FACTivity – Endangered Plants (Left High and Dry)
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In this FACTivity, you will use the data provided in a table to calculate the results of a planting program in Hawai'i. Then you will
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Left High and Dry? Attempting to Restore a Tropical Dry Forest in Hawaii
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Standards addressed in this Activity:
The Next Generation Science Standards (NGSS) are a set of K-12 science education standards emphasizing inquiry-based learning, real-world applications, and integrating engineering practices, aiming to deepen understanding of science while promoting critical thinking and problem-solving skills.
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MS-ESS3-3
Apply scientific principles to design a method for monitoring and minimizing a human impact on the environment.
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MS-LS2-4
Construct an argument supported by empirical evidence that changes to physical or biological components of an ecosystem affect populations.
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MS-LS2-5
Evaluate competing design solutions for maintaining biodiversity and ecosystem services.
The Common Core Standards are educational benchmarks in the United States that outline clear expectations for what students should know and be able to do in English language arts and mathematics from kindergarten through 12th grade, aiming to ensure consistency and coherence in education nationwide.
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Identify key steps in a text's description of a process related to history/social studies (e.g., how a bill becomes law, how interest rates are raised or lowered).
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Recognize a statistical question as one that anticipates variability in the data related to the question and accounts for it in the answers. For example, "How old am I?" is not a statistical question, but "How old are the students in my school?" is a statistical question because one anticipates variability in students' ages.
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Summarize numerical data sets in relation to their context, such as by:
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Understand that statistics can be used to gain information about a population by examining a sample of the population; generalizations about a population from a sample are valid only if the sample is representative of that population. Understand that random sampling tends to produce representative samples and support valid inferences.
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Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions. For example, estimate the mean word length in a book by randomly sampling words from the book; predict the winner of a school election based on randomly sampled survey data. Gauge how far off the estimate or prediction might be.
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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. For example, the mean height of players on the basketball team is 10 cm greater than the mean height of players on the soccer team, about twice the variability (mean absolute deviation) on either team; on a dot plot, the separation between the two distributions of heights is noticeable.
