This is a challenge based activity in which students use augmented reality and trial and error in order to determine how changes to a quadratic equation affect the shape of a parabola. Students use the Geogebra AR app to manipulate equations and change the parabola to fit around a physical object.

In this real world problem students solve questions based on the relationship between production costs and price.

Khan Academy video tutorial with practice exercises. Introduction to averages and algebra problems involving averages.

This learning video continues the theme of an early BLOSSOMS lesson, Flaws of Averages, using new examples—including how all the children from Lake Wobegon can be above average, as well as the Friendship Paradox. As mentioned in the original module, averages are often worthwhile representations of a set of data by a single descriptive number. The objective of this module, once again, is to simply point out a few pitfalls that could arise if one is not attentive to details when calculating and interpreting averages. Most students at any level in high school can understand the concept of the flaws of averages presented here. The essential prerequisite knowledge for this video lesson is the ability to calculate an average from a set of numbers. Materials needed include: pen and paper for the students; a blackboard or equivalent; and coins (one per student) or something similar that students can repeatedly use to create a random event with equal chances of the two outcomes (e.g. flipping a fair coin). The coins or something similar are recommended for one of the classroom activities, which will demonstrate the idea of regression toward the mean. Another activity will have the students create groups to show how the average number of friends of friends is greater than or equal to the average number of friends in a group, which is known as The Friendship Paradox. The lesson is designed for a typical 50-minute class session.

Modeling traffic data is important for urban planning, creating transportation systems, and even predicting how much foot traffic a retail store can expect in a given day. This genre of dynamic data science activities could be classified as “finding a needle in a haystack,” giving students a chance to mine big data to make insights about traffic use.

According to the Bay Area Rapid Transit District, about 400,000 people used the BART system daily in 2018. In BARTy, students investigate BART data from 2015 to learn about passenger use and explore traffic patterns. The Teacher Guide includes a game-like investigation to locate a “mystery meeting,” and suggests ways to help students figure out peak passenger use, popular stations, and the impact of events in San Francisco on BART usage.

Modeling traffic data is important for urban planning, creating transportation systems, and even predicting how much foot traffic a retail store can expect in a given day. This genre of dynamic data science activities could be classified as “finding a needle in a haystack,” giving students a chance to mine big data to make insights about traffic use. According to the Bay Area Rapid Transit District, about 400,000 people used the BART system daily in 2018. In BARTy, students investigate BART data from 2015 to learn about passenger use and explore traffic patterns.

This task provides a real world context for interpreting and solving exponential equations. There are two solutions provided for part (a). The first solution demonstrates how to deduce the conclusion by thinking in terms of the functions and their rates of change. The second approach illustrates a rigorous algebraic demonstration that the two populations can never be equal.

Students follow the steps of the engineering design process as they design and construct balloons for aerial surveillance. After their first attempts to create balloons, they are given the associated Estimating Buoyancy lesson to learn about volume, buoyancy and density to help them iterate more successful balloon designs.Applying their newfound knowledge, the young engineers build and test balloons that fly carrying small flip cameras that capture aerial images of their school. Students use the aerial footage to draw maps and estimate areas.

This real world task requires students to answer questions about equations for calculating compound interest.

The purpose of this task is to study an example of a function which varies discretely over time. Step functions are often good examples for this type of function. In practice, instead of a step function, bar graphs are sometimes used. Alternatively, Jessie's method of ''smoothing'' over the jumps is also very common.

This task asks students to use similarity to solve a problem in a context that will be familiar to many, though most students are accustomed to using intuition rather than geometric reasoning to set up the shot.

This document includes two activities related to earthquake base isolation. Learners explore earthquake hazards and damage to buildings by constructing model buildings and subjecting the buildings to ground vibration (shaking similar to earthquake vibrations) on a small shake table. Base isolation a powerful tool for earthquake engineering. It is meant to enable a building to survive a potentially devastating seismic impact through a proper initial design or subsequent modifications. The buildings are constructed by two- or three-person learner teams.

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BPCC Open Campus - Math 097: Basic Mathematics is a review of basic mathematics skills. Here's what's covered: -fundamental numeral operations of addition, subtraction, multiplication division of whole numbers, fractions, and decimals -ratio and proportion -percent -systems of measurement -an introduction to geometry NOTE: Open Campus courses are non-credit reviews and tutorials and cannot be used to satisfy requirements in any curriculum at BPCC.

In the master-equation formalism, a set of differential equations describe the time-evolution of the probability distribution of an ensemble of systems. This can be used, for example, to describe the varied mRNA copy numbers found in individual cells in a population.

The stochastic simulation algorithm (SSA, Kinetic Monte Carlo, Gillespie algorithm) produces an example trajectory for a particular member of a probabilistic ensemble by looping over the following steps. The current state of the system is used to determine the likelihood of each possible chemical reaction in relative comparison to the likelihoods for the other possible reactions, as well as to determine when the next reaction is expected. Pseudo-random numbers are drawn to "roll the dice" to determine exactly when the next reaction will proceed, and which kind of reaction it will happen to be.

This is a basketball math activity to have students collect data on free throw...

This task involves a fairly straightforward decaying exponential. Filling out the table and developing the general formula is complicated only by the need to work with a fraction that requires decisions about rounding and precision.

A series of 63 instructional videos from MATH085 - Pre-Algebra created by Jim Helmer for Bay College.

© 2017 Bay College and Content Creators. Except where otherwise noted this work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

A series of 63 instructional videos from MATH095 - Basic Algebra created by Jim Helmer for Bay College.

© 2017 Bay College and Content Creators. Except where otherwise noted this work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

A series of 38 instructional videos from MATH105 - Intermediate Algebra created by Jim Helmer for Bay College.

© 2017 Bay College and Content Creators. Except where otherwise noted this work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.