Students will explore sampling variability in the sample means of different random samples of a population, using data on Internet access from the U.S. Census Bureau’s American Community Survey.
1). Identify the sampling method used in a study and discuss its implications and potential limitations.
2). Critically evaluate the reliability and validity of results published in mainstream media.
3). Summarize and describe the distribution of a categorical variable in context.
This task involves two aspects of statistical reasoning: providing a probabilistic model for the situation at hand, and defining a way to collect data to determine whether or not the observed data is reasonably likely to occur under the chosen model. When guessing between two choices, there is no reason to suspect that one outcome is more likely than the other. Thus, a model that assumes the two outcomes to be equally likely (such as flipping a coin) is appropriate.
In this module, students are asked to look at how long it takes for planets and moons to complete their orbits, and how fast they are going.
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Students will participate in an online scavenger hunt based on a story that a geographer named Gina, who loves to travel, has escaped to an undisclosed location. It is their mission to bring her back to the school. Students must follow a series of clues about the location including landmarks, weather, and population—and use a U.S. Census Bureau data tool called State Facts for Students to answer questions that lead them one step closer to finding Gina.
This is a task from the Illustrative Mathematics website that is one part of a complete illustration of the standard to which it is aligned. Each task has at least one solution and some commentary that addresses important aspects of the task and its potential use.
In this introductory Excel tutorial (Activity I) students use Excel to explore the geodynamics model equation for ocean depth around a sea-floor spreading center. For students with no prior Excel experience.
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In this introductory Excel tutorial (Activity I) students use Excel to explore the geodynamics model equation for ocean depth around a sea-floor spreading center. For students with no prior Excel experience.
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Students import ocean bathymetry data from text files, they then use Excel to graph these observations along with model prediction to assess the model's ability to simulated the observed topographic features of the North Atlantic.
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Students import ocean bathymetry data from text files, they then use Excel to graph these observations along with model prediction to assess the model's ability to simulated the observed topographic features of the North Atlantic.
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In this exercise students work with light, temperature, and phytoplankton biomass proxy (chlorophyll a concentration) data to;
Become more skilled in reading and interpreting semi log graphs, temperature profiles, and time series plots.
Practice unit conversions.
Gain an understanding of k, the attenuation coefficient for nondirectional light.
See how the depth of the photic zone and the surface mixed layer varies seasonally at temperate latitudes and how this relates to seasonal phytoplankton productivity dynamics.
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An activity/lab where students determine the changes in 100-year flood determinations for 2 streams over time.
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Within this unit, I will take a three level design that is planned to make these courses more relevant to students and promote questions that interrogate the authority of statistics that students will encounter throughout the course and in their lives.
The skill of interrogating statistics is crucial for all adults in our society to become thinking consumers and users of data. In addition, it is important to deconstruct data to see implicit ideas of domination and subjugation that travel through numbers that can appear nuetral. Statistics shares a creation story with the field of Eugenics. Francis Galton, a mathematician who contributed many of the major ideas to statistics was also one of the originators of eugenics. The influence of eugenic thinking in statistics drives a notion of superiority, fitness and ranking alongside measurements. Milton Reynolds describes this in Shifting Frames:,” The term “eugenics” refers to a scientifically based, ideological movement dedicated to the reiification of race. It is the wellspring of scientific theories used to construct taxonomies of difference within the human family and to legitimize the subjugation of different groups.”.1 Statistics often does the work of justifying this subjugation through its “innocent” and authoritative work as a logical system. These embedded assumptions of superiority are validated by the seeming neutrality of mathematical calculations. The “taxonomies of difference” he describes are invalid and biased assumptions about difference that dominate our interpretations of data, however they appear as factual products legitimized by math.
This activity helps students develop a better understanding and stronger reasoning skills about the Central Limit Theorem and normal distributions.
Key words: Sample, Normal Distribution, Model, Distribution, Variability, Central Limit Theorem (CLT)
This activity allows students to plot arrival times for direct and head waves in a simple refraction system (2 or 3 layers, assuming horizontal interfaces). Students use provided MATLAB functions to investigate the effects of changing layer thicknesses and velocities on arrival times and crossover distances.
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An in-class activity for connecting earthquake magnitude, shaking, and intensity.
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Critical Data Studies (CDS) is an interdisciplinary field that addresses the ethical, legal, sociocultural, epistemological and political aspects of data science, big data, and digital infrastructure.
This course focuses on current topics in critical data studies scholarship. Students will develop tools and methods to think critically and engage the public in conversation about data and society.
The overall course and module are designed for asynchronous independent or group learning experiences. Instructors and students are encouraged to use the module as a whole or incorporate individual videos, discussion, writing and/or reading assignments into their course of study as desired.
[Note: The first module is available, and a second module is planned for a future release]
Seismograms of the 2004 M9.0 Sumatra earthquake, as recorded on station WANC on Wrnagell volcano, Alaska. The red signal shows the raw data and the blue represented data that have been lowpass filtered. The red spikes near 2800 s are local microearthquakes triggered by the passing of the surface waves.
Provenance: Jackie Caplan-Auerbach, Western Washington University
Reuse: This item is offered under a Creative Commons Attribution-NonCommercial-ShareAlike license http://creativecommons.org/licenses/by-nc-sa/3.0/ You may reuse this item for non-commercial purposes as long as you provide attribution and offer any derivative works under a similar license.
In this exercise, written for an undergraduate seismology class, students use MATLAB to analyze waveforms from the 2004 Sumatra M9.0 earthquake, as they were recorded on three seismic stations in Alaska. Two of the stations are broadbands and one is a short period station. Students use MATLAB scripts (provided) to plot and filter the time series data and to calculate power spectra at the different stations. They also see that surface waves from the Sumatra earthquake triggered microseismicity at Wrangell volcano as they passed through the hydrothermal system, an observation first made by West et al. (2005).
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Click to watch Jackie Caplan-Auerbach discuss her activity or watch the full webinar.
In doing this exercise students learn how the type of instrument and the instrument response affect the appearance of a seismogram. They identify body and surface waves in broadband seismograms. After examining the data on their own, students read a scientific paper that describes how microearthquakes were triggered by the passing surface waves. Not only does this provide them with experience reading and interpreting a scientific paper, but it shows them the types of observations made by the authors when they first analyzed the same data presented in this study.
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In this activity, students will determine whether there is a statistically significant difference in the number of watts of power produced on individual solar panels at Bryn Mawr College.
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Sonar technology allowed scientists to produce high-resolution maps of the sea floor for the first time. This sonar demonstration uses a Human Sound Wave to image the "sea floor" in a lecture hall. In doing so, students can see two-way travel times collected and plotted in real time. Students also evaluate sources of error that can be applied to a real sonar device.
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