Creating Stem and Leaf Plots

Oct 13, 2025 by pinkandtrash.com 68 views

Introduction

Stem and leaf plots are a type of data visualization used to represent a dataset in a compact and easy-to-understand format. They are commonly used in statistics and data analysis to display the distribution of a variable. In this article, we will explore how to use stem and leaf plots to answer questions related to a survey conducted by a surveyor. The survey asked about the age of people entering a mall on a Tuesday and again on a Saturday from 1 p.m. to 3 p.m.

Creating Stem and Leaf Plots

A stem and leaf plot consists of two columns: the stem column and the leaf column. The stem column represents the tens digit of the data, while the leaf column represents the ones digit. For example, if we have a dataset with the values 12, 23, 34, and 45, the stem and leaf plot would look like this:

Stem	Leaf
1	2
2	3
3	4
4	5

Interpreting Stem and Leaf Plots

To interpret a stem and leaf plot, we need to look at the stem column and the leaf column separately. The stem column gives us an idea of the range of values in the dataset, while the leaf column gives us an idea of the frequency of each value. For example, in the stem and leaf plot above, we can see that the range of values is from 12 to 45, and that the value 23 occurs twice.

Using Stem and Leaf Plots to Answer Questions

Now that we have a basic understanding of stem and leaf plots, let's use them to answer questions related to the survey conducted by the surveyor.

Question 7: How do the shapes compare?

To answer this question, we need to create a stem and leaf plot for the ages of people entering the mall on a Tuesday and a Saturday. Let's assume that the dataset for Tuesday is:

Age
12
23
34
45
56
67
78
89

And the dataset for Saturday is:

Age
12
23
34
45
56
67
78
89

The stem and leaf plots for both days would look like this:

Tuesday:

Stem	Leaf
1	2
2	3
3	4
4	5
5	6
6	7
7	8
8	9

Saturday:

Stem	Leaf
1	2
2	3
3	4
4	5
5	6
6	7
7	8
8	9

From the stem and leaf plots, we can see that the shapes of the two plots are identical. This means that the distribution of ages on Tuesday and Saturday is the same.

Question 8: How do the peaks compare?

To answer this question, we need to look at the leaf column of the stem and leaf plots. The peak of a stem and leaf plot is the value with the highest frequency. In this case, the peaks of both plots are the same, which is 23. This means that the value 23 occurs twice on both Tuesday and Saturday.

Question 9: What is the range of ages on Tuesday?

To answer this question, we need to look at the stem column of the stem and leaf plot. The range of ages is the difference between the highest and lowest values. In this case, the highest value is 89 and the lowest value is 12. Therefore, the range of ages on Tuesday is 77.

Question 10: What is the median age on Saturday?

To answer this question, we need to look at the leaf column of the stem and leaf plot. The median age is the middle value of the dataset. In this case, the dataset is already sorted, so the median age is the value in the middle, which is 34.

Question 11: What is the mode of ages on Tuesday?

To answer this question, we need to look at the leaf column of the stem and leaf plot. The mode is the value with the highest frequency. In this case, the value 23 occurs twice, which is the highest frequency. Therefore, the mode of ages on Tuesday is 23.

Question 12: What is the interquartile range (IQR) of ages on Saturday?

To answer this question, we need to look at the leaf column of the stem and leaf plot. The IQR is the difference between the 75th percentile and the 25th percentile. In this case, the 75th percentile is 56 and the 25th percentile is 23. Therefore, the IQR of ages on Saturday is 33.

Conclusion

In this article, we have used stem and leaf plots to answer questions related to a survey conducted by a surveyor. We have created stem and leaf plots for the ages of people entering the mall on a Tuesday and a Saturday, and have used them to answer questions about the shapes, peaks, range, median, mode, and interquartile range of the ages. We have seen that the stem and leaf plots are a useful tool for data analysis and visualization, and that they can be used to answer a wide range of questions about a dataset.

References

[1] "Stem and Leaf Plots." Math Is Fun, mathisfun.com/data/stem-and-leaf-plots.html.
[2] "Data Analysis with Stem and Leaf Plots." Statistics How To, statisticshowto.com/data-analysis-with-stem-and-leaf-plots/.
Stem and Leaf Plots: A Q&A Guide =====================================

Introduction

Q&A

Q: What is a stem and leaf plot?

A: A stem and leaf plot is a type of data visualization that displays a dataset in a compact and easy-to-understand format. It consists of two columns: the stem column and the leaf column. The stem column represents the tens digit of the data, while the leaf column represents the ones digit.

Q: How do I create a stem and leaf plot?

A: To create a stem and leaf plot, you need to follow these steps:

Sort the data in ascending order.
Identify the tens digit of each data point (this will be the stem).
Identify the ones digit of each data point (this will be the leaf).
Create a table with two columns: the stem column and the leaf column.
Fill in the stem column with the tens digit of each data point.
Fill in the leaf column with the ones digit of each data point.

Q: What is the purpose of a stem and leaf plot?

A: The purpose of a stem and leaf plot is to display the distribution of a variable in a compact and easy-to-understand format. It allows you to see the range of values, the frequency of each value, and the shape of the distribution.

Q: How do I interpret a stem and leaf plot?

A: To interpret a stem and leaf plot, you need to look at the stem column and the leaf column separately. The stem column gives you an idea of the range of values, while the leaf column gives you an idea of the frequency of each value.

Q: What is the difference between a stem and leaf plot and a histogram?

A: A stem and leaf plot and a histogram are both types of data visualization, but they display the data in different ways. A stem and leaf plot displays the data in a compact and easy-to-understand format, while a histogram displays the data in a graphical format.

Q: Can I use a stem and leaf plot to display categorical data?

A: No, a stem and leaf plot is typically used to display numerical data. If you want to display categorical data, you may want to use a different type of data visualization, such as a bar chart or a pie chart.

Q: How do I use a stem and leaf plot to answer questions about a dataset?

A: To use a stem and leaf plot to answer questions about a dataset, you need to follow these steps:

Create a stem and leaf plot of the dataset.
Look at the stem column and the leaf column separately.
Identify the range of values, the frequency of each value, and the shape of the distribution.
Use this information to answer questions about the dataset.

Q: What are some common applications of stem and leaf plots?

A: Stem and leaf plots are commonly used in statistics and data analysis to display the distribution of a variable. They are also used in business, economics, and social sciences to display data and answer questions about a dataset.

Q: Can I use a stem and leaf plot to display large datasets?

A: Yes, a stem and leaf plot can be used to display large datasets. However, it may be more difficult to interpret the plot if the dataset is very large.

Q: How do I create a stem and leaf plot in a spreadsheet?

A: To create a stem and leaf plot in a spreadsheet, you need to follow these steps:

Sort the data in ascending order.
Create a table with two columns: the stem column and the leaf column.
Fill in the stem column with the tens digit of each data point.
Fill in the leaf column with the ones digit of each data point.
Use the spreadsheet's built-in functions to create the stem and leaf plot.

Q: Can I use a stem and leaf plot to display data with decimal points?

A: Yes, a stem and leaf plot can be used to display data with decimal points. However, you may need to round the data to the nearest whole number to create the plot.

Conclusion

In this article, we have answered some frequently asked questions about stem and leaf plots. We have discussed the purpose of a stem and leaf plot, how to create one, and how to interpret it. We have also discussed some common applications of stem and leaf plots and how to use them to answer questions about a dataset.