The data in the scatterplot below are an individual's age (in years) and the expected life span (in years). The circles correspond to females and the x's to males. Which of the following conclusions is most accurate? There is a positive correlation between gender and life expectancy. There is a negative correlation between gender and life expectancy. There is a positive correlation between age and life expectancy for both males and females. There is a negative correlation between age and life expectancy for both males and females.

The data in the scatterplot below are an individual's weight and the time it takes (in seconds) on a treadmill to raise his or her pulse rate to 140 beats per minute. The o's correspond to females and the +'s to males. Which of the following conclusions is most accurate? There is a negative correlation between time and weight for males and for females. There is a positive correlation between time and weight for males and for females. There is a positive correlation between gender and weight. There is a negative correlation between gender and weight.

Now return to the scatterplot that you created earlier. Notice that there is an outlier in both longevity (40 years) and gestation (645 days). Note: This outlier corresponds to the longevity and gestation period of the elephant.What do you think will happen to the correlation if we remove this outlier?To do this in R, copy the following command:cor(a$longevity[a$animal!="elephant"],a$gestation[a$animal!="elephant"])Notice that the correlation between gestation and longevity has changed.Report the new value for the correlation between gestation and longevity and compare it to the value you found earlier when the outlier was included. What is it about this outlier that results in the fact that its inclusion in the data causes the correlation to increase? (Hint: look at the scatterplot.)

Which of the following provides one of the valid explanations for gender differences in life expectancy?Group of answer choicesMost researchers focus on the possibility that the X chromosome and female hormones protect women against health problems.Women live longer because they are much less likely to be overweight.Women actually experience about half as many serious illnesses as men do.Women visit their health-care providers more often than men do.

Jacob wants to see if there is a relationship between the speed of a male runner and his age. He collected the age and race time from 27 male runners in a local 200 meter race. His data is depicted in the scatterplot below.Which of the following interpretations does this scatterplot best support?Group of answer choicesThe decreasing exponential trendline is the best choice for this data because older men's running times are exponentially shorter than younger men's times.There is no relationship between men's ages and their running times in the 200 meter race.A linear trendline with a negative slope is the best choice for this data because older men's running times are shorter than younger men's times.The quadratic trendline is the best choice for this data because from Jacob's scatterplot it looks like men around 40 have the slowest running time (the vertex). Men both younger and older than 40 are faster than 40 year olds.A linear trendline with a positive slope is the best choice for this data because older men's running times are longer than younger men's times.

In order to study whether there is a relationship between gender and age at marriage, 50 couples were randomly selected and the age of the bride and groom were recorded.Which of the following would be a meaningful display of the data from this study? A histogram A pie chart Side-by-side boxplots A scatterplot A two-way table