SEP-4 

Objectives

Scientific investigations produce data that must be analyzed in order to derive meaning. Because data patterns and trends are not always obvious, scientists use a range of tools—including tabulation, graphical interpretation, visualization, and statistical analysis—to identify the significant features and patterns in the data. Scientists identify sources of error in the investigations and calculate the degree of certainty in the results. Modern technology makes the collection of large data sets much easier, providing secondary sources for analysis.

Middle School

• Analyzing data in 6–8 builds on K–5 experiences and progresses to extending quantitative analysis to investigations, distinguishing between correlation and causation, and basic statistical techniques of data and error analysis.

• Construct, analyze, and/or interpret graphical displays of data and/or large data sets to identify linear and nonlinear relationships.

• Use graphical displays (e.g., maps, charts, graphs, and/or tables) of large data sets to identify temporal and spatial relationships.

• Distinguish between causal and correlational relationships in data.

• Analyze and interpret data to provide evidence for phenomena.

• Apply concepts of statistics and probability (including mean, median, mode, and variability) to analyze and characterize data, using digital tools when feasible.

• Consider limitations of data analysis (e.g., measurement error), and/or seek to improve precision and accuracy of data with better technological tools and methods (e.g., https://www.nationmaster.commultiple trials).

• Analyze and interpret data to determine similarities and differences in findings.

• Analyze data to define an optimal operational range for a proposed object, tool, process or system that best meets criteria for success.

High School

• Analyzing data in 9–12 builds on K–8 experiences and progresses to introducing more detailed statistical analysis, the comparison of data sets for consistency, and the use of models to generate and analyze data.

• Analyze data using tools, technologies, and/or models (e.g., computational, mathematical) in order to make valid and reliable scientific claims or determine an optimal design solution.

• Apply concepts of statistics and probability (including determining function fits to data, slope, intercept, and correlation coefficient for linear fits) to scientific and engineering questions and problems, using digital tools when feasible.

• Consider limitations of data analysis (e.g., measurement error, sample selection) when analyzing and interpreting data.

• Compare and contrast various types of data sets (e.g., self-generated, archival) to examine consistency of measurements and observations.

• Evaluate the impact of new data on a working explanation and/or model of a proposed process or system.

• Analyze data to identify design features or characteristics of the components of a proposed process or system to optimize it relative to criteria for success.

Videos

• • Analyzing and Interpreting Data - Bozeman Science (Paul Anderson)

Resources

• • Google Sheets - Spreadsheets

  • CODAP - Common Online Data Analysis Program

  • GapMinder World - Environmental data by country

• Time lapse  - Visual satellite data

• Nationmaster - comparative statistics

• Discuss NGSS SEP "Analysis and Interpretation of Data"

CSCS Activities

• Harmonic Motion - Deriving the Formula for a Pendululm

• Density & Buoyancy - What causes something to sink or float?

• Genetics - Dihybrid Cross

• Heart Rate & Exercise

• Memory