Overview

In this series of mini case studies, students will explore the use of three biostatistical tests and apply them to biological data. The students will explore four different data sets and they must apply the correct statistical test to infer whether or not the data represented is significant.

Before the students can use their knowledge on a set of cases the instructor will go over an in-depth practice session. The practice is a hands-on experience where students will be acquiring the data to apply the test on. An example of this would be weighing different candies and applying a student's ...

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In this series of mini case studies, students will explore the use of three biostatistical tests and apply them to biological data. The students will explore four different data sets and they must apply the correct statistical test to infer whether or not the data represented is significant.

Before the students can use their knowledge on a set of cases the instructor will go over an in-depth practice session. The practice is a hands-on experience where students will be acquiring the data to apply the test on. An example of this would be weighing different candies and applying a student's t-test to the data or gathering the height of the males vs females in the classroom.
Within the classroom/laboratory the students are split into groups and collaborate to answer a series of biostat cases. The first case involves patients on two different type of anti-coagulant drugs, the students must apply a paired student t-test to decide if there is a difference in blood clotting between the two drugs. The second case uses linear regression to determine if body temperature effects the frequency of chirps in crickets. Lastly, students will explore a third case which investigates if deer feeding habits are related to the distribution of different types of browse (tender shoots, twigs and leaves of tree shrubs). Students have the opportunity to take on the role of Ecologist and Biologist and have a chance to apply inferential statistics.
The fourth case, which will be completed by the students out of the class/lab, investigates the effect of rising atmospheric CO2 levels on the Earth’s global surface temperature. The students will apply a regression analysis to the data to determine whether or not there is a significant relationship between the two parameters.

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Objectives

  • How to apply statistics to biological data.

Context and requirements

Level College
Discipline Biology
Course General Biology I and II
Activity Content Four biostat asisgnments/cases
Technological Requirements Excel
Best Use Mini case studies

Author’s Notes

Benefits

  • This series of mini case studies helps students see how statistics are applied to biological data and the importance of statistics in allowing scientists to draw conclusions from results.

Challenges

  • Students struggle with understanding and interpreting the p-value;
  • Students also struggle with selecting the correct graph type or which data to graph;
  • The students also represent the raw data on the graphs instead of graphing the average for the data.

Tips

  • The instructor should provide a lot of feedback and guidance during this activity since students have issues graphing and selecting the correct statistical test;
  • It is important that students get a lot of practice with different data sets.

Activity Pedagogical Components

CASE STUDY

For a description of this strategy, please see here.

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