1. What is the difference between a sample and a population in statistics?
- A sample is the entire group being studied, while a population is a subset of that group.
- A population is the entire group being studied, while a sample is a subset of that grouop.
- A sample is the entire group being studied, while a population is a subset of a sample.
2. Which of the following statements best describes the law of large numbers?
- The law of large numbers states that as the smaple size increases, the sample mean becomes more variable.
- The law of large numbers states that as the smaple size increases, the sample mean approaches the population mean with increasing accuracy.
- The law of large numbers states that as the smaple size increases, the sample variance approaches the population variance.
- The law of large numbers states that as the smaple size increases, the sample becomes more biased.
3. Which of the following best describes the central limit theorem?
- The central limit theorem states that the mean of a population is always normally distributed.
- The central limit theorem states that as the sample size increases, the sample mean approaches the population mean.
- The central limit theorem states that as the sample size increases, the sampling distribution of the mean approaches a normal distribution, regardless of the distribution of the population.
- The central limit theorem states that as the sample size increases, the variance of the population decreases.