We were assigned this project by our professor for STA 138. Jenny and I chose to become partners to work together.

We will be working with 2 datasets, baby and ischemic.

For the first dataset baby:

The goal is to investigate if the probability of low birth weight of infant is related to information on mother such as age, weight smoking status etc. The response variable is birth with values 1 (low birth weight), 0 (no low birth weight). We have to figure out how to use logistic regression to perform data summary, goodness-of-fit, and model selection. We than use the final model to estimate the percentage of correct classification. Our model came out to be 76% accurate for in the dataset accuracy. While the goal was to only determine the accuracy of in the dataset, it remains to be seen how accurate this model can be using other data not included in the dataset.

For the second dataset ischemic:

Data were collected by a health insurance company on its subscribers who had made claims resulting from ischemic (heart disease) for the time period of January 1, 1998 through December 31, 1999. The response is the number emergency room visits, and the goal is to model its mean as a function of 8 other variables. We than use Poisson regression to perform data summary, goodness-of-fit and model selection. The goal is to understand the model of the mean as a function of 8 variables.