase the likelihood of capturing the population's diversity.
a sample
Bias
sample.
The use of a small number of people to represent a greater population is called sampling. The sample can be randomly chosen so that it is a reliable reflection of most of the population.