<p> Chapter 6 iClicker Questions</p><p>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.</p><p>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.</p><p>3. 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.</p><p>4. When transforming raw scores into z scores, the formula to which we refer is:</p><p> a) (μ – X) Z= Σ</p><p> b) (X – μ) Z= σ</p><p> c) (∑ – X) Z= Σ</p><p> d) (X – σ) Z= S 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? a) -2.6 b) 1.6 c) -2.3 d) 1.3</p><p>6. The mean of a z distribution is always: a) 1. b) 0. c) 10. d) 100.</p><p>7. A normal distribution of standardized scores is called the: a) standard normal distribution. b) null distribution. c) z distribution. d) sample distribution.</p><p>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.</p><p>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) The distribution of means is more spread out. </p><p>10. The standard deviation of a distribution of means is called the: a) standard score. b) standard error. c) central limit theorem. d) normal curve. 11. In chapter 6 of your textbook, the authors give examples of how the normal curve can be used 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.</p>