Analytic Approach

The three questions below will guide the selection of appropriate methods to create data visualizations to show smoking cessation expenditures and to assess associations between smoking cessation program expenditures, smoking-related health care expenditures, and demographic factors.
  1. What is the response (Y) of interest and how is it measured? The primary responses of interest are total health care expenditures and cessation expenditures. Both of these are continuous variables.
  2. Are predictor variables mentioned in the problem statement? If so, how many and what are their measurement levels? Associations between smoking-related expenditures and the demographic factors land area, median household income, state gross domestic product, and tobacco production are of interest. These are all continuous variables.
  3. What are you being asked to deliver? A data description, an interval estimate, an answer to a question, or a predictive model? We are being asked to give a data description of smoking prevention programs and to assess the association with health care expenditures and demographic factors. Geospatial data is easily assimilated when plotted on maps and allows the audience to identify regional or geographic trends. Correlation analysis can be conducted to quantify the association between pairs of continuous variables.
Last updated: October 12, 2017
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