Homework Help is Here – Start Your Trial Now!
Math
Statistics
Babies born with low birth weights (less than 2500 grams) are at an increased risk for many infant diseases. Researchers in North Carolina collected data to see what variables may influence the birth weight (in grams) of a child, including whether the mother drank alcohol 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 plot was created to summarize some of the data collected. Weight 3600 3400- 3200- 3000- 2800- 2600- 2400- Smoke O No A Yes O 004 O O O O 4 < 00 04 8 O O 2 CA A M

Babies born with low birth weights (less than 2500 grams) are at an increased risk for many infant diseases. Researchers in North Carolina collected data to see what variables may influence the birth weight (in grams) of a child, including whether the mother drank alcohol 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 plot was created to summarize some of the data collected. Weight 3600 3400- 3200- 3000- 2800- 2600- 2400- Smoke O No A Yes O 004 O O O O 4 < 00 04 8 O O 2 CA A M

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
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 North Carolina collected data to see what variables may influence the birth weight (in grams) of a child, including whether the mother drank alcohol 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 plot was created to summarize some of the data collected. 3600 Smoke O No A Yes 3400 3200- 3000- 2800 - 2600 2400- 33 34 35 36 37 38 39 40 41 42 43 Gestation What is the response variable in this study? O Whether the mother smoked during pregnancy O Gestation of the pregnancy O The mother's age O Birth weight 00 00 o Weight
Transcribed Image Text:Babies born with low birth weights (less than 2500 grams) are at an increased risk for many infant diseases. Researchers in North Carolina collected data to see what variables may influence the birth weight (in grams) of a child, including whether the mother drank alcohol 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 plot was created to summarize some of the data collected. 3600 Smoke O No A Yes 3400 3200- 3000- 2800 - 2600 2400- 33 34 35 36 37 38 39 40 41 42 43 Gestation What is the response variable in this study? O Whether the mother smoked during pregnancy O Gestation of the pregnancy O The mother's age O Birth weight 00 00 o Weight
Blocking in the Randomizing Subjects applet In 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 also seen that blocking on a person's sex reduced the variability in the difference in height. This reduction in variation happened because sex 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 of reduced 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, and then do at least 1,000 replications of random assignment. Select the Both option to see the two distributions and summary statistics of difference in the proportion of subjects that have the gene. The one labeled CR is completely randomized, and the one labeled RAB is randomized block. What are the standard deviations of the graph of the differences in the proportions of balance genes in each treatment for the randomized block design and for the completely randomized design? How do the standard deviations 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 associated with 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 associated with 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 with the 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 associated with the factor x.
Transcribed Image Text:Blocking in the Randomizing Subjects applet In 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 also seen that blocking on a person's sex reduced the variability in the difference in height. This reduction in variation happened because sex 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 of reduced 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, and then do at least 1,000 replications of random assignment. Select the Both option to see the two distributions and summary statistics of difference in the proportion of subjects that have the gene. The one labeled CR is completely randomized, and the one labeled RAB is randomized block. What are the standard deviations of the graph of the differences in the proportions of balance genes in each treatment for the randomized block design and for the completely randomized design? How do the standard deviations 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 associated with 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 associated with 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 with the 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 associated with the factor x.
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 5 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS