Students will compare data for two states using comparison symbols and both rounded and unrounded (exact) numbers. Students will then write their own question to compare the data.
Spreadsheets Across the Curriculum module/Geology of National Parks course. Students study how discharge per unit area varies with elevation in the high country of Glacier National Park from USGS hydrograph data from Swiftcurrent Creek and its tributary Grinnell Creek..
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This website is a unique advanced-level comprehensive self-study source for statistical time series analysis, which introduces two major paradigm shifts initiated in the recent past and provides access to all the literature required to become an accomplished scholar in this subject area,
In this exercise, students use whole-rock major- and trace-element compositions of volcanic rocks to explore the origins of compositional variation in igneous suites. Large datasets from the Yellowstone and Crater Lake calderas are downloaded from the GEOROC database, imported into Excel spreadsheets, and graphed to learn about the different petrogeneses of these two volcanic suites.
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This lesson centers around the How AI Works: Computer Vision video from the How AI Works video series. Watch this video first before exploring the lesson plan.
Students learn how computer vision works. They first look at optical illusions to identify the features of the drawing that their eyes noticed. Students watch a video explaining computer vision and how a computer "sees". They design an algorithm that uses a network to decide what number the seven segment display is displaying. Finally, students test their algorithm.
This lesson can be taught on its own, or as part of a 7-lesson sequence on How AI Works. Duration: 45 minutes
An in-class statistics activity for computing and interpreting the standard deviation from a sample.
Word Count: 156850
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This lesson combines conditional probability and combinations to determine the probability of picking a fair coin given that it flipped 4 out of 6 heads. [Probability playlist: Lesson 16 of 29]
Students will learn about the nature and importance of qualitative research as a complement to numerical data — specifically how sociologists use in-depth ethnographic research to study specific places and groups. After students investigate census data on the demographics of their school’s ZIP code, they will observe a location at their school (e.g., a student center or cafeteria). Students will record their notes, understanding the importance of reflexivity in field research. Then they will write a short paper about their field study.
The applets in this section of Statistical Java allow you to see how levels of confidence are achieved through repeated sampling. The confidence intervals are related to the probability of successes in a Binomial experiment.
Today we’re going to talk about confidence intervals. Confidence intervals allow us to quantify our uncertainty, by allowing us to define a range of values for our predictions and assigning a likelihood that something falls within that range. And confidence intervals come up a lot like when you get delivery windows for packages, during elections when pollsters cite margin of errors, and we use them instinctively in everyday decisions. But confidence intervals also demonstrate the tradeoff of accuracy for precision - the greater our confidence, usually the less useful our range.
This activity represents a culmination project for this unit by means of which students can assess whether the IPCC prediction of increased storminess as an outcome of global warming survives testing. For the previous three weeks students will have conducted several inquiry-based group activities designed to introduce and reinforce fundamental meteorology/climatology concepts. In this 2-day project, students access online AVHRR SST imagery, as well as tabulated numeric data regarding historical North American tropical cyclones, import data into Excel for interpretation and analysis, and submit two group reports.
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The objective of this lesson is to introduce students to rainfall-runoff modeling using machine learning algorithms. In this lesson, students will walk through the process of accessing data, visualizing the data, statistically analyzing the data and using machine learning software packages to construct rainfall-runoff models.
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This book is designed as a short and introductory resource specifically aimed to help students grasp key concepts typically found in undergraduate psychology statistics subjects. It was initially developed for online and intensive programs, which are becoming increasingly popular in psychology education. The book utilises jamovi, a free and open-source statistical software. This peer reviewed book is completely free to download, use, and adapt and it is released using the CC BY-NC 4.0 licence.
A quantitative skills-intensive exercise using data from the Mineral Mountains, Utah, to calculate mass balance and to address the "space problem" involved with emplacing plutons into the crust.
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Students use gesture to describe the bulk deformation and local deformation apparent in images of a contractional analog experiment. Students then calculate bulk shortening and bulk thickening for the experiment and describe the structures accommodating that strain.
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The applets in this section allow you to see how the common Xbar control chart is constructed with known variance. The Xbar chart is constructed by collecting a sample of size n at different times t.
We may be living IN a simulation (according to Elon Musk and many others), but that doesn't mean we don't need to perform simulations ourselves. Today, we're going to talk about good experimental design and how we can create controlled experiments to minimize bias when collecting data. We'll also talk about single and double blind studies, randomized block design, and how placebos work.
During this demo, participants use springs and a map of the Pacific Northwest with GPS vectors to investigate the stresses and surface expression of subduction zones, specifically the Juan de Fuca plate diving beneath the North American plate.
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The applets in this section allow you to see how different bivariate data look under different correlation structures. The Movie applet either creates data for a particular correlation or animates a multitude data sets ranging correlations from -1 to 1.