Which dot plot most accurately represents the distribution of the number of pets in households? Consider the following: 1. Dot plot ranging from 0 to 6: three dots at 0, five dots at 1, four dots at 2, three dots at 3, two dots at 4, zero dots at 5, and one dot at 6. 2. Dot plot ranging from 0 to 6: two dots at 1, three dots at 2, and one dot at 5. 3. Dot plot ranging from 0 to 6: one dot at 0, two dots at 1, one dot at 2, one dot at 3, one dot at 4, one dot at 5, and two dots at 6. 4. Dot plot ranging from 0 to 6: one dot at 1, two dots at 2, three dots at 3, two dots at 4, and one dot at 5.

To determine which dot plot most accurately represents the distribution of the number of pets in households, we would ideally need some real-world data on the number of pets per household. However, in the absence of specific data, we can make some educated assumptions.

Considering common scenarios, many households tend to have one or two pets, such as a dog or cat. Fewer households have no pets, and as the number of pets increases beyond two, the number of such households usually decreases. Thus, the distribution of the number of pets in households is likely skewed to the right, with a peak at one or two, and tails off as the number of pets increases.

Among the dot plots provided, Dot Plot 1 seems to most closely match common assumptions. It shows the highest numbers of households have one or two pets, which is typical. It also depicts some households with zero pets and gradually fewer households as the number of pets increases, which reflects the right-skewness of the distribution.

Dot Plot 1 details: - Three dots at 0 (suggesting some households have no pets) - Five dots at 1 (many households have one pet) - Four dots at 2 (many households also have two pets) - Declining numbers of dots from 3 to 6 (fewer households have more than two pets)

This distribution matches typical expectations, making Dot Plot 1 the most accurate representation based on common assumptions about pet ownership.

Extra: Dot plots are a simple way to visualize data where each dot represents one count or instance. The number of dots above each number on the horizontal axis indicates how many times that value appears in the data set. In the case of household pets, the values on the horizontal axis represent the number of pets (0, 1, 2, etc.), and the dots represent how many households have that number of pets.

When interpreting a dot plot, look for patterns such as clusters, gaps, peaks, and the spread of the dots to understand the distribution of the data. For example, a cluster of dots near a particular value suggests that the value is common. Gaps indicate the absence or rarity of a value in the data set. Peaks show where the data are concentrated, and the spread indicates the range within the data.

In the context of pet ownership, a properly constructed dot plot allows us to quickly see which numbers of pets are most common in households, and how the number of pets diminishes as we move to higher numbers on the scale. This is often consistent with real-world observations that while many people have pets, there is a natural decrease in the number of households with a large number of pets.