Using Line Plots to Predict Snow Days

This lesson teaches how to create lime plots using fractional data. It emphasizes the importance of ordering data from least to greatest and maintaining accuracy in spacing. The lesson also covers handling fractions with unlike denominators by finding common denominators. A practical example is provided using snowfall data to predict snow days, demonstrating the utility of lime plots in visualizing data trends.

What is the first step in creating a lime plot?

• Marking the line with Xs

• Ordering data from least to greatest

• Predicting future trends

• Finding common denominators

Why is it important to have accurate spacing in a lime plot?

• To use fewer data points

• To save space on the paper

• To easily compare sections of data

• To make the plot look neat

Why are common denominators useful when working with fractional data in lime plots?

• They make the plot more colorful

• They help in ordering fractions

• They simplify the plot's design

• They reduce the number of data points

What is the purpose of crossing out data as you plot it?

• To reduce the number of data points

• To make the plot more artistic

• To highlight important data

• To ensure no data is missed

Based on the lime plot, which month is more likely to have a snow day?

• March

• December

• February

• January