For Exercise 1.70, see page 40; for 1.71 to 1.73, see pages 41-42; for 1.74 to 1.77, see pages 44-45; for 1.78, see page 46; for 1.79 and 1.80, see page 49; for 1.81 and 1.82, see page 50; and for 1.83 and 1.84, see page 53.
1.85 Find the error.
Each of the following statements contains an error. Describe the error and then correct the statement.
1.85
(a) A density curve is a mathematical model for the distribution of a quantitative variable. (b) The area under the curve for a density curve is always equal to 1. (c) If a variable can take only negative values, then the density curve for its distribution will still lie entirely above the axis.
1.86 Find the error.
Each of the following statements contains an error. Describe the error and then correct the statement.
1.87 Sketch some Normal curves.
1.87
(c) The curve shifts to the left or right, but the spread remains the same.
1.88 The effect of changing the standard deviation.
1.89 Know your density.
Sketch density curves that might describe distributions with the following shapes.
1.90 Gross domestic product.
Refer to Exercise 1.46, where we examined the gross domestic product of 189 countries.
gdp
1.91 Do women talk more?
Conventional wisdom suggests that women are more talkative than men. One study designed to examine this stereotype collected data on the speech of 42 women and 37 men in the United States.30
1.91
(a) According to the rule, 68% of women speak between 5232 and 23,362 words per day, 95% of women speak between -3833 and 32,427 words per day, and 99.7% of women speak between -12,898 and 41,492 words per day. (b) This rule doesn—t seem to fit because you can—t speak a negative amount of words per day; therefore, the percentages don—t make sense. (c) According to the rule, 68% of men speak between 5004 and 23,116 words per day, 95% of men speak between -4052 and 32,172 words per day, and 99.7% of men speak between -13,108 and 41,228 words per day. Similar to the women, the rule doesn—t seem to fit because, again, you can—t speak a negative amount of words per day, so the percentages don—t make sense. (d) The data do show that the mean number of words spoken per day is higher for women than for men, but it is very close; in addition, the standard deviations are nearly the same, making the intervals very close. To put it in perspective, the women only speak about 1-2% more words per day on average. That small of a difference could just be due to chance.
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1.92 Data from Mexico.
Refer to the previous exercise. A similar study in Mexico was conducted with 31 women and 20 men. The women averaged 14,704 words per day with a standard deviation of 6215. For men, the mean was 15,022 and the standard deviation was 7864.
1.93 Total scores for accounting course.
Following are the total scores of 10 students in an accounting course:
acct
62 | 93 | 54 | 76 | 73 | 98 | 64 | 55 | 80 | 71 |
Previous experience with this course suggests that these scores should come from a distribution that is approximately Normal with mean 72 and standard deviation 10.
1.93
(a) The standardized values are: -1, 2.1, -1.8, 0.4, 0.1, 2.6, -0.8, -1.7, 0.8, -0.1. (b) 85 percentile ? . (c) Only two scores, the 93 and the 98.
1.94 Assign more grades.
acct
Refer to the previous exercise. The grading policy says that the cutoffs for the other grades correspond to the following: the bottom 5% receive an F, the next 15% receive a D, the next 35% receive a C, and the next 30% receive a B. These cutoffs are based on the distribution.
1.95 Visualizing the standard deviation.
Figure 1.34 shows two Normal curves, both with mean 0. Approximately what is the standard deviation of each of these curves?
1.95
The wider curve has a standard deviation of about 0.4. The narrower curve has a standard deviation about 0.2.
1.96 Exploring Normal quantile plots.
1.97 Length of pregnancies.
The length of human pregnancies from conception to birth varies according to a distribution that is approximately Normal with mean 266 days and standard deviation 16 days. Use the 68-95-99.7 rule to answer the following questions.
1.97
(a) 95% of pregnancies last between 234 and 298 days. (b) The shortest pregnancies are 234 days or less.
1.98 Uniform random numbers.
Use software to generate 100 observations from the distribution described in Exercise 1.72 (page 41). (The software will probably call this a “uniform distribution.”) Make a histogram of these observations. How does the histogram compare with the density curve in Figure 1.20? Make a Normal quantile plot of your data. According to this plot, how does the uniform distribution deviate from Normality?
1.99 Use Table A or software.
Use Table A or software to find the proportion of observations from a standard Normal distribution that falls in each of the following regions. In each case, sketch a standard Normal curve and shade the area representing the region.
1.99
(a) 0.0179. (b) 0.9821. (c) 0.0548. (d) 0.9273.
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1.100 Use Table A or software.
Use Table A or software to find the value of for each of the following situations. In each case, sketch a standard Normal curve and shade the area representing the region.
1.101 Use Table A or software.
Consider a Normal distribution with mean 200 and standard deviation 20.
1.101
(a) Between -0.5 and 1. 0.5328. (b) corresponds with the 12.5 percentile . corresponds with the 87.5 percentile . Solving gives .
1.102 Length of pregnancies.
The length of human pregnancies from conception to birth varies according to a distribution that is approximately Normal with mean 266 days and standard deviation 16 days.
1.103 Quartiles of Normal distributions.
The median of any Normal distribution is the same as its mean. We can use Normal calculations to find the quartiles for Normal distributions.
1.103
(a) The area to the left of the first quartile is 25%. The corresponding is -0.67. The area to the left of the third quartile is 75%. The corresponding is 0.67. (b) For the first quartile, . For the third quartile, .
1.104 Deciles of Normal distributions.
The deciles of any distribution are the 10th, 20th, . . . , 90th percentiles. The first and last deciles are the 10th and 90th percentiles, respectively.
1.105 Normal random numbers.
Use software to generate 100 observations from the standard Normal distribution. Make a histogram of these observations. How does the shape of the histogram compare with a Normal density curve? Make a Normal quantile plot of the data. Does the plot suggest any important deviations from Normality? (Repeating this exercise several times is a good way to become familiar with how Normal quantile plots look when data are actually close to Normal.)
1.105
(a) For those who get enough sleep, 56.8% are high exercisers and 43.2% are low exercisers. (b) For those who don't get enough sleep, 37.9% are high exercisers and 62.1% are low exercisers. (c) Those who get enough sleep are more likely to be high exercisers than those who don't get enough sleep.
1.106 Trade balance.
bestbus
Refer to Exercise 1.49 (page 35) where you examined the distribution of trade balance for 145 countries in the best countries for business data set. Generate a histogram and a normal quantile plot for these data. Describe the shape of the distribution and whether or not the normal quantile plot suggests that this distribution is Normal.
1.107 Gross domestic product per capita.
Refer to the previous exercise. The data set also contains the gross domestic product per capita calculated by dividing the gross domestic produce by the size of the population for each country.
bestbus
1.107
(b) The distribution is right-skewed; this is also shown in the Normal quantile plot.