1. The following are the number of children of a sample of women from the USA taken from the 2010 NHANES data set.
\begin{tabular}{lllllllllllll}
2 & 6 & 2 & 1 & 5 & 1 & 1 & 2 & 1 & 1 & 1 & 1 & 2 \\
4 & 3 & 2 & 4 & 3 & 2 & 3 & 1 & 1 & 7 & 3 & 1 & 2 \\
1 & 1 & 2 & 2 & 4 & 5 & 7 & 3 & 1 & 3 & 2 & 1 & 2 \\
5 & 5 & 4 & 3 & 2 & 2 & 2 & 4 & 4 & 3 & 2 & 3 & 3
\end{tabular}
a. [2] Use your calculator to construct a histogram and boxplot (showing outliers) for this data set. Make sure the class limits for your histogram are whole numbers.

Step 1 ：Organize the data in ascending order. This will make it easier to identify the minimum, maximum, median, and quartiles for the boxplot.

Step 2 ：To construct a histogram, determine the range of the data (maximum - minimum), decide on the number of classes (or bins), and then calculate the class width. The class width should be a whole number. Use the formula \(\text{Class Width} = \frac{\text{Range}}{\text{Number of Classes}}\).

Step 3 ：Count the number of data points in each class to determine the height of each bar in the histogram.

Step 4 ：For the boxplot, identify the minimum, maximum, median (Q2), first quartile (Q1), and third quartile (Q3). The box is drawn from Q1 to Q3 with a line inside the box for the median. The 'whiskers' extend from the box to the minimum and maximum values that are not outliers. Outliers are typically defined as values that are 1.5 times the interquartile range (Q3 - Q1) below Q1 or above Q3.

Step 5 ：Plot the boxplot and histogram using your calculator or a software like Excel or Google Sheets.

Step 6 ：Check your results to ensure they meet the requirements of the problem.