This collection of activities explores the relationship between blood flow, pressure, and the factors of resistance through graphs and modeling direct and inverse variation.

In this activity, students use real water chemistry data and descriptive statistics in Excel to examine primary productivity in an urban estuary of the Salish Sea. They will consider how actual data do or do not support expected annual trends.

This lab is an exploration of enzyme function and the effects of environmental conditions on the activity of the enzyme amylase. The lab utilizes analytical and graphing skills to assess enzyme activity.

In this activity, students will explore the concept of binary fission, generation time, and bacterial growth curves, with an emphasis on the log phase. Students will use semi-log graphs and linear graphs to plot bacterial cell growth.

In this activity, students will model a noisy set of bacterial cell count data using both exponential and logistic growth models. For each model the students will plot the data (or a linear transformation of the data) and apply the method of least squares to fit the model's parameters. Activities include both theoretical and conceptual work, exploring the properties of the differential equation models, as well as hands-on computational work, using spreadsheets to quickly process large amounts of data. This activity is meant as a capstone to the differential calculus portion of a typical undergraduate Calculus I course. It explores a biological application of a variety of differential calculus concepts, including: differential equations, numerical differentiation, optimization, and limits. Additional topics explored include semi-log plots and linear regression.

Students typically find linear regression analysis of data sets in a biology classroom challenging. These activities could be used in a Biology, Chemistry, Mathematics, or Statistics course. The collection provides student activity files with Excel instructions and Instructor Activity files with Excel instructions and solutions to problems. Students will be able to perform linear regression analysis, find correlation coefficient, create a scatter plot and find the r-square using MS Excel 365. Students will be able to interpret data sets, describe the relationship between biological variables, and predict the value of an output variable based on the input of an predictor variable.

In this activity, students will explore the use of a hemocytometer for counting cells, demonstrate the relationship between the grid seen in the microscope with volume of liquid in suspension and count cells to determine concentration.

This module explores how cell size and shape varies across cell types in the human body by having students calculate relative proportions of numbers in scientific notation. The adaptation has added a review of scientific notation.

In this powerpoint, several of the resources from the published module 'Sizes, Scales and Specialization' are used to create a mini-module that has students examine the size and abundance of different human cell types using scientific notation.

This module explores how cell size and shape varies across cell types in the human body by having students calculate relative proportions of numbers in scientific notation.

In this activity, students will explore the concept of binary fission, generation time, and bacterial growth curves, with an emphasis on the log phase. Students will use semi-log graphs and linear graphs to plot bacterial cell growth.

In this activity, students will perform an experiment utilizing dialysis tubing to create cellular models to demonstrate the linear relationship between cell weight and time in varying tonicities. Videos and data sets (of faculty results) are provided for

In this activity, students will explore the use of a hemocytometer for counting cells, demonstrate the relationship between the grid seen in the microscope with volume of liquid in suspension and count cells to determine concentration.

This module explores surface area to volume ratios in a cube and sphere in relation to cell size.

Students are introduced to concepts of sampling distributions, p-values, and hypothesis testing. Using both simulated and real data for methylmercury level in fish populations, students will determine whether observations fall within government safety guidelines for safe consumption.

In this activity, students use real water chemistry data and descriptive statistics in Excel to examine primary productivity in an urban estuary of the Salish Sea. They will consider how actual data do or do not support expected annual trends.

In this adaptation students in online classrooms will use linear regression at home and in synchronous online time to analyze real data on vector-borne diseases and explore how environmental factors affect disease transmission.

Students are introduced to concepts of hypothesis testing using elementary hypothesis tests, t-tests, and p-values as they compare a given fish population for methylmercury levels (using real and hypothetical data) against real-world mercury standards.

In this activity students will use linear regression to analyze real data on vector-borne diseases and explore how environmental factors such as climate change or population density influence the transmission of these diseases.

This module utilizes a user-friendly database exploring data selection, box-and-whisker plot, and correlation analysis. It also guides students on how to make a poster of their data and conclusions.

In this activity, students will explore the concept of binary fission, generation time, and bacterial growth curves, with an emphasis on the log phase. Students will use semi-log graphs and linear graphs to plot bacterial cell growth.

In this adaptation students in online classrooms will use linear regression at home and in synchronous online time to analyze real data on vector-borne diseases and explore how environmental factors affect disease transmission.

In this activity, students will explore the use of a hemocytometer for counting cells, demonstrate the relationship between the grid seen in the microscope with volume of liquid in suspension and count cells to determine concentration.

In this activity, students will explore the concept of binary fission, generation time, and bacterial growth curves, with an emphasis on the log phase. Students will use semi-log graphs and linear graphs to plot bacterial cell growth.

In this activity, students will explore the use of a hemocytometer for counting cells, demonstrate the relationship between the grid seen in the microscope with volume of liquid in suspension and count cells to determine concentration.

In this activity students will use linear regression to analyze real data on vector-borne diseases and explore how environmental factors such as climate change or population density influence the transmission of these diseases.

This collection of activities explores the relationship between blood flow, pressure, and the factors of resistance through graphs and modeling direct and inverse variation.

Students are introduced to concepts of sampling distributions, p-values, and hypothesis testing. Using both simulated and real data for methylmercury level in fish populations, students will determine whether observations fall within government safety guidelines for safe consumption.

Students are introduced to concepts of hypothesis testing using elementary hypothesis tests, t-tests, and p-values as they compare a given fish population for methylmercury levels (using real and hypothetical data) against real-world mercury standards.