1 1 pts A distribution of sample means is a collection of sample means from samples of different sizes from different populations. samples of size N from different populations. samples of size N from the same population. samples of different sizes from the same population Question 2 1 pts A friend of mine studies the effects of praise on happiness. She believes that children who receive praise are happier overall than children who do not receive praise. She measures happiness by counting the number of times a child smiles in a one hour period. She knows that in the population of children who do not receive praise smiles average 4 times per hour with a standard deviation of .5, and that these data are normally distributed. She selects a sample of 100 children whom she knows receive praise and finds that they smile an average of 3.5 times per hour. The characteristics of the appropriate comparison (sampling) distribution are a mean of zero and a standard deviation of 1. a mean of 4 and a standard deviation of .5. a mean of 4 and a standard deviation of .05. a mean of 3.5 and a standard deviation of .5. Question 3 1 pts The normal approximation to the binomial distribution is most useful for finding which of the following? The probability P(X = 5) when X is a binomial random variable with large n The probability P(X 5) when X is a binomial random variable with large n. The probability P(X = 5) when X is a normal random variable with small n The probability P(X 5) when X is a normal random variable with small n Question 4 1 pts The central limit theorem tells us that the sampling distribution of the sample mean is approximately normal. Which of the following conditions are necessary for the theorem to be valid: a) The sample size has to be large. b) We have to be sampling from a normal population. c) The population has to be symmetric. d) Both a) and c). Question 5 1 pts The Central Limit Theorem is important in statistics because a) for a large sample size n, it says the population is approximately normal b) for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size. c) for a large sample size n, it says the sampling distribution of the sample mean is approximately normal, regardless of the shape of the population d) both a) and c).above. Question 6 1 pts The standard error of the proportion p will become larger as p approaches 0. as p approaches .50. as p approaches 1.00. as n increases. Question 7 1 pts Since the sample size is always smaller than the size of the population, the sample mean must always be smaller than the population mean must be larger than the population mean must be equal to the population mean can be smaller, larger, or equal to the population mean Question 8 1 pts A simple random sample from an infinite population is a sample selected such that each element is selected independently and from the same population each element has a 0.5 probability of being selected each element has a probability of at least 0.5 of being selected the probability of being selected changes Question 9 1 pts If we consider the simple random sampling process as an experiment, the sample mean is always zero always smaller than the population mean a random variable exactly equal to the population mean Question 10 1 pts As the sample size becomes larger, the sampling distribution of sample mean approaches a binomial distribution either binomial distribution or normal distribution normal distribution none of the above