STRAIGHTER LINE STATISTICS
CORRECT 100%
The histogram below displays the distribution of 50 ages at death due to trauma
(accidents and homicides) that were observed in a certain hospital during a week.
What percentage of deaths were individuals younger than 35? - ANSWER 68%
From the histogram we can find that 3 + 18 + 13 = 34 out of the 50 observations fall
below age 35 (those within the first three bars), and since the question asks about the
percentage of observations, the answer is (34/50) * 100 = 68%.
Here again is the histogram showing the distribution of 50 ages at death due to trauma
(accidents and homicides) that were observed in a certain hospital during a week.
Which of the following best describes the shape of the histogram? - ANSWER Right-
skewed with a possible outlier
The histogram displays a tail to the right (i.e., it is skewed right) with one isolated
observation at around 90 years, which is possibly an outlier.
Here again is the histogram showing the distribution of 50 ages at death due to trauma
(accidents and homicides) that were observed in a certain hospital during a week.
Assume that the largest observation in this dataset is 90. If this observation were
wrongly recorded as 900, then: - ANSWER The mean will increase, but the median
won't change.
The mean will increase, because the mean tends to be pulled by an outlier. So moving
the largest value, 90, farther to the right, to 900, would tend to pull the mean to the right,
making it larger. The median wouldn't be affected, because moving 90 to 900 wouldn't
change the 25th or the 26th value in the data.
The following data, on the number of children ever born per 1,000 women, are from the
Current Population Reports - Fertility of American Women: 2008
For the data described by the above histogram, - ANSWER (B) the median will be
smaller than the mean
Remember that we'd expect the mean and the median to be nearly the same only if the
distribution were nearly symmetric. But notice this distribution is skewed to the right (the
tail is towards the right) and we also see a suspected outlier on the right side.
Remember that both of these shape features will tend to pull the mean more than they
would pull the median.
CORRECT 100%
The histogram below displays the distribution of 50 ages at death due to trauma
(accidents and homicides) that were observed in a certain hospital during a week.
What percentage of deaths were individuals younger than 35? - ANSWER 68%
From the histogram we can find that 3 + 18 + 13 = 34 out of the 50 observations fall
below age 35 (those within the first three bars), and since the question asks about the
percentage of observations, the answer is (34/50) * 100 = 68%.
Here again is the histogram showing the distribution of 50 ages at death due to trauma
(accidents and homicides) that were observed in a certain hospital during a week.
Which of the following best describes the shape of the histogram? - ANSWER Right-
skewed with a possible outlier
The histogram displays a tail to the right (i.e., it is skewed right) with one isolated
observation at around 90 years, which is possibly an outlier.
Here again is the histogram showing the distribution of 50 ages at death due to trauma
(accidents and homicides) that were observed in a certain hospital during a week.
Assume that the largest observation in this dataset is 90. If this observation were
wrongly recorded as 900, then: - ANSWER The mean will increase, but the median
won't change.
The mean will increase, because the mean tends to be pulled by an outlier. So moving
the largest value, 90, farther to the right, to 900, would tend to pull the mean to the right,
making it larger. The median wouldn't be affected, because moving 90 to 900 wouldn't
change the 25th or the 26th value in the data.
The following data, on the number of children ever born per 1,000 women, are from the
Current Population Reports - Fertility of American Women: 2008
For the data described by the above histogram, - ANSWER (B) the median will be
smaller than the mean
Remember that we'd expect the mean and the median to be nearly the same only if the
distribution were nearly symmetric. But notice this distribution is skewed to the right (the
tail is towards the right) and we also see a suspected outlier on the right side.
Remember that both of these shape features will tend to pull the mean more than they
would pull the median.
