At the United Nations Millennium Summit 2000, world leaders agreed to work together to achieve eight development goals by 2015. These goals included eradicating extreme poverty and hunger, achieving universal primary education, promoting gender equality, reducing child mortality, and combating diseases. "We will have time to reach the Millennium Development Goals... but only if we break with business as usual.... Success will require sustained action.... It takes time to train the teachers, nurses and engineers; to build the roads, schools and hospitals; to grow the small and large businesses able to create the jobs and income needed. So we must start now. And we must more than double global development assistance over the next few years. Nothing less will help to achieve the Goals." -Kofi Annan, former UN Secretary-General, June 7, 2000. According to Kofi Annan, how can the goals be achieved?

During new product development, companies often involve “lead users,” i.e., creative individuals who are on the leading edge of an important market trend. Creativity and Innovation Management (Feb. 2008) published an article on identifying the social network characteristics of lead users of children’s computer games. Data were collected for n = 326 children and the following variables measured: lead-user rating ( y , measured on a 5-point scale), gender (

$$x _ { 1 } = 1$$

if female, 0 if male), age

$$\left( x _ { 2 } , \text { years } \right)$$

degree of centrality (

$$x _ { 3 }$$

, measured as the number of direct ties to other peers in the network), and betweenness centrality (

$$x_4$$

, measured as the number of shortest paths between peers). A first-order model for y was fit to the data, yielding the following least squares prediction equation:

$$\hat { y } = 3.58 + .01 x _ { 1 } - .06 x _ { 2 } - .01 x _ { 3 } + .42 x _ { 4 }$$

Give a practical interpretation of the estimate of

$$\beta _ { 4 }$$

in the model.

Tris (hydroxymethyl)aminomethane, commonly called TRIS or Trizma, is often used as a buffer in biochemical studies. Its buffering range is from pH 7 to $9 ,$ and $K _ { b }$ is $1.19 \times 10 ^ { - 6 }$ for the reaction

$$\begin{array} {l}{{\left( \mathrm { HOCH } _ { 2 } \right) _ { 3 } \mathrm { CNH } _ { 2 } ( a q ) + \mathrm { H } _ { 2 } \mathrm { O } ( l ) \rightleftharpoons \left( \mathrm { HOCH } _ { 2 } \right) _ { 3 } \mathrm { CNH } _ { 3 } ^ { + } ( a q ) + \mathrm { OH } ^ { - } ( a q )} \\\quad {\text{TRIS}\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \text{TRISH}^+}} \end{array}$$

A buffer is prepared by diluting 50.0 g of TRIS base and 65.0 g of TRIS hydrochloride (written as TRISHCl to a total volume of 2.0 L. What is the pH of this buffer? What is the pH after 0.50 mL of 12 M HCl is added to a 200.0-mL portion of the buffer?

The article “Human Lateralization from Head to Foot: Sex-Related Factors” (Science, 1978: 1291–1292) reports for both a sample of right-handed men and a sample of right-handed women the number of individuals whose feet were the same size, had a bigger left than right foot (a difference of half a shoe size or more), or had a bigger right than left foot.

$$\begin{array}{|c|c|c|c|c|} \hline & & & & \text { Sample } \\ & \mathbf{L}>\mathbf{R} & \mathbf{L}=\mathbf{R} & \mathbf{L}<\mathbf{R} & \text { Size } \\ \hline \text { Men } & 2 & 10 & 28 & 40 \\ \hline \text { Women } & 55 & 18 & 14 & 87 \\ \hline \end{array}$$

Does the data indicate that gender has a strong effect on the development of foot asymmetry? State the appropriate null and alternative hypotheses, compute the value of $\chi^{2}$, and obtain information about the P-value.

Construct the indicated stemplot from the data in Table. Then write a brief interpretation of the stemplot. Life Expectancy by Gender for 12 Nations of South America.

$$\begin{matrix} \text{Nation} & \text{Male} & \text{Female}\\ \text{Argentina} & \text{72.5} & \text{79.1}\\ \text{Bolivia} & \text{65.1} & \text{69.2}\\ \text{Brazil} & \text{71.0} & \text{77.8}\\ \text{Chile} & \text{76.2} & \text{82.3}\\ \text{Colombia} & \text{74.5} & \text{80.5}\\ \text{Ecuador} & \text{73.2} & \text{78.8}\\ \text{Guyana} & \text{60.0} & \text{67.0}\\ \text{Paraguay} & \text{71.7} & \text{77.6}\\ \text{Peru} & \text{75.1} & \text{78.3}\\ \text{Suriname} & \text{69.4} & \text{75.5}\\ \text{Uruguay} & \text{73.0} & \text{80.0}\\ \text{Venezuela} & \text{72.0} & \text{79.3}\\ \end{matrix}$$

A back-to-back stemplot for life expectancies of males and females in the nations of South America (Round to nearest year and use split stems.)

