# Create and interpret dot plots (simple)

Lesson

Dot plots are a graphical way of showing how often a particular choice was made or how many times an event occurred. They are best used for small to medium size data sets.

Just by looking at a dot plot we can see:

• the most frequent (common) choice/ event.
• the highest and lowest scores
• how spread out the scores are
• whether there are any outliers (scores that are very different from the rest)

#### Worked Example

##### Question 1

Mrs. Brown took a survey of the type of pets owned by her students and displayed her results in the dot plot below.

a) Which pet is most common?

Think: The most common pet will have the most dots, so the column will be the tallest.

Do: Birds were the most common type of pets.

b) There is the fewest of which type of pet?

Think: "Fewest" means "least" so we are looking for the column with the least number of dots.

Do: There is the fewest "other" pets.

c) How many students had cats?

Think: One dot represents one cat, so we need to count the number of dots.

Do: $6$6 students had cats.

d) Which pets could belong to the other category?

A) Birds    B) Dogs    C) Mice    D) Cats

Think: We need to find the animal that was not mentioned in the dot plot.

Do: Birds, dogs and cats were all columns in the dot plot, so C) mice could belong to the other category.

## Class Activity: Create Your Own Dot Plot

1. Think of a question to ask your classmates e.g. shoe size, type of pet, number of siblings (remember you don't want too many different answers so pick carefully).

2. Keep a tally of people's answers.

3. Create a dot plot of your data. Remember to include a title for your graph, as well as the names of all the possible responses (even if no people picked a particular answer).

4. Discuss your results as a class.

### Outcomes

#### S2-1

Conduct investigations using the statistical enquiry cycle:– posing and answering questions; – gathering, sorting, and displaying category and whole-number data; – communicating findings based on the data.