Optimizing Hospital Infection Risk with Regression Analysis

Abstract

Milestone 2: Exploratory Data Analysis and Regression Overview and Objectives The objective of this project is to analyze data using regression analysis. As a reminder, regression analysis creates formulas to predict the value of one or more variables based on other variables we measure. You’ll also make inferences based on your regression data and determine which variables are significant in your model. This will help you identify the explanatory variables that best explain the variance in your response variable. Part One: Brain Size Excel Tasks: In the tab labeled “Brain Size”, please compute the following on your Excel sheet using the Head Size column. Five-Number Summary Interquartile Range and Lower/Upper Limits for outlier bounds, according to the IQR method. Identify whether any of the values are outliers, using the IQR method. Next, create a scatterplot: Create a scatterplot that shows the relationship between head size and brain weight. Include a regression equation and R-squared value in your scatterplot. Analysis of Results: Please respond in complete sentences to each question. According to your regression, what equation will you use to predict head size, given a person’s brain weight? According to your equation and r-squared statistic, what kind of relationship exists between head size and brain weight? Whenever datasets contain outliers, it’s important to ask yourself whether the outlier should be removed from your data before conducting further analysis. For example, if you see an outlier, and it’s obvious that the number was just a typo or the result of damaged measurement equipment, you should perform your analysis with AND without the outlier included, and you should explain why you omitted it the second time. Based on what you see in the data, are the outliers you see worth omitting? Why or why not? Do you think the other variables (Gender or Age Range) would also be significant in predicting brain weight along with head size? Why or why not? Part Two: Infection Risk in Hospitals Excel Tasks: Using the Infection Risk dataset, determine the following for the Age variable: Mean Median Mode Standard deviation Once you’ve found these measures, find a regression model that predicts the infection risk of patients using the other data recorded: Determine which columns/variables, apart from the InfctRisk column, might help you predict the chance...