A realtor wants to sell some riverfront lots. To set a fair price for them, he studies several similar riverfront lots nearby that were sold recently. The table shows the area of the lots (in hundreds of square feet) and their selling prices (in thousands of dollars).

$$\begin{matrix} \text{Square Footage} & \text{Price}\\ \text{189} & \text{240}\\ \text{232} & \text{260}\\ \text{172} & \text{230}\\ \text{195} & \text{230}\\ \text{240} & \text{280}\\ \text{210} & \text{260}\\ \text{200} & \text{240}\\ \text{230} & \text{250}\\ \text{191} & \text{241}\\ \text{198} & \text{255}\\ \end{matrix}$$

a. Create a scatter plot for the data. Does it appear to have a linear trend? b. The coefficient of determination for the data is found to be equal to $r^2 = 0.673.$ Explain what that means in terms of association of the price of the lot and its area. c. Calculate a regression line for the data.

Construct the indicated stemplot from the data in Table. Then write a brief interpretation of the stemplot. Life Expectancy by Gender for 12 Nations of South America.

$$\begin{matrix} \text{Nation} & \text{Male} & \text{Female}\\ \text{Argentina} & \text{72.5} & \text{79.1}\\ \text{Bolivia} & \text{65.1} & \text{69.2}\\ \text{Brazil} & \text{71.0} & \text{77.8}\\ \text{Chile} & \text{76.2} & \text{82.3}\\ \text{Colombia} & \text{74.5} & \text{80.5}\\ \text{Ecuador} & \text{73.2} & \text{78.8}\\ \text{Guyana} & \text{60.0} & \text{67.0}\\ \text{Paraguay} & \text{71.7} & \text{77.6}\\ \text{Peru} & \text{75.1} & \text{78.3}\\ \text{Suriname} & \text{69.4} & \text{75.5}\\ \text{Uruguay} & \text{73.0} & \text{80.0}\\ \text{Venezuela} & \text{72.0} & \text{79.3}\\ \end{matrix}$$

A stemplot showing the difference between female and male life expectancies in the nations of South America (Use unrounded data and do not split stems.)

At a recent football game you noticed that students tend to be near the same height as their parent of the same gender. You surveyed several students and their parents and recorded the data below.

$$\begin{matrix} \text{Student's Height (in.)} & \text{Parent's Height (in.)}\\ \text{61} & \text{56}\\ \text{62} & \text{57}\\ \text{63} & \text{62}\\ \text{65} & \text{66}\\ \text{65} & \text{60}\\ \text{66} & \text{66}\\ \text{67} & \text{68}\\ \text{68} & \text{63}\\ \text{68} & \text{69}\\ \text{70} & \text{71}\\ \text{72} & \text{68}\\ \text{71} & \text{73}\\ \text{73} & \text{67}\\ \text{74} & \text{71}\\ \end{matrix}$$

Tyler's father came to pick him up and you asked his height. He is 6 feet tall. What is his residual and where does the data point lie in relation to the best-fit line?

Use the document to answer the following questions. At the United Nations Millennium Summit in 2000, world leaders agreed to work together to achieve eight development goals by 2015. These goals included eradicating extreme poverty and hunger, achieving universal primary education, promoting gender equality reducing child mortality, and combating diseases. We will have time to reach the Millennium Development Goals... but only if we break with business as usual. Success will require sustained action it takes time to tram the teachers, nurses and engineers; to build the roads, schools and hospitals; to grow the small and large businesses able to create the jobs and income needed. So we must start now. And we must more than double global development assistance over the next few years. Nothing less will help to achieve the Goals.” —Kofi Annan, former UN Secretary-General. June 7, 2005. According to Kofi Annan, how can the goals be achieved?

