PENNY GENETICS: How Well Does a Punnett Square Predict the Actual Ratios?
In this mini lab you will make predictions using Punnett Squares and then use pennies to
simulate the genetic crosses. You will then use a statistical test to compare the actual results
with the predicted results.
The trait you are looking at is the gene that codes for Cystic Fibrosis in humans. Remember,
cystic fibrosis disease is due to a recessive allele.
●
F allele - codes for normal CFTR protein, no cystic fibrosis disease
●
f allele - codes for mutated CFTR protein, cystic fibrosis disease will develop
Part 1: Punnett square predicted ratios (expected ratios)
To find the predicted ratios draw a Punnett Square to show the cross between two carriers of
cystic fibrosis (heterozygous individuals). The Punnett Square depicts the ratio of theoretically
predicted genotypes based on the rules of probability.
Parental genotypes:
Mother:
Father:
Cross:
______ x _______
Percentage of descendant’s genotype:
Percentage of Descendant’s phonotype:
Part 2: Penny genetics for actual ratio (observed ratios)
Now we will collect data using pennies to represent the crosses. You will use a penny toss to
represent the heterozygous genotype of one parent, and a second penny toss to represent the
●
Head - dominant allele F
●
Tail - recessive allele f
After you have tossed the penny twice the results will show you the genotype of the offspring.
Repeat the coin flip to determine the genotype of a second offspring.
Repeat the procedure 4 times.
Record the percentage of offspring genotypes:
% FF
%Ff
%ff
Qualitative Analysis (answer in complete sentences):
●
What do the pennies represent in the simulation?
●
When you toss the coin to see which side lands up, what part of the sexual
reproduction process are you modeling?
●
When you put the two coins that are flipped together, what part of the sexual
reproduction process are you modeling?
Quantitative Analysis
You will perform a Chi-Square Goodness of Fit test to determine if there is a significant
difference between what was observed (penny toss) and what was expected (Punnett square).
Using the tables below Answer the following in complete sentences.
1. What is the null hypothesis for this test?
2. What is the alternative hypothesis for this test?
3. Complete a Chi-Square table to show your work for the Chi-Square test. Include the
Chi-Square formula and at least one example calculation.
4. Determine the DF for the test.
5. Determine the critical Chi-square value using a table of significance.
6. Interpret your statistical test to determine if there is a significant difference between
what was observed and what was expected.
Null Hypothesis:
Alternative Hypothesis:
Chi square table
Genotype
Observed
Expected
FF
Ff
ff
TOTAL
Calculations:
You can calculate the chi-square (X2) value by using the formula:
Where O is the observed frequency and E is the expected
frequency for each outcome (n). the symbol ∑ means the sum of.
So you will have to add all the results for each row. Use the table
above. Show your work here or use the table of frequencies to
break down the formula for x2.
Calculated X2 = _________________________________
Chi-Square
Degrees of Freedom: ________
DF= (number of rows - 1) X (number of columns - 1)
*the row and column for the total in the contingency table are not included
Critical X2 Value: _________
Conclusion:
Example format: Since the calculated χ2 value of _____is lower/higher than the critical χ2 value of ____
at the 0.05 level of significance, I accept/reject the null hypothesis and conclude that there is/ is NO
significant association between ________ and _______. They associate randomly in relation to each
other.
Table of critical values for the chi-square test
● If the calculated value is lower than the 0.05 level of significance, accept the null
hypothesis and conclude that there is NO significant association between the
variables.
● If the calculated value is higher than the 0.05 level of significance, reject the null
hypothesis and conclude that there IS a significant association between the variables.
Consider your results. Where the observed values much different from the expected values?
Why might your results not be the same as the expected results in the Punnett square?
Explain your answer. Reflect on your chi 2 conclusion. What does this result mean about
your penny experiment and Punnett squares.