Explain.

Question 3 10 pts 3. Consider a skewed right distribution. Which of these best describes the shape of the sampling distribution when n = 5? There is no way to predict the shape without conducting a simulation Skewed right, but less severe than the population from which the samples were taken. Skewed right, but more severe than the population from which the samples were taken. Approximately normal due to the Central Limit Theorem. Uniform because the Central Limit Theorem does not apply until n > 30. Question 4 10 pts 4. Consider a skewed right distribution. Which of these best describes the shape of the sampling distribution when n = 100? There is no way to predict the shape without conducting a simulation Skewed right, but less severe than the population from which the samples were taken. Skewed right, but more severe than the population from which the samples were taken. Approximately normal due to the Central Limit Theorem. Uniform because of the Central Limit Theorem