Normal Distribution Characteristics
The content includes review questions on normal distribution characteristics, skewness, kurtosis, Z-scores, and detecting non-normality using various graphs. It covers topics like symmetry, bimodality, bell shape, mean-median-mode relationship, skewness, kurtosis, Z-score calculation, and normalization. The questions aim to test understanding of these key statistical concepts.
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Unit 4 Quiz: Review questions
Can you explain your answer? Use your fingers to indicate your answer: 1=A, 2=B, 3=C, 4=D. After viewing the question, show me your answer in 15 seconds. Next, turn to your neighbor and you have one minute to convince him/her that you are right.
Which of the following is NOT a characteristic of a normal curve? A. symmetrical B. bimodal C. bell-shaped D. the mean, median, and mode are the same.
Which of the following statement is true? A.Kurtosis refers to the degree of asymmetry in the distribution. B. Skewness is the relative ratio of the mass of the distribution located in the center versus in the tails. C.The kurtosis of the normal distribution is 1. D.The normal distribution is symmetrical and hence has zero skewness.
Which of the following graph can NOT be used for detecting non- normality? A. Normal quantile plot B. Q-Q plot C. Pie chart D. Histogram
Which of the following statements is false? A. Z scores not only give the distance of the score from the mean in standard deviation units, but also the direction of the score from the mean by using the sign of the Z score (+ or -). B. The mean of a set of Z scores is 0 and the variance and standard deviation of a set of Z scores are 1. C. Normality is a theoretical construct. In many cases it is assumed, not really observed. D. Transforming raw scores to z scores can normalize the distribution.
In a test the mean is 60 and the standard deviation is 10. The test score of Jay Walker is 50. What is his z score? A. -1 B. +1 C. 0 D. -2
