(Please don't copy)All solve the problem Babies born with low birth weights (less than 2500 grams) are at an increased risk for many infant diseases. Researchers in NorthCarolina collected data to see what variables may influence the birth weight (in grams) of a child, including whether the mother drankalcohol during pregnancy, whether the mother smoked during pregnancy, the mother's age (years), the gestation of the pregnancy(number of weeks from conception until birth), the mother's race, the length of the birth (hours), and several others. The following plotwas created to summarize some of the data collected.3600SmokeO NoA Yes34003200-3000-2800 -26002400-3334353637383940414243GestationWhat is the response variable in this study?O Whether the mother smoked during pregnancyO Gestation of the pregnancyO The mother's ageO Birth weight0000 oWeight Blocking in the Randomizing Subjects appletIn Exploration 4.2 you used the Randomizing Subjects applet to randomly assign subjects to two groups. At the end of the exploration,you blocked on a person's sex and saw this eliminated all the variability in the difference in proportion of males. You should have alsoseen that blocking on a person's sex reduced the variability in the difference in height. This reduction in variation happened becausesex is associated with height. What about other variables? Open up the Randomizing Subjects applet to answer the following.(a) Another variable that can be used in the applet is "balance gene," which is categorical. Let's see if we get the same benefits ofreduced variability with this variable, like we did with height, when blocking on sex. Select the Reveal gene? option, use the pull-down menu to display the distribution of the difference in the proportion of subjects with the balance gene in the two groups, andthen do at least 1,000 replications of random assignment. Select the Both option to see the two distributions and summarystatistics of difference in the proportion of subjects that have the gene. The one labeled CR is completely randomized, and the onelabeled RAB is randomized block. What are the standard deviations of the graph of the differences in the proportions of balancegenes in each treatment for the randomized block design and for the completely randomized design? How do the standarddeviations compare? Does it appear that a person's sex is associated with the balance gene?O The SDs for both are about 0.20, so they are quite similar. Therefore, it does appear that a person's sex is associatedwith the balance gene.O The SDs for both are about 0.20, so they are quite similar. Therefore, it does not appear that a person's sex is associatedwith the balance gene.(b) Repeat part (a) of this question, except look at the quantitative variable called factor x.O The SDs for both are about 4.1, so they are quite similar. Therefore, it does appear that a person's sex is associated withthe factor x.O The SDs for both are about 4.1, so they are quite similar. Therefore, it does not appear that a person's sex is associatedwith the factor x.

Question

(Please don't copy)All solve the problem Babies born with low birth weights (less than 2500 grams) are at an increased risk for many infant diseases. Researchers in NorthCarolina collected data to see what variables may influence the birth weight (in grams) of a child, including whether the mother drankalcohol during pregnancy, whether the mother smoked during pregnancy, the mother's age (years), the gestation of the pregnancy(number of weeks from conception until birth), the mother's race, the length of the birth (hours), and several others. The following plotwas created to summarize some of the data collected.3600SmokeO NoA Yes34003200-3000-2800 -26002400-3334353637383940414243GestationWhat is the response variable in this study?O Whether the mother smoked during pregnancyO Gestation of the pregnancyO The mother's ageO Birth weight0000 oWeight Blocking in the Randomizing Subjects appletIn Exploration 4.2 you used the Randomizing Subjects applet to randomly assign subjects to two groups. At the end of the exploration,you blocked on a person's sex and saw this eliminated all the variability in the difference in proportion of males. You should have alsoseen that blocking on a person's sex reduced the variability in the difference in height. This reduction in variation happened becausesex is associated with height. What about other variables? Open up the Randomizing Subjects applet to answer the following.(a) Another variable that can be used in the applet is &#34;balance gene,&#34; which is categorical. Let's see if we get the same benefits ofreduced variability with this variable, like we did with height, when blocking on sex. Select the Reveal gene? option, use the pull-down menu to display the distribution of the difference in the proportion of subjects with the balance gene in the two groups, andthen do at least 1,000 replications of random assignment. Select the Both option to see the two distributions and summarystatistics of difference in the proportion of subjects that have the gene. The one labeled CR is completely randomized, and the onelabeled RAB is randomized block. What are the standard deviations of the graph of the differences in the proportions of balancegenes in each treatment for the randomized block design and for the completely randomized design? How do the standarddeviations compare? Does it appear that a person's sex is associated with the balance gene?O The SDs for both are about 0.20, so they are quite similar. Therefore, it does appear that a person's sex is associatedwith the balance gene.O The SDs for both are about 0.20, so they are quite similar. Therefore, it does not appear that a person's sex is associatedwith the balance gene.(b) Repeat part (a) of this question, except look at the quantitative variable called factor x.O The SDs for both are about 4.1, so they are quite similar. Therefore, it does appear that a person's sex is associated withthe factor x.O The SDs for both are about 4.1, so they are quite similar. Therefore, it does not appear that a person's sex is associatedwith the factor x.

Accepted Answer

The F test is used to compare the standard deviation of two samples. It is calculated by dividing…