US Historical Climate: Excel Statistical

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In this intermediate Excel activity, students import US Historical Climate Network mean temperature data into Excel from a station of their choice. They are then guided through the activity on how to use Excel for statistical calculations, graphing, and linear trend estimates. The activity assumes some familiarity with Excel and graphing in Excel.

HS-ESS3-5 Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth systems.

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.

Ask questions to determine relationships, including quantitative relationships, between independent and dependent variables.

Make a quantitative and/or qualitative claim regarding the relationship between dependent and independent variables.

Construct, use, and/or present an oral and written argument or counter-arguments based on data and evidence.

Use mathematical, computational, and/or algorithmic representations of phenomena or design solutions to describe and/or support claims and/or explanations.

Develop and/or use a model (including mathematical and computational) to generate data to support explanations, predict phenomena, analyze systems, and/or solve problems.

Select appropriate tools to collect, record, analyze, and evaluate data.

Make directional hypotheses that specify what happens to a dependent variable when an independent variable is manipulated.

The foundation for Earth’s global climate systems is the electromagnetic radiation from the sun, as well as its reflection, absorption, storage, and redistribution among the atmosphere, ocean, and land systems, and this energy’s re-radiation into space.

Current models predict that, although future regional climate changes will be complex and varied, average global temperatures will continue to rise. The outcomes predicted by global climate models strongly depend on the amounts of human-generated greenhouse gases added to the atmosphere each year and by the ways in which these gases are absorbed by the ocean and biosphere.

Empirical evidence is required to differentiate between cause and correlation and make claims about specific causes and effects.

Cause and effect relationships can be suggested and predicted for complex natural and human designed systems by examining what is known about smaller scale mechanisms within the system.

The significance of a phenomenon is dependent on the scale, proportion, and quantity at which it occurs.

Algebraic thinking is used to examine scientific data and predict the effect of a change in one variable on another (e.g., linear growth vs. exponential growth).

Change and rates of change can be quantified and modeled over very short or very long periods of time. Some system changes are irreversible.

Models can be used to predict the behavior of a system, but these predictions have limited precision and reliability due to the assumptions and approximations inherent in models.

Classifications or explanations used at one scale may fail or need revision when information from smaller or larger scales is introduced; thus requiring improved investigations and experiments.

Mathematical representations are needed to identify some patterns.

Patterns observable at one scale may not be observable or exist at other scales.

US Historical Climate: Excel Statistical

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Science and Engineering Practices

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