Practice correlating with US milk production data

Practice interpreting a scatter plot and writing a claim using the evidence in the graph. The graph uses 2010 milk production data from the US Department of Agriculture.
Details

Activity Type: 

Mini-Lesson

Types of Instruction: 

  • Data Practice

Grades: 

  • 6, 7, 8

Subjects: 

  • Life Science, Social Science

Topics: 

  • Economics

Statistical Concepts: 

  • Correlation

Skills: 

  • Correlations

Graph Types: 

  • Scatter plot

Standards: 

Analyzing and interpreting data
Using mathematics and computational thinking
Constructing explanations and designing solutions
Scale, proportion, and quantity
Display numerical data in plots on a number line, including dot plots, histograms, and box plots.
Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability.
Determine the meaning of words and phrases as they are used in a text, including figurative, connotative, and technical meanings; analyze the impact of a specific word choice on meaning and tone.
Determine the meaning of words and phrases as they are used in a text, including figurative, connotative, and technical meanings; analyze the impact of specific word choices on meaning and tone, including analogies or allusions to other texts.
Write arguments to support claims with clear reasons and relevant evidence.
Write arguments to support claims with clear reasons and relevant evidence.
Determine the meaning of symbols, key terms, and other domain-specific words and phrases as they are used in a specific scientific or technical context relevant to grades 6-8 texts and topics.
Integrate quantitative or technical information expressed in words in a text with a version of that information expressed visually (e.g., in a flowchart, diagram, model, graph, or table).
Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
Stability and change
Analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects.
Gather and make sense of information to describe that synthetic materials come from natural resources and impact society.