3. The Child Health and Development Studies investigate a range of topics. One study considered allpregnancies between 1960 and 1967 among women in the Kaiser Foundation Health Plan in the SanFrancisco East Bay area. Here, we study the relationship between smoking and weight of the baby.The variable smoke is coded 1 if the mother is a smoker, and 0 if not. The summary table below showsthe results of a linear regression model for predicting the average birth weight of babies, measured inounces, based on the smoking status of the mother.EstimateStd. Errort value Pr(>It])(Intercept)123.050.65189.600.0000smoke-8.941.03-8.650.0000The variability within the smokers and non-smokers are about equal and the distributions are symmetric.With these conditions satisfied, it is reasonable to apply the model. (Note that we don't need to checklinearity since the predictor has only two levels.)(a) Write the equation of the regression model.(b) Interpret the slope in this context, and calculate the predicted birth weight of babies born tosmoker and non-smoker mothers.(c) Is there a statistically significant relationship between the average birth weight and smoking?

The regression is used to predict the value of an unknown variable using the known value of the…

3. The Child Health and Development Studies investigate a range of topics. One study considered all pregnancies between 1960 and 1967 among women in the Kaiser Foundation Health Plan in the San Francisco East Bay area. Here, we study the relationship between smoking and weight of the baby. The variable smoke is coded 1 if the mother is a smoker, and 0 if not. The summary table below shows the results of a linear regression model for predicting the average birth weight of babies, measured in ounces, based on the smoking status of the mother. Estimate Std. Error t value Pr(>|t|) (Intercept) 123.05 0.65 189.60 0.0000 smoke -8.94 1.03 -8.65 0.0000 The variability within the smokers and non-smokers are about equal and the distributions are symmetric. With these conditions satisfied, it is reasonable to apply the model. (Note that we don't need to check linearity since the predictor has only two levels.) (a) Write the equation of the regression model.

3. The Child Health and Development Studies investigate a range of topics. One study considered all pregnancies between 1960 and 1967 among women in the Kaiser Foundation Health Plan in the San Francisco East Bay area. Here, we study the relationship between smoking and weight of the baby. The variable smoke is coded 1 if the mother is a smoker, and 0 if not. The summary table below shows the results of a linear regression model for predicting the average birth weight of babies, measured in ounces, based on the smoking status of the mother. Estimate Std. Error t value Pr(>|t|) (Intercept) 123.05 0.65 189.60 0.0000 smoke -8.94 1.03 -8.65 0.0000 The variability within the smokers and non-smokers are about equal and the distributions are symmetric. With these conditions satisfied, it is reasonable to apply the model. (Note that we don't need to check linearity since the predictor has only two levels.) (a) Write the equation of the regression model.

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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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

3. The Child Health and Development Studies investigate a range of topics. One study considered all
pregnancies between 1960 and 1967 among women in the Kaiser Foundation Health Plan in the San
Francisco East Bay area. Here, we study the relationship between smoking and weight of the baby.
The variable smoke is coded 1 if the mother is a smoker, and 0 if not. The summary table below shows
the results of a linear regression model for predicting the average birth weight of babies, measured in
ounces, based on the smoking status of the mother.
Estimate
Std. Error
t value Pr(>It])
(Intercept)
123.05
0.65
189.60
0.0000
smoke
-8.94
1.03
-8.65
0.0000
The variability within the smokers and non-smokers are about equal and the distributions are symmetric.
With these conditions satisfied, it is reasonable to apply the model. (Note that we don't need to check
linearity since the predictor has only two levels.)
(a) Write the equation of the regression model.
(b) Interpret the slope in this context, and calculate the predicted birth weight of babies born to
smoker and non-smoker mothers.
(c) Is there a statistically significant relationship between the average birth weight and smoking?

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