The table shows the distribution, by age and gender, of the $29.3$ million Americans who live alone. Use the data in the table to solve the exercise.

$$\begin{array}{l} \text{NUMBER OF PEOPLE IN THE UNITED STATES}\\ \text{ LIVING ALONE, IN MILLIONS}\\ \begin{array}{|l|c|c|c|c|c|c|c|} \hline & \text{Ages 15 - 24} & \text{Ages 25 - 34} & \text{Ages 35 - 44} & \text{Ages 45 - 64} & \text{Ages 65 - 74} & \text{Ages $\ge$ 75} & \text{Total}\\ \hline \text{Male} & 0.7 & 2.2 & 2.6 & 4.3 & 1.3 & 1.4 & 12.5\\ \hline \text{Female} & 0.8 & 1.6 & 1.6 & 5.0 & 2.9 & 4.9 & 16.8\\ \hline \text{Total} & 1.5 & 3.8 & 4.2 & 9.3 & 4.2 & 6.3 & 29.3\\ \hline \end{array} \end{array}$$

Find the probability, expressed as a decimal rounded to the nearest hundredth, that a randomly selected American living alone is in the $25-34$ age range.

In the article "Bigger Teeth for Longer Life? Longevity and Molar Height in Two Roe Deer Populations", researchers developed a model to predict the tooth height (in mm),y, of roe deer based on their age, $x_1$, gender, $x_2$(0=female, 1=male), and location, $x_3$ (Trois Fontaines deer, which have a shorter life expectancy, and Chaize, which have a longer life expectancy, $x_3$=0 for Trois Fontaines, $x_3$=1 for (Chize). The model is $\hat{y}=7.790-0.382 x_{1}-0.587 x_{2}-0.925 x_{3}+0.091 x_{2} x_{3}$. (a) What is the expected tooth length of a female roe deet who is 12 years old and lives in Trois Fontaines? (b) What is the expected tooth length of a male roe deer who is 8 years old and Lives in Chize? (c) What is the interaction term? What does the coefficient of the interaction term imply about tooth length?

On February 28, 2013, a Field Poll Survey reported that $61 \%$ of California registered voters approved of allowing two people of the same gender to marry and have regular marriage laws apply to them. Among 18 to 39-year-olds (California registered voters), the approval rating was $78 \%$. Six in ten California registered voters said that the upcoming Supreme Court's ruling about the constitutionality of California's Proposition 8 was either very or somewhat important to them. Out of those CA registered voters who support same-sex marriage, $75 \%$ say the ruling is important to them.

In this problem, let's:

• $C=$ California registered voters who support same-sex marriage.

• $B$ = California registered voters who say the Supreme Court's ruling about the constitutionality of California's Proposition 8 is very or somewhat important to them

• $A=$ California registered voters who are 18 to 39 years old.

Are $C$ and $B$ mutually exclusive events? Show why or why not.

Many observational studies conclude that low-fat diets protect against cancer and cardiovascular "events" (heart attacks, stroke, and so forth). Experimental results, however, are generally negative. In 2006, the Women's Health Initiative (WHI) published its results. This was a large-scale randomized trial on women who had reached menopause. As one part of the study, 48,835 women were randomized: 19,541 were assigned to the treatment group and put on a low-fat diet. The other 29,294 women were assigned to the control group and ate as they normally would. Subjects were followed for 8 years. Among other things, the investigators found that 1,357 women on the low-fat diet experienced at least one cardiovascular event, compared to 2,088 in the control group. can the difference between the two groups be explained by chance? What do you conclude about the effect of the low-fat diet?

As mentioned in Exercise 4.52, a July 21 survey on www.HuffingtonPost.com asked people to choose their favorite junk food from a list of choices. Considering that there were 4801 female respondents and 3201 male respondents, even though the findings were not broken down by gender, let's assume that the following table represents the results for the 8002 respondents.

$$\begin{array}{lcc} \hline \text { Favorite Junk Food } & \text { Female } & \text { Male } \\ \hline \text { Chocolate } & 1518 & 531 \\ \text { Sugary candy } & 218 & 127 \\ \text { Ice cream } & 685 & 586 \\ \text { Fast food } & 312 & 463 \\ \text { Cookies } & 431 & 219 \\ \text { Chips } & 458 & 649 \\ \text { Cake } & 387 & 103 \\ \text { Pizza } & 792 & 523 \\ \hline \end{array}$$

Let's say that one respondent is chosen at random from this sample of 8002 people. Identify the probabilities for each. a. The likelihood that a feminine event will involve chocolate. b. Probability of the union of events male and cake.