Module #10 Assignment

 

Module 18 Assignment


9.1 Analysis of Variance (ANOVA) and Regression Coefficients:


To conduct an ANOVA and interpret the coefficients for the model using the "cystfiber" data, use:



if (!exists("cystfiber")) {

  data("cystfibr")

}


model <- lm(formula = spemax ~ age + weight + bmp + fev1, data = cystfiber)


anova_result <- anova(model)


print(anova_result)


coefficients(model)


If the "cystfibr" data hasn't previously been loaded, this code loads it first. We then used the above formula to fit a linear regression model. To perform an ANOVA and present the findings, we utilize the anova function. Lastly, we use the coefficients function to print the regression coefficients.



9.2 Analysis of Log-Transformed Data and Regression Coefficients:


To analyze log-transformed data ad regression coefficients, you can log-transform the birth weight, as well as the abdominal and biparietal diameters, from the "secher" data.



if (!exists("secher")) {

  data("secher")

}


secher$log_bwt <- log(secher$bwt)

secher$log_ad <- log(secher$ad)

secher$log_bp <- log(secher$bp)


model <- lm(log_bwt ~ log_ad + log_bp, data = secher)


summary(model)


If it hasn't previously been loaded, we use this to load the "secher" data first. Subsequently, the birth weight, abdominal diameter, and biparietal diameter are log-transformed, resulting in the creation of additional variables labeled with "log_". With these log-transformed data, we then fit a linear regression model. Information about the model, including the regression coefficients you are interested in, can be found on the summary(model) line. The coefficients show the impact of the biparietal and abdominal log-transformed diameters on the log-transformed birth weight.


The summary output's "log_ad" and "log_bp" coefficient values can be used to understand the findings. As shown by your inquiry, the total of these coefficients will be close to 3. This represents the expected change in log-transformed birth weight for each unit change in log-transformed abdominal and biparietal diameters. The units of measurement and the context of your data determine how the coefficients should be interpreted.

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