Random Samples

What is a random sample?

• A subset of individuals chosen from a larger population, where each individual has an equal chance of being selected.

• A group of individuals selected based on specific characteristics or criteria.

• A sample that is selected randomly but does not represent the larger population.

• A collection of data points gathered from a single individual.

How can you ensure a sample is random?

• Using a random number generator to select participants.

• Choosing participants based on their availability.

• Selecting participants who volunteer for the study.

• Drawing names from a hat to select participants.

What is stratified sampling?

• A method where the population is divided into subgroups and random samples are taken from each stratum.

• A sampling method that selects individuals based on their characteristics without randomization.

• A technique that involves surveying the entire population without any subgroup division.

• A method that uses only one subgroup to represent the entire population.

Why might a convenience sample lead to inaccurate results?

• It is usually faster and cheaper to conduct.

• It may not represent the diversity of the entire population.

• It allows for easier data collection.

• It is often used in qualitative research.

How can surveys be biased?

• Through leading questions, non-random sampling, or if certain groups are overrepresented or underrepresented.

• By ensuring all participants are randomly selected and representative of the population.

• By asking open-ended questions that allow for diverse responses.

• Through the use of neutral language in questions.

What does it mean if a sample is biased?

• A biased sample is one that accurately represents the population.

• A biased sample is one that does not accurately represent the population, leading to skewed or invalid results.

• A biased sample is one that includes only a small number of participants.

• A biased sample is one that is randomly selected from the population.

What is the difference between a sample and a population?

• A sample is the entire group being studied, while a population is a smaller group selected from that sample.

• A population is the entire group being studied, while a sample is a smaller group selected from that population.

• A sample includes all members of a population, while a population includes only a few members.

• A population is a random selection of individuals, while a sample is a systematic selection of individuals.

What is a statistic?

• A statistic is a numerical value that summarizes a characteristic of a sample.

• A statistic is a graphical representation of data.

• A statistic is a method for collecting data.

• A statistic is a type of mathematical equation.

What is sampling error?

• The difference between the results obtained from a sample and the actual values in the population.

• The process of selecting a representative group from a population.

• The error that occurs when a sample is too small to represent the population accurately.

• The variation in data that occurs due to random chance.

Why is it important for a sample to be representative of the population?

• A representative sample ensures that the results of a survey or study can be generalized to the entire population, making the findings more valid.

• A representative sample is necessary to ensure that the sample size is large enough to draw conclusions.

• A representative sample helps to reduce the cost of conducting surveys and studies.

• A representative sample allows researchers to focus on a specific subgroup of the population.