Statistics for the Behavioral Sciences Susan A. Nolan and Thomas E. Heinzen Statistics for the Behavioral Sciences Second Edition Chapter 6: The Normal Curve, Standardization, and z Scores iClicker Questions Copyright © 2012 by Worth Publishers

Chapter 6 1. All of the following are true of the normal curve EXCEPT: a) it is bell-shaped. b) it is unimodal. c) it has an inverted U shape. d) it is symmetric.

Chapter 6 (Answer) All of the following are true of the normal curve EXCEPT: a) it is bell-shaped. b) it is unimodal. c) it has an inverted U shape. d) it is symmetric.

Chapter 6 2. A normal distribution of scores will more closely resemble a normal curve as: a) the sample size increases. b) the sample size decreases. c) more outliers are added to the sample. d) scores are converted to z-scores.

Chapter 6 (Answer) 2. A normal distribution of scores will more closely resemble a normal curve as: a) the sample size increases. b) the sample size decreases. c) more outliers are added to the sample. d) scores are converted to z-scores.

Chapter 6 A z score is defined as the: a) mean score. b) square of the mean score. c) square root of the mean score divided by the mean. d) number of standard deviations a particular score is from the mean.

Chapter 6 (Answer) A z score is defined as the: a) mean score. b) square of the mean score. c) square root of the mean score divided by the mean. d) number of standard deviations a particular score is from the mean.

Chapter 6 When transforming raw scores into z scores, the formula is: a) (μ – X) Z= ___________ Σ b) (X – μ) Z= __________ σ c) (∑ – X)   d) (X – σ) Z= _________ S

Chapter 6 (Answer) When transforming raw scores into z scores, the formula is: a) (μ – X) Z= ___________ Σ b) (X – μ) Z= __________ σ c) (∑ – X)   d) (X – σ) Z= _________ S

Chapter 6 Matthew recently took an IQ test in which he scored an IQ of 120. If the population’s mean IQ is 100 with a standard deviation of 15, what is Matthew’s z score? -2.6 1.6 c) -2.3 d) 1.3

Chapter 6 (Answer) 5. Matthew recently took an IQ test in which he scored an IQ of 120. If the population’s mean IQ is 100 with a standard deviation of 15, what is Matthew’s z score? -2.6 b) 1.6 c) -2.3 d) 1.3

Chapter 6 The mean of a z distribution is always: a) 1. b) 0. c) 10.

Chapter 6 (Answer) The mean of a z distribution is always: a) 1. b) 0.

Chapter 6 A normal distribution of standardized scores is called the: a) standard normal distribution. b) null distribution. c) z distribution. d) sample distribution.

Chapter 6 (Answer) A normal distribution of standardized scores is called the: a) standard normal distribution. b) null distribution. c) z distribution. d) sample distribution.

Chapter 6 The assertion that a distribution of sample means approaches a normal curve as sample size increases is called: a) Bayes theorem. b) the normal curve. c) De Moivre’s theorem. d) the central limit theorem.

Chapter 6 (Answer) 8. The assertion that a distribution of sample means approaches a normal curve as sample size increases is called: a) Bayes theorem. b) the normal curve. c) De Moivre’s theorem. d) the central limit theorem.

Chapter 6 9. How is a distribution of means different from a distribution of raw scores? a) The distribution of means is more tightly packed. b) The distribution of means has a greater standard deviation. c) The distribution of means cannot be plotted on a graph. d) All of the above are true.

Chapter 6 (Answer) How is a distribution of means different from a distribution of raw scores? a) The distribution of means is more tightly packed. b) The distribution of means has a greater standard deviation. c) The distribution of means cannot be plotted on a graph. d) All of the above are true.

Chapter 6 The standard deviation of a distribution of means is called the: a) standard score. b) standard error. c) central limit theorem. d) normal curve.

Chapter 6 (Answer) The standard deviation of a distribution of means is called the: a) standard score. b) standard error. c) central limit theorem. d) normal curve.

Chapter 6 Statisticians can use principles based on the normal curve to: a) catch cheaters. b) encourage people to conform to expected behavior. c) remove unwanted scores from the data set. d) detect confounds in an experiment.

Chapter 6 (Answer) 11. Statisticians can use principles based on the normal curve to: a) catch cheaters. b) encourage people to conform to expected behavior. c) remove unwanted scores from the data set. d) detect confounds in an experiment.