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The\({\chi ^2}\)value means nothing on its own- it is used to find the probability that, assuming the hypothesis is true, the observed data set could have resulted from random fluctuations. A low probability suggests that the observed data are consistent with the hypothesis, and thus the hypothesis should be rejected, A standard cutoff point used by biologists is a probability of 0.05(5%). If the probability corresponding to the\({\chi ^2}\)value is 0.05or considered statistically significant, the hypothesis (that the genes are unlinked) should be rejected. If the probability is above 0.05, the results are not statistically significant: the observed data are consistent with the hypothesis.

To find the probability, locate your\({\chi ^2}\)value in the\({\chi ^2}\)Distribution table in Appendix F. The 鈥渄egree of freedom鈥 (pdf) of your data set is the number of categories (here,4 phenotypes), minus 1, so df=3.

(a). Determines which values on the df =3 line of the table your calculated\({\chi ^2}\)value lies between.

(b). The column headings for these values show the probability range for your\({\chi ^2}\)number. Based on whether there is non-significant (p\( \le \)0.05) or significant (p>0.05) difference between the observed and expected values, are the data consistent with the hypothesis that the two genes are unlinked and assorting independently, or is there enough evidence to reject this hypothesis?

Short Answer

Expert verified

(a) The \({\chi ^2}\)values lie between 1.42 and 2.37 following the reference with appendix F.

(b) The hypothesis given in the question is supported since the probability values are statistically significant

Step by step solution

01

Chi-square

The chi-square value is calculated to compare with the degree of freedom distribution to find if the hypothesis is supported or not. The standard value of probability is 0.05.If the probability value is greater than 0.05, then the hypothesis is significant. If the probability value is less than or equal to 0.05, then the hypothesis is not significant.

02

Explanation of part “a”

The sum value is calculated as 2.14 from the previous subdivision.

The degree of freedom given in the question is 3. By comparing the degrees of freedom, the\({\chi ^2}\)value lies in between 1.42 and 2.37. The value 2.14 lies between the value of 1.42 and 2.37 by appendix F.

03

Step 3: Explanation of part “b”

The genes that possess unlinked alleles get assorted independently. The unlinked alleles are present in different chromosomes. The phenotypic ratio of the F1dihybrid cross is 1:1:1:1.

The hypothesis in the given question is supported since the p-value lies between 0.5 and 0.70. The p value is greater than 0.05, so the hypothesis is supported, and the p value is significant by the given condition.

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Most popular questions from this chapter

Reciprocal cross between two primrose varieties, A and B, produced the following results: AfemaleBmaleoffspringwith all green (non-variegated) leaves;BfemaleAmaleoffspring with patterned (variegated) leaves. Explain these results

Review the description of meiosis (see Figure 13.8) and Mendel鈥檚 laws of segregation and independent assortment (see Concept 14.1). What is the physical basis for each of Mendel鈥檚 laws?

A wild-type fruit fly (heterozygous for the gray body color and red eyes) is mated with a black fruit fly with purple eyes. The offspring are wild-type, 721; black purple, 751; gray purple, 49; black red, 45. What is the recombination frequency between these genes for the body color and eye color? Using information for problem 3, what fruit flies (genotypes and phenotypes) would you mate to determine the order of the body color, wing size, and eye color genes on the chromosome?

The goodness of fit is measured by\({\chi ^{^2}}\). This statistic measures the amounts by which the observed values differ from their respective predictions to indicate how closely the two sets of values match. The formula for calculating this value is

\({\chi ^{}} = \sum \frac{{{{\left( {o - e} \right)}^2}}}{e}\)

Where o=observed and e= expected. Calculate the\({\chi ^{^2}}\)value for the data using the table below. Fill out the table, carrying out the operations indicated in the top row. Then add up the entries in the last column to find the\({\chi ^{^2}}\)value.

Testcross Offspring

Expected

(e)

Observed

(o)

Deviation

(o-e)

(o-e)2

(o-e)2/e

(A-B-)

220

(aaB-)

210

(A-bb)

231

(aabb)

239

\({\chi ^2}\) =sum

A planet is inhabited by creatures that reproduce with the same hereditary patterns seen in humans. Three phenotypic characters are height (T = tall, t= dwarf), head appendages (A = antennae, a = no antennae), and nose morphology (S = upturned snout, s = downturned snout). Since the creatures are not 鈥渋ntelligent,鈥 Earth scientists are able to do some controlled breeding experiments using various heterozygotes in testcrosses. For tall heterozygotes with antennae, the offspring are tall antennae, 46; dwarf antennae, 7; dwarf no antennae, 42; tall no antennae, 5. For heterozygotes with antennae and an upturned snout, the offspring are antennae upturned snout 47; antennae downturned snout, 2; no antennae downturned snout, 48; no antennae upturned snout, 3. Calculate the recombination frequencies for both experiments.

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