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Is evolution occurring in humans?
Part 2: -Chi Square test
Materials:
- Notebooks & pencils
- Printable
Student Worksheets
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Objectives:
Use the chi-square test to determine if the number of students with a
certain trait is significantly different from expected. Compare
current data with the last run of the CIESE Genetics Project.
Procedures
Resources (to get you started)
There is also an excellent chi-square simulator available online designed by Alan Lemmon and EvoTutor.org
Georgetown University has a couple of useful sites:
You may also wish to use the online Chi-square calculator.
Or a detailed overview of chi square testing including a section on requirements for the chi square test.
Critical values of Chi square distribution from NIST/SEMATECH e-Handbook of Statistical Methods,
Teacher guidelines
Students can de divided into groups of 2 and assigned one trait to start with. They can perform their calculations and report to the class. If time permits you can have students check all the traits and write up a report using the questions below.
It is recommended that students do portions of the test by hand so that they understand the nature of the calculations they are performing. It is recommended that the chi square test be done as a spreadsheet exercise because it will encourage the use of technology to extend the testing ability the student can do in a given amount of time. You can start from scratch designing a functioning spreadsheet or use one that has been designed for you.
Student Directions
Using the data gathered during the current running of the Genetics project, determine if there is a significant difference between these data and the numbers expected based on the last run of the Genetics project. You will need the numbers for the dominant phenotype and recessive phenotype and the percentages from the last run for dominant phenotype and recessive phenotype.
The chi square test is not the best test for significant differences. See heading "Some important points about chi-squared".
Question
1. Are your numbers significantly different from expected? Can we conclude that evolution is taking place?
2. Read carefully the chi square requirements and determine if there is a potential source of error in your study. Which chi square requirement might a critic of your work suggest has not been satisfied? Design an experiment that would address this issue.
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