When the items being tallied are numbers, a line plot can be used to visually display numerical data. A line plot uses X marks above a number line to show the frequencies. For example, a line plot of the number of books students read shows the frequencies of students who read 1 book, 2 books, and so on up to 7 books.
A frequency table organizes categorical data into categories and displays the frequency of each category. For example, a frequency table asking students' favorite color would have categories for different colors and show how many students chose each color. Analyzing frequency tables and line plots can identify outliers, clusters, or gaps in the data distributions.
2. Vocabulary
Data - information, often given in the form
of numbers or categories.
Frequency Table – a table that displays
the number of times each item or category
occurs in a data set.
Line Plot – a number line diagram that
uses X marks to show the frequencies of
items being tallied.
4. Books Students Read Last Month (numerical)
# of Books Tallies Frequency
1 llll 5 students
2 llll 5
3 llll l 6
4 ll 2
5
6
7 llll 4
5. Making a Line Plot
Is a visual of the frequency distribution.
Line plots are NOT used for categorical
data.
Draw a number line whose scale starts
at or before the minimum data value
and stops at or after the maximum data
value. Use a consistent increment.
6. Completed Line Plot -
When the items being tallied are numbers, a line plot
can be used to visually display numerical data. A line
plot uses X marks above a number line to show the
frequencies. The X marks above
the number line show
X the frequencies.
X X X
The Number Line X X X X
shows the number X X X X
of books read. X X X X X
X X X X X
1 2 3 4 5 6 7
Number of Books Read
7. Making a Frequency Table
Categorical data: data that can
be placed into categories.
Categorical question: What is
your favorite color?
8. Completed Frequency Table-
Favorite Color (category)
people
Color Tallies Frequency
Blue llll 5
Red lll 3
Yellow l 1
Purple ll 2
Orange llll 4
Green
Black ll 2
9. Variability in Data Distributions
Outliers-Unusually high or low values in
a distribution.
Clusters-An group of data values with
higher frequency than surrounding
values.
Gaps-Areas in the scale where there is a
lack of data values.
10. Analyze the Data
Now look at the Frequency
Tables and the Line Plots from
your notes to see if you can
identify any outliers, clusters or
gaps.