Question

It is well documented that active maternal smoking during pregnancy is associated with lower-birth-weight babies. Researchers wanted to determine if there is a relationship between paternal smoking habits and birth weight. The researchers administered a questionnaire to each parent of newborn infants. One question asked whether the individual smoked regularly. Because the survey was administered within 15 days of birth, it was assumed that any regular smokers were also regular smokers during pregnancy. Birth weights for the babies (in grams) of nonsmoking mothers were obtained and divided into two groups, nonsmoking fathers and smoking fathers. The given data are representative of the data collected by the researchers. The researchers concluded that the birth weight of babies whose father smoked was less than the birth weight of babies whose father did not smoke. $$ \begin{array}{lll|lll} &{\text { Nonsmokers }} & &&{\text { Smokers }} \\ \hline 4194 & 3522 & 3454 & 3998 & 3455 & 3066 \\ \hline 3062 & 3771 & 3783 & 3150 & 2986 & 2918 \\ \hline 3544 & 3746 & 4019 & 4216 & 3502 & 3457 \\ \hline 4054 & 3518 & 3884 & 3493 & 3255 & 3234 \\ \hline 4248 & 3719 & 3668 & 2860 & 3282 & 2746 \\ \hline 3128 & 3290 & 3423 & 3686 & 2851 & 3145 \\ \hline 3471 & 4354 & 3544 & 3807 & 3548 & 4104 \\ \hline 3994 & 2976 & 4067 & 3963 & 3892 & 2768 \\ \hline 3732 & 3823 & 3302 & 3769 & 3509 & 3629 \\ \hline 3436 & 3976 & 3263 & 4131 & 3129 & 4263 \\ \hline \end{array} $$ (a) Is this an observational study or a designed experiment? Why? (b) What is the explanatory variable? What is the response variable? (c) Can you think of any lurking variables that may affect the results of the study? (d) In the article, the researchers stated that "birthweights were adjusted for possible confounders $\ldots .$ "What does this mean? (e) Determine summary statistics (mean, median, standard deviation, quartiles) for each group. (f) Interpret the first quartile for both the nonsmoker and smoker group. (g) Draw a side-by-side box plot of the data. Does the side-byside boxplot confirm the conclusions of the study?

Name: Problem 18, Chapter 3: Statistics Informed Decisions Using Data
Uploaded: 2023-06-26T14:13:33-08:00
Duration: 7 min 59 s
Channel: Sheryl Ezze

   It is well documented that active maternal smoking during pregnancy is associated with lower-birth-weight babies. Researchers wanted to determine if there is a relationship between paternal smoking habits and birth weight. The researchers administered a questionnaire to each parent of newborn infants. One question asked whether the individual smoked regularly. Because the survey was administered within 15 days of birth, it was assumed that any regular smokers were also regular smokers during pregnancy. Birth weights for the babies (in grams) of nonsmoking mothers were obtained and divided into two groups, nonsmoking fathers and smoking fathers. The given data are representative of the data collected by the researchers. The researchers concluded that the birth weight of babies whose father smoked was less than the birth weight of babies whose father did not smoke.
$$
\begin{array}{lll|lll}
&{\text { Nonsmokers }} & &&{\text { Smokers }} \\
\hline 4194 & 3522 & 3454 & 3998 & 3455 & 3066 \\
\hline 3062 & 3771 & 3783 & 3150 & 2986 & 2918 \\
\hline 3544 & 3746 & 4019 & 4216 & 3502 & 3457 \\
\hline 4054 & 3518 & 3884 & 3493 & 3255 & 3234 \\
\hline 4248 & 3719 & 3668 & 2860 & 3282 & 2746 \\
\hline 3128 & 3290 & 3423 & 3686 & 2851 & 3145 \\
\hline 3471 & 4354 & 3544 & 3807 & 3548 & 4104 \\
\hline 3994 & 2976 & 4067 & 3963 & 3892 & 2768 \\
\hline 3732 & 3823 & 3302 & 3769 & 3509 & 3629 \\
\hline 3436 & 3976 & 3263 & 4131 & 3129 & 4263 \\
\hline
\end{array}
$$
(a) Is this an observational study or a designed experiment? Why?
(b) What is the explanatory variable? What is the response variable?
(c) Can you think of any lurking variables that may affect the results of the study?
(d) In the article, the researchers stated that "birthweights were adjusted for possible confounders $\ldots .$ "What does this mean?
(e) Determine summary statistics (mean, median, standard deviation, quartiles) for each group.
(f) Interpret the first quartile for both the nonsmoker and smoker group.
(g) Draw a side-by-side box plot of the data. Does the side-byside boxplot confirm the conclusions of the study?

