Unit 6: The Normal Distribution - Practice Quiz

1 What is the general shape of a normal curve?

2 In a perfectly normal distribution, where is the highest point of the curve?

3 What does NPC commonly stand for in statistics?

4 Which statement describes the symmetry of a normal probability curve?

5 In a normal distribution, the mean, median, and mode are:

6 What happens to the normal curve as it extends farther from the mean?

7 What is the total area under a normal probability curve?

8 A normal curve can be used as a model for which type of distribution?

9 According to the Central Limit Theorem, the sampling distribution of a mean tends to become approximately normal when:

10 What does a sampling distribution describe?

11 What does skewness describe?

12 A distribution with a longer tail toward higher scores is called:

13 A distribution with a longer tail toward lower scores is called:

14 What is the skewness of a perfectly symmetric normal distribution?

15 What does kurtosis describe?

16 A distribution that is more peaked than the normal curve is called:

17 A distribution that is flatter than the normal curve is called:

18 A distribution with kurtosis similar to the normal curve is called:

19 Approximately what percentage of scores in a normal distribution lies within one standard deviation of the mean?

20 Which measure indicates how spread out scores are around the mean?

21 A distribution has a mean of 50 and a standard deviation of 8. In a perfectly normal distribution, what is the relationship among the mean, median, and mode?

22 In a normal distribution with and , which score is located one standard deviation above the mean?

23 Why does the total area under a normal curve equal ?

24 A score of indicates that a score is:

25 A test score of comes from a distribution with and . What is the score's -value?

26 Approximately what proportion of observations in a normal distribution lies between and ?

27 For a normal probability curve, what proportion of the area lies above the mean?

28 Which statement best describes the tails of a normal probability curve?

29 A normal distribution has and . Approximately what percentage of scores falls between and ?

30 According to the central limit theorem, the sampling distribution of the mean tends to become approximately normal when:

31 A population has . What is the standard error of the mean for samples of size ?

32 If the sample size increases from to while population variability remains constant, what happens to the standard error of the mean?

33 A population has mean and standard deviation . For samples of size , what is the mean and standard error of the sampling distribution of sample means?

34 A sample mean has a -score of . What does this indicate about the sample mean?

35 A distribution has a long tail extending toward higher scores, while most scores cluster at the lower end. What type of skewness does it show?

36 In a positively skewed distribution, which ordering is generally expected among the mean, median, and mode?

37 A researcher finds that a few unusually low scores are pulling the distribution's mean below its median. Which type of skewness is most likely present?

38 A distribution is more sharply peaked and has heavier tails than a normal distribution. How is it classified?

39 Which description best fits a platykurtic distribution?

40 A distribution has kurtosis similar to that of the normal distribution. Which label is appropriate?

41 A continuous distribution is perfectly symmetric about its mean, but its tails are substantially heavier than those of a normal distribution. Which conclusion is most defensible?

42 For a truly normal variable , which transformation preserves normality while changing the mean and standard deviation?

43 A normal distribution has mean and standard deviation . Which interval contains approximately the central of observations under the empirical rule?

44 A population has mean and standard deviation . For samples of size , what is the approximate probability that the sample mean exceeds , assuming the normal model applies?

45 Which statement best explains why the normal curve can model the sampling distribution of a mean even when the population itself is not normal?

46 A heavily right-skewed population is sampled with . Which inference about the sampling distribution of is most appropriate?

47 If sample size increases from to while population variability remains unchanged, how does the standard error of the mean change?

48 A score of comes from a distribution with mean and standard deviation . What is its standard score, and how should it be interpreted?

49 Two normal distributions have different means but identical standard deviations. For a fixed raw-score distance above each mean, which statement is correct?

50 For a standard normal variable , which expression is equivalent to ?

51 A distribution has mean , median , and mode . Which description is most consistent with these values?

52 A researcher log-transforms a strongly right-skewed reaction-time variable and obtains a distribution that is nearly symmetric. What has most likely occurred?

53 Which pattern would most strongly suggest negative skewness in a psychological test-score distribution?

54 A distribution has skewness close to zero, but a histogram shows two equally sized peaks located symmetrically around the center. Which conclusion is best?

55 Relative to a normal distribution, a leptokurtic distribution is generally characterized by which combination?

56 A software package reports excess kurtosis of . What is the appropriate classification relative to the normal distribution?

57 Which statement correctly distinguishes skewness from kurtosis?

58 Which property of the normal probability curve explains why the probability of observing exactly one specified value is zero in the continuous model?

59 A normal curve is transformed from raw scores to -scores. Which feature changes under this transformation?

60 Why does the normal probability curve never actually touch the horizontal axis, even though its height becomes extremely small in the tails?