The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

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

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

The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

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.

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 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.

Methylmercury contamination within fish populations is an important toxin that affect human, animal, and environmental health, serving as a carcinogen (cancer-causing agent) and endocrine-disruptor (compounds that in some way alter the signaling of the hormone system. The impacts of exceeding safe dietary methylmercury levels were tragically made clear in Ontario, Canada, where a First Nations community in Grassy Narrows are living with the consequences of methylmercury poisoning in the fish supply. The fish were contaminated due to the dumping of mercury in the traditional waterways of the First Nation community. In 2016, there were highly publicized protests in Muskrat Falls, Labrador, Canada, where the Inuit people raised direct concerns about the potential for a proposed Nalcor Energy hydroelectric dam, to increase mercury levels in fish in those waters, which are an integral part of their traditional diet. Despite significant protests, the project was completed in 2019 and 41 km were flooded. This module uses these real-world examples as a jumping-off point for exercises that will guide case-study driven discussion on mathematical, biological and ethical concerns.

Students are introduced to concepts of sampling distributions and hypothesis testing using a simulation applet, 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 perform the Kaplan-Meier survival analysis on raw data obtained from an experiment that explores the effect of overexpressing the Snakeskin (Ssk) protein on the lifespan of a population of fruit flies. This tight junction equivalent protein is expressed at higher levels than normal specifically in the gut and throughout the entire lifespan of the flies. Because aging guts are accompanied by both a mislocalization and a decrease in the expression levels of junctional proteins, including Ssk, it was hypothesized that overexpressing Ssk may lead to a healthier fly with a longer lifespan. This data will be analyzed in order to determine if there is a significant difference between the control flies in which no overexpression occurs and the experimental group in which Ssk is overexpressed.

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.

The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

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 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 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.

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 are introduced to graphing and modeling data in a step-wise fashion. Real data of covid-19 deaths over time are used to incrementally ask students to fit the data to several models and discuss which model fits best.

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 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.

Methylmercury contamination within fish populations is an important toxin that affect human, animal, and environmental health, serving as a carcinogen (cancer-causing agent) and endocrine-disruptor (compounds that in some way alter the signaling of the hormone system. The impacts of exceeding safe dietary methylmercury levels were tragically made clear in Ontario, Canada, where a First Nations community in Grassy Narrows are living with the consequences of methylmercury poisoning in the fish supply. The fish were contaminated due to the dumping of mercury in the traditional waterways of the First Nation community. In 2016, there were highly publicized protests in Muskrat Falls, Labrador, Canada, where the Inuit people raised direct concerns about the potential for a proposed Nalcor Energy hydroelectric dam, to increase mercury levels in fish in those waters, which are an integral part of their traditional diet. Despite significant protests, the project was completed in 2019 and 41 km were flooded. This module uses these real-world examples as a jumping-off point for exercises that will guide case-study driven discussion on mathematical, biological and ethical concerns.

Students are introduced to concepts of sampling distributions and hypothesis testing using a simulation applet, 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 perform the Kaplan-Meier survival analysis on raw data obtained from an experiment that explores the effect of overexpressing the Snakeskin (Ssk) protein on the lifespan of a population of fruit flies. This tight junction equivalent protein is expressed at higher levels than normal specifically in the gut and throughout the entire lifespan of the flies. Because aging guts are accompanied by both a mislocalization and a decrease in the expression levels of junctional proteins, including Ssk, it was hypothesized that overexpressing Ssk may lead to a healthier fly with a longer lifespan. This data will be analyzed in order to determine if there is a significant difference between the control flies in which no overexpression occurs and the experimental group in which Ssk is overexpressed.

The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

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.

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.

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

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

The exploitation of African elephants in the form of ivory poaching is exacerbated by warfare. The affects of this anthropogenic evolutionary force on the African savanna elephant (Loxodonta africana) in the Gorongoas National Park in Mozambique was investigated (Campbell-Staton, et. al. 2021) after the Mozambican civil war (1997-1992).  This multipart lesson is based on this research.  Here, we explore allele frequencies, phenotypic data, and the use of a chi-squared test to determine if the population is in Hardy-Weinberg Equilibrium.  Because one gene influencing tusklessness is X-linked, we also explore inheritance of the trait, using hemophilia as an example.  The data used in this part of the lesson are simulated data based on reports from Zambia.

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.

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.

Methylmercury contamination within fish populations is an important toxin that affect human, animal, and environmental health, serving as a carcinogen (cancer-causing agent) and endocrine-disruptor (compounds that in some way alter the signaling of the hormone system. The impacts of exceeding safe dietary methylmercury levels were tragically made clear in Ontario, Canada, where a First Nations community in Grassy Narrows are living with the consequences of methylmercury poisoning in the fish supply. The fish were contaminated due to the dumping of mercury in the traditional waterways of the First Nation community. In 2016, there were highly publicized protests in Muskrat Falls, Labrador, Canada, where the Inuit people raised direct concerns about the potential for a proposed Nalcor Energy hydroelectric dam, to increase mercury levels in fish in those waters, which are an integral part of their traditional diet. Despite significant protests, the project was completed in 2019 and 41 km were flooded. This module uses these real-world examples as a jumping-off point for exercises that will guide case-study driven discussion on mathematical, biological and ethical concerns.

Students are introduced to concepts of sampling distributions and hypothesis testing using a simulation applet, 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 perform the Kaplan-Meier survival analysis on raw data obtained from an experiment that explores the effect of overexpressing the Snakeskin (Ssk) protein on the lifespan of a population of fruit flies. This tight junction equivalent protein is expressed at higher levels than normal specifically in the gut and throughout the entire lifespan of the flies. Because aging guts are accompanied by both a mislocalization and a decrease in the expression levels of junctional proteins, including Ssk, it was hypothesized that overexpressing Ssk may lead to a healthier fly with a longer lifespan. This data will be analyzed in order to determine if there is a significant difference between the control flies in which no overexpression occurs and the experimental group in which Ssk is overexpressed.

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 activity, students will analyze raw data obtained from an experiment that explores the effect of overexpressing the Ssk protein in order to strengthen the intestinal barrier and prevent bacteria from leaking out of the gut and into the hemolymph, which is the fruit fly equivalent to blood in the circulatory system. Using Excel, students will fit an exponential function to the few known data points and will then interpolate the missing data points and extrapolate a few future data points. They will also learn how they can fit a linear model by transforming the data (applying the logarithmic function) and use that model to estimate the missing data points. This activity involves both statistical analysis and mathematical modeling as well as displaying the usefulness of mathematical models for biological data analysis.

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 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 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.

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 activity, students are introduced to graphing and modeling data in a step-wise fashion. Real data of covid-19 deaths over time are used to incrementally ask students to fit the data to several models and discuss which model fits best.

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

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 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.

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

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.

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.

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.