Featured in PASCO’s Advanced Biology through Inquiry Teacher Guide
This manual features 22 challenging, standards-based, inquiry lab activities for AP, IB, and honors programs.
After learning the technique for growing roots and preparing root tip squashes for microscope analysis, students observe the root tips for evidence of mitosis and statistically analyze the data.
After learning the technique for growing roots and preparing root tip squashes for microscope analysis, students observe the root tips for evidence of mitosis. They compare the number of cells in mitosis to the number of cells in interphase. They apply the chi-square “test of independence” to compare their results with provided data. Following the initial investigation, students can move to independent inquiry and test a particular treatment to see if it affects the rate of mitosis in roots. Chi-square analysis can be applied to evaluate the significance of the results.
Many biology teachers are familiar with the chi-square “goodness-of-fit” test, which tests how well observed data fits with expected data. However, this investigation requires the less familiar chi-square “test of independence,” which tests whether two categories are independent of each other. In many cases the goodness-of-fit test and the test of independence have similar outcomes for the same data set. For example, the chi-square value obtained from each method might indicate that the investigator should reject the null hypothesis. The value obtained from the test of independence will be more conservative in “treatment” situations—like the mitosis investigation—and is therefore a more valid statistical method to apply. (The value is less than what would be obtained for the goodness-of-fit test and makes it less likely that the null hypothesis is rejected.) Rather than use the observed cells in the control group to calculate expected values for the treatment group, as would be done in a goodness-of-fit test, observed cells in both control and treatment groups are used to calculate expected values in a 2 × 2 contingency table for the test of independence.
This experiment may require software and an interface for data collection.