Consider a situation where you have a parental cross with the mother and father phenotypes listed below. Remember that the genotype for the wild-type parent is always homozygous. The counts of the F1offspring are listed in Table 1. Two randomly selected individuals are selected and mated to produce a set of F2individuals. If you test the F2counts to determine whether they are consistent with an autosomal recessive mode of inheritance, what is your decision? Use a 0.05 significance level. PARENTAL CROSS Parental cross: Mother with wild type phenotype, Father with disease phenotype. Table 1. F1 DATA GenderPhenotypeDiseaseWild-typeMale600Female650 Table 2. F2 DATA GenderPhenotypeDiseaseWild-typeMale4623Female4115 A. Reject the null hypothesis that the F2 data are consistent with an autosomal recessive mode of inheritance; the p-value for the chi-square goodness of fit test < 0.05.B. Do not reject the null hypothesis that the F2 data are consistent with an autosomal recessive mode of inheritance; chi-square goodness of fit test statistic value is between 1 and 10.C. Reject the null hypothesis that the F2 data are consistent with an autosomal recessive mode of inheritance; the p-value for the chi-square goodness of fit test > 0.05.D. Reject the null hypothesis that the F2 data are consistent with an autosomal recessive mode of inheritance; the true mode of inheritance is X-linked recessive.E. Do not reject the null hypothesis that the F2 data are consistent with an autosomal dominant, homozygous lethal mode of inheritance; chi-square goodness of fit test p-value > 0.10.

From the given information, F2 COUNTS FOR DATA SET: Gender|Disease Phenotype Wild type Total…

Answered: Consider a situation where you have a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider a situation where you have a parental cross with the mother and father phenotypes listed below. Remember that the genotype for the wild-type parent is always homozygous.

The counts of the F₁offspring are listed in Table 1. Two randomly selected individuals are selected and mated to produce a set of F₂individuals. If you test the F₂counts to determine whether they are consistent with an autosomal recessive mode of inheritance, what is your decision? Use a 0.05 significance level.

PARENTAL CROSS

Parental cross: Mother with wild type phenotype, Father with disease phenotype.

Table 1. F1 DATA

Gender	Phenotype
Disease	Wild-type
Male	60	0
Female	65	0

Table 2. F2 DATA

Gender	Phenotype
Disease	Wild-type
Male	46	23
Female	41	15

A. Reject the null hypothesis that the F₂ data are consistent with an autosomal recessive mode of inheritance; the p-value for the chi-square goodness of fit test < 0.05.

B. Do not reject the null hypothesis that the F₂ data are consistent with an autosomal recessive mode of inheritance; chi-square goodness of fit test statistic value is between 1 and 10.

C. Reject the null hypothesis that the F₂ data are consistent with an autosomal recessive mode of inheritance; the p-value for the chi-square goodness of fit test > 0.05.

D. Reject the null hypothesis that the F₂ data are consistent with an autosomal recessive mode of inheritance; the true mode of inheritance is X-linked recessive.

E. Do not reject the null hypothesis that the F₂ data are consistent with an autosomal dominant, homozygous lethal mode of inheritance; chi-square goodness of fit test p-value > 0.10.

Definition Definition Measure of central tendency that is the value that occurs most frequently in a data set. A data set may have more than one mode if multiple categories repeat an equal number of times. For example, in a data set with five item—3, 5, 5, 29, 473—the mode is 5 because it occurs twice and no other value occurs more than once. On a histogram or bar chart, the element with the highest bar represents the mode. Therefore, the mode is sometimes considered the most popular option. The mode is useful for nominal or categorical data (e.g., the most common color car that users purchase), but it is problematic for continuous data because it is more likely not to have any value that is more frequent than the other.

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