Statistics Informed Decisions Using Data

Michael Sullivan III 5th Edition

Chapter 3, Problem 18

Instant Answer

Solved by Expert Sheryl Ezze

06/26/2023

Step 1

They simply observed and recorded the smoking habits of the parents and the birth weights of their babies. (b) The explanatory variable is the smoking habits of the fathers (nonsmokers or smokers). The response variable is the birth weight of the babies. (c) Show more…

Show all steps

Thanks for your feedback!

It is well documented that active maternal smoking during pregnancy is associated with lower-birth-weight babies. Researchers wanted to determine if there is a relationship between paternal smoking habits and birth weight. The researchers administered a questionnaire to each parent of newborn infants. One question asked whether the individual smoked regularly. Because the survey was administered within 15 days of birth, it was assumed that any regular smokers were also regular smokers during pregnancy. Birth weights for the babies (in grams) of nonsmoking mothers were obtained and divided into two groups, nonsmoking fathers and smoking fathers. The given data are representative of the data collected by the researchers. The researchers concluded that the birth weight of babies whose father smoked was less than the birth weight of babies whose father did not smoke. $$ \begin{array}{lll|lll} &{\text { Nonsmokers }} & &&{\text { Smokers }} \\ \hline 4194 & 3522 & 3454 & 3998 & 3455 & 3066 \\ \hline 3062 & 3771 & 3783 & 3150 & 2986 & 2918 \\ \hline 3544 & 3746 & 4019 & 4216 & 3502 & 3457 \\ \hline 4054 & 3518 & 3884 & 3493 & 3255 & 3234 \\ \hline 4248 & 3719 & 3668 & 2860 & 3282 & 2746 \\ \hline 3128 & 3290 & 3423 & 3686 & 2851 & 3145 \\ \hline 3471 & 4354 & 3544 & 3807 & 3548 & 4104 \\ \hline 3994 & 2976 & 4067 & 3963 & 3892 & 2768 \\ \hline 3732 & 3823 & 3302 & 3769 & 3509 & 3629 \\ \hline 3436 & 3976 & 3263 & 4131 & 3129 & 4263 \\ \hline \end{array} $$ (a) Is this an observational study or a designed experiment? Why? (b) What is the explanatory variable? What is the response variable? (c) Can you think of any lurking variables that may affect the results of the study? (d) In the article, the researchers stated that "birthweights were adjusted for possible confounders $\ldots .$ "What does this mean? (e) Determine summary statistics (mean, median, standard deviation, quartiles) for each group. (f) Interpret the first quartile for both the nonsmoker and smoker group. (g) Draw a side-by-side box plot of the data. Does the side-byside boxplot confirm the conclusions of the study?

Play audio

Feedback

Sheryl Ezze and 58 other subject Intro Stats / AP Statistics educators are ready to help you.

Ask a new question

Labs

Want to see this concept in action?

NEW

Explore this concept interactively to see how it behaves as you change inputs.

View Labs

Key Concepts

Side-by-Side Box Plots

Side-by-side box plots are graphical representations that display the distribution of two or more groups of data on the same scale. They succinctly show aspects such as the median, quartiles, and potential outliers, making it easier to visually compare the central tendencies and variability between groups, and to assess whether differences are present that support the study's conclusions.

Observational Study vs Designed Experiment

This concept involves distinguishing between studies where the investigator observes individuals and measures variables of interest without assigning treatments (observational study) versus studies where subjects are randomly assigned to treatment groups (designed experiments). In observational studies, the researcher does not intervene, which influences the ability to infer causal relationships due to potential confounding factors.

Explanatory and Response Variables

The explanatory variable is the one that is hypothesized to explain or cause changes in another variable, while the response variable is the outcome that is being studied. In the context of research, clearly identifying which variable is being manipulated or categorized (the explanatory) and which is observed as the effect (the response) is crucial for setting up the analysis.

Lurking and Confounding Variables

This concept refers to variables that are not included as part of the study but may influence both the explanatory and response variables. Lurking variables can create a false impression of a relationship, and confounders are specific types of lurking variables that can bias study findings by being related to both the treatment and the outcome.

Adjustment for Confounders

Adjusting for confounders means statistically controlling for variables that may distort the true relationship between the explanatory and response variables. This adjustment is done to isolate the effect of the primary variable of interest by reducing the bias introduced by these additional variables.

Summary Statistics

Summary statistics such as the mean, median, standard deviation, and quartiles provide a concise overview of the central tendency, spread, and distribution of a dataset. These statistics are essential tools for describing and comparing different groups in a study, offering insights into the overall pattern of the data.

Interpretation of Quartiles

Quartiles divide an ordered dataset into four equal parts, and the first quartile (25th percentile) represents the value below which 25% of the data fall. Interpreting quartiles helps in understanding the distribution of the data, specifically providing information about its lower range and outlier detection.

Please give Ace some feedback